BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
GRAFIK DAN VISUALISASI KOMPUTER – TSV 3323
COMPUTER GRAPHICS AND VISUALISATION – TSV 3323
3 Credit Hours
Prerequisite: None
Course Synopsis
The course provides an introduction and fundamental algorithms in computer graphics, their
theoretical as well as implementation aspects. The topics discussed include two and three
dimensional transformations, projections, view function, modeling and rendering. Elements of
multimedia and visualisation shall also be discussed in this course.
Course Outcomes
At the end of this course, students are able to:
1. Define and justify the fundamental concepts and techniques used in the field of
computer graphics and visualisation including history of computer graphics, concepts
and technologies.
2. Justify examples of current computer graphics applications, relating to the computer
graphics and military application.
3. Apply modern hardware and software technologies used in computer graphics and
battlefield environment.
4. Implement concepts and computer graphics programming to generate 2D and 3D
graphics primitives in battlefield application using OpenGL programming.
References
1. Marschner, S. & Shirley, P. (2016). Fundamentals of Computer Graphics. Fourth Edition.
Boca Raton: CRC Press, Taylor & Francis.
2. Hughes, J.F., van Dam, A., Foley, J.D., McGuire, M., Feiner, S.K., Sklar, D.F. & Akeley,
K. (2014). Computer Graphics: Principles and Practice. New Jersey: Addison-Wesley.
3. Hill, F.S. & Kelley, S.M. (2007). Computer Graphics Using OpenGL. Third Edition. India:
Pearson Prentice Hall.
123
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
SIMULASI DAN REKA BENTUK PEMODELAN KOMPUTER – TSV 3333
COMPUTER SIMULATION AND MODELLING DESIGN – TSV 3333
3 Credit Hours
Prerequisite: None
Course Synopsis
This course demonstrates to the students on how computers may be used to simulate the
behaviour of the real world systems by utilising mathematical models with an emphasis on
discrete system simulation. The simulation projects will be done using simulation software
packages and structured programming languages. Topics include chain of events, priority
queues, random numbers generation, and statistical analyses.
Course Outcomes
At the end of this course, students are able to:
1. Relate data structures for writing simulation programs and building simulation software.
2. Design mathematical and logical models to represent systems.
3. Identify real world systems using programming language with an emphasis on waiting
line systems.
4. Distinguish real world systems using a simulation language.
5. Construct statistical data analysis on the simulation of a system, by examining both input
and output and altering the model variables to address the problem for which the model
is designed.
References
1. Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2015). Discrete-Event System
Simulation. Fifth Edition. London: Pearson Education Limited.
2. Karian, Z.A. & Dudewicz, E.J. (1998). Modern Statistical, Systems, and GPSS
Simulation. Second Edition. Boca Raton: CRC Press.
3. Law, A.M. (2014). Simulation Modelling and Analysis. Fifth Edition. New York: McGraw-
Hill Education.
124
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
ANALITIK DAN PEMBANGUNAN DATA RAYA – TSV 3343
BIG DATA ANALYTICS AND DEVELOPMENT – TSV 3343
3 Credit Hours
Prerequisite: None
Course Synopsis
This course aims to provide an overview of advanced machine learning, data mining and
statistical techniques that arise in data analytic applications. In this course, students will learn
and practice data analytic techniques, including parallel algorithms, online algorithm, locality
sensitive hashing, topic modeling, structure learning, time-series analysis, and data
development techniques. One or more warfare applications associated with each technique will
also be discussed and applied.
Course Outcomes
At the end of this course, students are able to:
1. Describe the basic idea of big data analytics and development in warfare.
2. Explain the basic idea of advanced topic modeling techniques.
3. Apply warfare applications and design graphical model solutions to the problems.
References
1. Li, K.C., Jiang, H., Yang, L.T. & Cuzzocrea, A. (2015). Big Data: Algorithms, Analytics,
and Applications. Boca Raton: CRC Press.
2. Loshin, D. (2013). Big Data Analytics: From Strategic Planning to Enterprise Integration
with Tools, Techniques, NoSQL, and Graph. Waltham: Elsevier Science.
3. Services, E.M.C.E. (2015). Data Science and Big Data Analytics: Discovering,
Analysing, Visualising and Presenting Data. Indianapolis: John Wiley & Sons Inc.
125
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
BIDANG FOKUS: FORENSIK DIGITAL
FOCUS AREA: DIGITAL FORENSICS
FORENSIK SISTEM PEMFAILAN – TSF 3313
FILE SYSTEM FORENSICS – TSF 3313
3 Credit Hours
Prerequisite: None
Course Synopsis
In this course, students gain knowledge on the basic concepts and theories of a volume and file
system. Students will also learn how to implement it to an investigation. For each file system,
students will learn different analysis techniques and special considerations that an investigator
needs to decide. This course also teaches how the information could be used in an actual case
scenario.
Course Outcomes
At the end of this course, students are able to:
1. Explain the concepts of digital investigation.
2. Identify the components of volume analysis and types of partitions of a system.
3. Differentiate between file system and file allocation tables.
4. Analyse NTFS, Ext2 and Ext3 data structures.
5. Initiate file system forensics investigation by using file system forensics tools.
References
1. Carrier, B. (2005). File System Forensic Analysis. New Jersey: Pearson Education.
2. Malin, C.H., Casey, E. & Aquilina, J.M. (2012). Malware Forensics Field Guide for
Windows Systems: Digital Forensics Field Guides. Waltham: Elsevier Science.
3. Daniel, L. (2011). Digital Forensics for Legal Professionals: Understanding Digital
Evidence from the Warrant to the Courtroom. Waltham: Elsevier Science.
4. Hoog, A. & Strzempka, K. (2011). iPhone and iOS Forensics: Investigation, Analysis and
Mobile Security for Apple iPhone, iPad and iOS Devices. Waltham: Elsevier Science.
5. Elrick, D., & Lockhart, K. (2014). Forensic Examination of Windows-Supported File
Systems. California: CreateSpace Independent Publishing Platform.
126
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PENYIASATAN JENAYAH DIGITAL – TSF 3323
DIGITAL CRIME INVESTIGATION – TSF 3323
3 Credit Hours
Prerequisite: None
Course Synopsis
In this course, students gain knowledge on the field of computer crime. Basic criminal
techniques, the relevant of laws, computer forensics will be introduced to the students. Students
will also explore litigation such as depositions, expert reports and trials. This course is the
students’ gateway into the world of investigating computer crimes.
Course Outcomes
At the end of this course, students are able to:
1. Classify various types of computer crimes.
2. Explain the cyber laws of Malaysia.
3. Analyse computer forensic techniques.
4. Compose digital evidence from computer crime cases via computer forensic tools for the
purpose of litigation.
5. Identify the effect of computer crimes and individual threats.
References
1. Easttom, C. & Taylor, J. (2011). Computer Crime, Investigation, and the Law. Boston:
Course Technology.
2. Malaysia & Board, I.L.B.S.L.R. (2001). Cyber Laws of Malaysia: Contains Digital
Signature Act 1997 (Act 562), Computer Crimes Act 1997 (Act 563), Telemedicine Act
1997 (Act 564): as at 5 January 2001. Malaysia: International Law Book Services.
3. Widup, S. (2014). Computer Forensics and Digital Investigation with EnCase Forensic.
New York: McGraw-Hill Education.
4. Altheide, C. & Carvey, H. (2011). Digital Forensics with Open Source Tools. Waltham:
Elsevier Science.
5. Casey, E. (2010). Handbook of Digital Forensics and Investigation. Burlington: Elsevier
Academic Press.
127
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
FORENSIK DATA DAN MEDIA DIGITAL – TSF 3333
DATA AND DIGITAL MEDIA FORENSICS – TSF 3333
3 Credit Hours
Prerequisite: None
Course Synopsis
The area of digital media forensics is not just the art of finding deleted or hidden data but it is
also the understanding of the underlying technologies behind the various tools used and the
ability to present scientifically valid information. In this course, students will deal with the
collection, preservation and analysis of digital media such that the evidence can be successfully
presented in a court of law.
Course Outcomes
At the end of this course, students are able to:
1. Describe how to acquire digital evidence from various digital media.
2. Explain the underlying technologies behind the various tools used in digital media
analysis and forensics.
3. Analyse digital evidence using scientifically derived and proven methods that can be
used to facilitate or further the reconstruction of events in an investigation.
References
1. Bommisetty, S., Tamma, R., Skulkin, O. & Mahalik, H. (2018). Practical Mobile
Forensics. Third Edition. Birmingham: Packt Publishing.
2. EC-Council. (2016). Computer Forensics: Investigating Data and Image Files (CHFI).
Boston: Cengage Learning.
3. EC-Council. (2016). Computer Forensics: Investigating File and Operating Systems,
Wireless Networks, and Storage (CHFI). Boston: Cengage Learning.
4. Schroader, A. & Cohen, T. (2011). Alternate Data Storage Forensics. Burlington:
Elsevier Science.
128
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
FORENSIK DIGITAL - TSS 3323
DIGITAL FORENSICS - TSS 3323
3 Credit Hours
Prerequisite: None
Course Synopsis
Upon completing this course, the students will be able to practice the theory and skills
necessary to perform rudimentary computer forensic investigations such as discovering
evidences, recovering deleted data or damaged file information, understanding the role of
technology and tool needed in investigating computer-based crime (e.g. tracing the originator of
defamatory emails to recover signs of fraud), and dealing with the investigative bodies at
elementary level to prosecute the necessary evidence.
Course Outcomes
At the end of this course, students are able to:
1. Describe the concepts and techniques of digital forensics and its importance.
2. Construct sufficient knowledge of the digital forensic investigation.
3. Demonstrate a proper digital forensic investigation.
4. Combine digital forensics tools to conduct the investigation.
References
1. Michael W. Graves (2014). Digital Archaeology: The Art and Science of Digital
Forensics. Boston: Addison-Wesley Professional.
2. Anthony T. S. Ho, Shujun Li (2015). Handbook of Digital Forensics of Multimedia Data
and Devices. West Sussex: John Wiley & Sons Ltd.
3. A.J. Sammes, Brian Jenkinson (2013). Forensic Computing: A Practitioner’s Guide.
London: Springer-Verlag
4. Cowen, D. (2012). Computer Forensics A Beginner’s Guide. New York: McGraw-Hill
Osborne.
5. Volonino, Anzaldua & Godwin (2007). Computer Forensics: Principles and Practices.
New Jersey: Prentice Hall.
129
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
SINOPSIS KURSUS ELEKTIF
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER (KEPUJIAN) (ZC00)
FORENSIK RANGKAIAN – TSF 3723
NETWORK FORENSICS – TSF 3723
3 Credit Hours
Prerequisite: None
Course Synopsis
This course enables the understanding of how to recognise hackers' tracks and uncover the
network-based evidence. It provides an explanation on how to uncover suspicious e-mail
attachment from packet captures. The course also explores tracking intrusion via network and
understanding of encryption-cracking attacks and other related tracking mechanism and
techniques.
Course Learning Outcomes
At the end of this course, students are able to:
1. Describe methodologies for managing any network forensics investigation.
2. Analyse forensic evidence from multiple communication devices i.e routers, firewalls and
web proxies.
3. Derive a plan to manage network control in an organisation.
References
1. Davidoff, S. & Ham, J. (2012). Network Forensics: Tracking Hackers Through
Cyberspace. Westford: Pearson Education Inc.
2. Datt, S. (2016). Learning Network Forensics. Birmingham: Packt Publishing.
3. Messier, R. (2017). Network Forensics. Indianapolis: Wiley.
130
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PENGINTIPAN KETENTERAAN DAN INDUSTRI – TSF 3733
MILITARY AND INDUSTRY ESPIONAGE – TSF 3733
3 Credit Hours
Prerequisite: None
Course Synopsis
In this course, students will learn to define and describe the espionage. This module examines
the motivations for military and industrial espionage and the various methods of attack on the
physical security of an organisation, its electronic infrastructures and its staff and suppliers.
Students will learn to analyse and mitigate potential attacks through military and industrial
espionage, and will carry out risk management processes in military and industrial espionage.
Course Learning Outcomes
At the end of this course, students are able to:
1. Identify, defend and countermeasure potential attacks through military and industrial
espionage.
2. Differentiate the concept, types and characters of espionage.
3. Design and implement basic espionage behaviour.
4. Read and analyse military and industrial espionage.
References
1. Clancy, T. & Greaney, M. (2012). Threat Vector. New York: Penguin Publishing Group.
2. Stoll, C. (2012). Cuckoo’s Egg. New York: Knopf Doubleday Publishing Group.
3. Brown, A. (2011). The Grey Line: Modern Corporate Espionage and Counter
Intelligence. Columbus: Amur Strategic Research Group.
4. Winkler, I. (2005). Spies Among Us: How to Stop the Spies, Terrorists, Hackers, and
Criminals You Don’t Even Know You Encounter Every Day. Indianapolis: Wiley.
5. Carr, J. (2011). Inside Cyber Warfare: Mapping the Cyber Underworld. Sebastopol:
O’Reilly Media.
131
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
INTERAKSI MANUSIA-KOMPUTER - TSI 3723
HUMAN-COMPUTER INTERACTION - TSI 3723
3 Credit Hours
Prerequisite: None
Course Synopsis
This course is an introduction to the fundamentals of human-computer interaction, user interface
design and usability analysis. Students will learn principles and guidelines for usability,
quantitative and qualitative analysis methods besides apply them through critiques of existing
interfaces and development of new ones. Topics covered will also include cognitive models and
visual models. Students will learn the principles of visual design and prototyping methods that
inform effective interaction design.
Course Outcomes
At the end of this course, students are able to:
1. Distinguish between the types of knowledge produced in science, engineering and
design.
2. Explain the theoretical perspectives on cognition and human behaviour that are relevant
to the design of interactive systems.
3. Design an experimental study.
4. Develop one or more prototypes of a design by using prototypes in the design process.
References
1. Sharp, H., Rogers, Y. & Preece, J. (2015). Interaction Design: Beyond Human-Computer
Interaction. Fourth Edition. West Sussex: John Wiley & Sons.
2. Shneiderman, B., Plaisant, C., Cohen, M. & Jacobs, S. (2016). Designing the User
Interface: Strategies for Effective Human-Computer Interaction. Sixth Edition. Boston:
Addison-Wesley.
3. Don, N. (2013). The Design of Everyday Things. Revised and Expanded Edition. New
York: Basic Books.
4. Solis, T. (2016). Human-Computer Interaction: The Fundamentals Made Easy!
Charleston: CreateSpace Independent Publishing.
132
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
REALITI MAYA - TSI 3733
VIRTUAL REALITY - TSI 3733
3 Credit Hours
Prerequisite: None
Course Synopsis
The course teaches the fundamentals of Virtual Reality (VR) and provides laboratory
experiences where students learn how to develop immersive, interactive and animated 3D
computer models. Authoring tools like 3D Studio Max, VirTools and VRML will be introduced
and allowed for creating unique applications in the arts, engineering, humanities, medicine,
science or any other areas. The course emphasises on cross-discipline collaboration and
teamwork in group projects. Each team will develop a complete virtual reality application in the
area of interest.
Course Outcomes
At the end of this course, students are able to:
1. Describe and identify Virtual Reality Technology, the application and implications of VR
in various fields.
2. Explain the functionality of VR Technology and Human Senses that are related to VR
Technology.
3. Build and produce a VR application system in diverse fields.
References
1. LaValle, S.M. (2016). Virtual Reality. Boston: Cambridge University Press.
2. Blascovich, J. & Bailenson, J. (2012). Infinite Reality: The Hidden Blueprint of our Virtual
Lives. New York: William Morrow Paperbacks.
3. Jerald, J. (2015). The VR Book: Human-Centered Design for Virtual Reality. New York:
Morgan & Claypool Publishers, ACM Books.
133
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PENYELIDIKAN OPERASI – TSI 3743
OPERATIONAL RESEARCH - TSI 3743
3 Credit Hours
Prerequisite: None
Course Synopsis
This course is designed to expose students with modelling, solution and analysis of such
optimisation problems that are found in various industries and application areas. The use of
optimisation is common in computer science especially in artificial intelligence and computer
security. Examples of applications are widely encountered in transportation and logistics,
manufacturing environments, service operations, product design and development and so forth.
Topics include linear programming, transportation model, network model, project management,
and analytic hierarchy process.
Course Outcomes
At the end of this course, students are able to:
1. Understand and identify basic concepts of objectives, decision variables and constraints
correctly.
2. Demonstrate and apply their knowledge with the basic notions and techniques to
develop the algorithm and basic operations research.
3. Analyse a simple Operational Research problem using linear programming, network
model, transportation model and simulation model.
4. Identify, formulate and solve transportation, assignment, networks, queuing models and
simulation.
References
1. Anderson, S. & Williams, M. (2008). An Introduction to Management Science. Twelfth
Edition. Washington: Cengage Learning.
2. Frederick, S.H. & Gerald, J.L. (2009). Introduction to Operations Research. Seventh
Edition. New York: McGraw-Hill.
3. Hamdy, A.T. (2010). Operations Research: An Introduction. Ninth Edition. New Jersey:
Prentice Hall.
4. Stevenson, O. (2007). An Introduction to Management Science with Spreadsheets.
International Edition. New York: McGraw-Hill.
5. Wayne, L.W. (2004). Operations Research: Applications and Algorithms. Fourth Edition.
California: Duxbury Press.
134
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PENGURUSAN KESELAMATAN MAKLUMAT - TSS 3333
INFORMATION SECURITY MANAGEMENT - TSS 3333
3 Credit Hours
Prerequisite: None
Course Synopsis
The course introduces an understanding of information security management concepts,
including planning for security, security policy, risk management, law and ethics and advanced
cryptography. It will also provide the knowledge and skills needed to plan the implementation of
an information security management system that provides efficient, effective safeguards and
responds to the organisation’s needs.
Course Outcomes
At the end of this course, students are able to:
1. Understand the concepts of information security management.
2. Identify the issues and risks related to information security.
3. Provide understanding on security policy and resources involved in identifying secure
networks.
4. Understand standard methods and metrics in managing information security.
References
1. Whitman, M. & Mattord, H. (2010). Management of Information Security. Third Edition.
Boston: Thomson Course Technology.
2. Purser, S. (2004). A Practical Guide to Managing Information Security. London: Artech
House.
3. Krause, M. & Harold, F.T. (2012). Security Handbook of Information Management. Sixth
Edition. Boca Raton: Auerbach Publications.
4. Dhillon, G. (2007). Principles of Information System Security. New York: Wiley.
5. Andress, J. (2011). The Basics of Information Security: Understanding the
Fundamentals of Informaton Security in Theory and Practice. Maryland Heights:
Syngress.
135
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PENGGODAM BERETIKA - TSS 3353
ETHICAL HACKER - TSS 3353
3 Credit Hours
Prerequisite: None
Course Synopsis
The course introduces the knowledge on how hackers attack computers and networks and how
to protect systems from hackers. Students will learn legal restrictions and ethical guidelines, and
will be required to obey them. Students will perform hands-on labs such as port scanning,
footprinting, sniffing and other techniques used by computer hackers.
Course Outcomes
At the end of this course, students are able to:
1. Understand what an ethical hacker can and cannot do legally.
2. Learn more on hacking techniques and to protect the computer and networks.
3. Understand vulnerabilities in networks and systems.
4. Provide the best solution for their computers and networks.
References
1. EC-Council. (2010). Network Defense: Security and Vulnerability Assessment. Boston:
Course Technology Press.
2. Harris, S., Harper, A., Eagle, C. & Ness, J. (2011). Gray Hat Hacking: The Ethical
Hacker’s Handbook. Third Edition. New York: McGraw-Hill/Osborne.
3. Krutz, R.L. & Vines, R.D. (2008). The CEH Prep Guide: The Comprehensive Guide to
Certified Ethical Hacking. New York: Wiley Publishing.
4. McClure, S., Scambray, J. & Kurtz, G. (2009). Hacking Exposed Network Security
Secrets and Solutions. Sixth Edition. New York: McGraw-Hill/Osborne.
5. Simpson, M.T. (2011). Hands-on Ethical Hacking and Network Defense. Second Edition.
Boston: Course Technology Press.
136
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
AUDIO DAN VIDEO DIGITAL – TSV 3713
DIGITAL AUDIO AND VIDEO – TSV 3713
3 Credit Hours
Prerequisite: None
Course Synopsis
Students need to master this course well because it discusses the basic foundation knowledge
by all students who intend to specialise in this field later. Students from other specialisations will
also find this course attractive because audio and video technology has many applications in
various fields such as advertising, education, marketing, industrial and social.
Course Learning Outcomes
At the end of this course, students are able to:
1. Identify all elements of audio and video in multimedia applications.
2. Distinguish the appropriate audio and video techniques in a multimedia project
development.
3. Apply the proper techniques of audio and video knowledge in developing an audio and
video project.
References
1. Zettl, H. (2010). Video Basics 6. Boston: Wadsworth Cengage Learning.
2. Huber, D.M. & Runstein, R.E. (2017). Modern Recording Techniques. New York:
Routledge Taylor & Francis.
3. Cancellaro, J. (2006). Exploring Sound Design for Interactive Media. New York: Delmar
Learning.
4. Shaner, P. & Jones, G.E. (2004). Real World Digital Video. San Francisco: Peachpit
Press.
137
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
ANIMASI KOMPUTER – TSV 3723
COMPUTER ANIMATION – TSV 3723
3 Credit Hours
Prerequisite: None
Course Synopsis
In this course, students will learn how to define and describe animation concepts. This includes
demonstration on how to manipulate it to create animation design. To understand more about
animation, students should have to understand the animation concepts in advance.
Course Learning Outcomes
At the end of this course, students are able to:
1. Identify the importance of 2D animation.
2. Explain the concepts, types and steps in producing 2D animation process.
3. Compare the types of animation.
4. Apply all the animation knowledge to create 2D animation.
References
1. Williams, R. (2012). The Animator’s Survival Kit: A Manual of Methods, Principles and
Formulas for Classical, Computer, Games, Stop Motion and Internet Animators. New
York: Farrar, Straus and Giroux.
2. Corsaro, S. & Parrott, C.J. (2004). Hollywood 2D Digital Animation: The New Flash
Production Revolution. Boston: Cengage Learning PTR.
3. Georgenes, C. & Putney, J. (2010). Animation with Scripting for Adobe Flash
Professional CS5 Studio Techniques. Berkeley: Peachpit.
4. Blair, P. (1994). Cartoon Animation. Laguna Hill: Walter Foster Publishing.
5. Murphy, M. (2008). Beginner’s Guide to Animation. New York: Watson-Guptill
Publications.
6. White, T. (2012). Animation from Pencils to Pixels: Classical Techniques for the Digital
Animator. Burlington: Focal Press.
138
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PEMPROSESAN IMEJ DIGITAL - TSI 3333
DIGITAL IMAGE PROCESSING - TSI 3333
3 Credit Hours
Prerequisite: None
Course Synopsis
The course is designed to introduce students to theoretical concepts and practical issues
associated with image processing. The following topics are covered: image pre-processing,
image enhancement, image segmentation and analysis. A special effort will be made to develop
students' problem solving skills and engineering intuition in the subject area. Upon completion of
the course, the students should be knowledgeable and competent in applying the concepts, and
should be capable of reading advanced textbooks and research literature in the image-
processing field.
Course Outcomes
At the end of this course, students are able to:
1. Describe concepts and techniques of digital image processing through the study of most
important digital image models.
2. Construct sufficient knowledge to be able to reason about various technique of digital
image.
3. Build a complete digital image processing system
References
1. Gonzales, R.C. and Woods, R.E. (2017). Digital Image Processing. 4th Edition. New
Jersey: Prentice Hall.
2. Gonzales, R.C. , Woods, R.E. & Eddins, S.L. (2012). Digital Image Processing Using
MATLAB 2nd Edition. New Jersey: Prentice Hall.
3. McAndrew, A. (2015). A Computational Introduction to Digital Image Processing 2nd
Edition. Chapman and Hall/CRC.
4. Norliza, M.N. & Omar, M.R. (2009). Pemprosesan Imej untuk Pengguna Baru
Menggunakan MATLAB. Kuala Lumpur: Universiti Teknologi Malaysia.
5. Solomon, C. and Breckon, T. (2011). Fundamentals of Digital Image Processing: A
Practical Approach with Examples in MATLAB. Prentice Hall. 1st Edition. Wiley.
139
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
OBJEKTIF DAN HASIL PEMBELAJARAN
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER (SISTEM CERDAS) (ZC20)
Matlamat:
Matlamat program Ijazah Sarjana Muda Sains Komputer (Sistem Cerdas) adalah untuk
melahirkan graduan yang mempunyai kepimpinan intelektual yang berkarakter dalam bidang
Sains Komputer khususnya dalam bidang pengkhususan Sistem Cerdas dan Kepintaran
Buatan.
Objektif Pembelajaran Program
Programme Educational Objectives (PEO)
PEO 1 Graduan berupaya mengaplikasikan pengetahuan, prinsip,
kemahiran dan teknik asas terkini dalam reka bentuk,
pembangunan dan penyelidikan dalam bidang sistem cerdas dan
kepintaran buatan.
Graduates are able to apply the latest knowledge, principles, skills
and techniques in design, development and research in the field of
intelligent systems and artificial intelligence.
PEO 2 Graduan berupaya memikul kepimpinan, peranan profesional dan
pengurusan secara berkesan dalam memberi khidmat kepada
organisasi di mana mereka bekerja dan juga kepada Negara
dalam bidang sistem cerdas dan kepintaran buatan.
Graduates are able to effectively take on leadership, professional
and management roles in serving the organisation in which they
work and for the Nation in the field of intelligent systems and
artificial intelligence.
PEO 3 Graduan berupaya menyediakan perkhidmatan dalam bidang
sistem cerdas dan kepintaran buatan kepada masyarakat dan
juga keperluan pengkomputeran Negara.
Graduates are capable of providing services in the field of
intelligent systems and artificial intelligence to the public as well as
computing needs of the Nation.
140
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PEO 4 Graduan yang berupaya menunjukkan kemahiran keusahawanan
dan keperluan pembelajaran sepanjang hayat untuk
pembangunan karier dalam bidang sistem cerdas dan kepintaran
buatan yang berjaya.
Graduates who are capable of demonstrating entrepreneurial
skills and lifelong learning needs for successful career
development in the field of intelligent systems and artificial
intelligence.
Hasil Pembelajaran Program
Programme Learning Outcomes (PLO)
PLO 1 Graduan berupaya mengaplikasikan pengetahuan dalam prinsip,
teori dan teknik sistem cerdas dan kepintaran buatan dalam
pelbagai bidang aplikasi.
Graduates are able to apply knowledge in the principles, theories
and techniques of intelligent systems and artificial intelligence in a
variety of applications.
PLO 2 Graduan berkebolehan dari segi teknikal dan praktikal dalam
mengaplikasikan pendekatan saintifik dan alatan secara cekap
dan efektif dalam mereka bentuk dan membina atur cara
komputer yang berkualiti tinggi khususnya dalam bidang sistem
cerdas dan kepintaran buatan.
Graduates are technically and practically capable of applying
scientific approaches and tools efficiently and effectively in
designing and building high quality computer programs,
particularly in the areas of intelligent systems and artificial
intelligence.
PLO 3 Graduan berupaya berfikir secara kritikal dan analitik dalam
merancang, menganalisis, mereka bentuk dan melaksanakan
sistem cerdas dan kepintaran buatan dalam menyelesaikan
masalah dunia sebenar.
Graduates are able to think critically and analytically in designing,
analysing, designing and implementing intelligent systems and
141
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
artificial intelligence in solving real-world problems.
PLO 4 Graduan berupaya berkomunikasi dan bekerja sama ada secara
individu atau/dan berkumpulan secara efektif dalam bidang sistem
cerdas dan kepintaran buatan merentasi pelbagai konteks dan
pengguna.
Graduates are able to effectively communicate and work either
individually or / and in a group, in the field of intelligent systems
and artificial intelligence across multiple contexts and users.
PLO 5 Graduan yang bertanggungjawab dan berdedikasi untuk
berkhidmat dalam bidang sistem cerdas dan kepintaran buatan
kepada masyarakat dan Negara.
Graduates who are responsible and dedicated to serving in the
field of intelligent systems and artificial intelligence to the
community and the Nation.
PLO 6 Graduan berupaya mengekalkan pembangunan profesional dan
etika selaras dengan prinsip etika dan undang-undang dalam
bidang sistem cerdas dan kepintaran buatan.
Graduates are capable of maintaining professional and ethical
development in accordance with ethical and legal principles in the
areas of intelligent systems and artificial intelligence.
PLO 7 Graduan berupaya melibatkan diri dan menjalankan pembelajaran
sepanjang hayat secara kendiri untuk pembangunan akademik
dan kerjaya khususnya dalam bidang sistem cerdas dan
kepintaran buatan.
Graduates are capable of engaging and conducting lifelong
learning for academic and career development especially in the
areas of intelligent systems and artificial intelligence.
PLO 8 Graduan berkeupayaan membangunkan kemahiran
keusahawanan khususnya dalam bidang sistem cerdas dan
kepintaran buatan.
Graduates have the potential to develop entrepreneurial skills
142
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
especially in the areas of intelligent systems and artificial
intelligence.
PLO 9 Graduan yang berupaya menunjukkan kemahiran kepimpinan
dalam bidang sistem cerdas dan kepintaran buatan ke arah
pembangunan Negara.
Graduates who are capable of demonstrating leadership skills in
the field of intelligent systems and artificial intelligence towards
National development.
143
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
STRUKTUR KURSUS DAN JUMLAH KREDIT KEPERLUAN
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER (SISTEM CERDAS)
(ZC20)
JUMLAH KREDIT
Jumlah keperluan kredit yang perlu dipenuhi untuk bergraduat adalah seperti mana jadual di
bawah dan tempoh pengajian yang perlu diikuti adalah enam semester lazim dan dua semester
pendek. Pecahan kursus yang perlu diambil adalah seperti berikut:
KURSUS KREDIT
Kursus Universiti: 24 (+2)
i. Kursus Teras Universiti 6
ii. Kursus Elektif Universiti
63
Kursus Teras Program: 15
i. Teras Jabatan 12
ii. Teras Program 120 (+2)
Kursus Elektif Program
JUMLAH KREDIT UNTUK BERGRADUAT
KURSUS TERAS
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER (SISTEM CERDAS) (ZC20)
KURSUS TERAS JABATAN
Kursus-kursus Teras Jabatan adalah wajib diambil oleh semua pelajar di Jabatan Sains
Komputer seperti berikut:
KOD KURSUS NAMA KURSUS KREDIT
TSJ 3213 Discrete Mathematics 3
TSJ 3223 Statistics 3
TSK 3306 Project 6
TSK 330C Industrial Training 12
TSP 3213 Fundamentals of Programming 3
TSP 3223 Object-oriented Programming 3
TSP 3233 Data Structures 3
TSP 3243 Web Programming and Development 3
144
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
TST 3213 Computer Organisation and Architecture 3
TST 3223 Database Systems 3
TST 3233 Computer Networks 3
TST 3243 Operating Systems 3
TST 3253 Systems Analysis and Design 3
TST 3263 Computer and Network Security 3
TST 3273 Artificial Intelligence 3
TST 3283 Ethics and Professionalism in ICT 3
TST 3293 Software Engineering 3
63
JUMLAH KREDIT
KURSUS TERAS PROGRAM
Kursus-kursus Teras Program adalah wajib diambil oleh semua pelajar Program Ijazah Sarjana
Muda Sains Komputer (Sistem Cerdas) seperti berikut:
KOD KURSUS NAMA KURSUS KREDIT
TSI 3313 Computational Intelligence 3
TSI 3323 Data Mining 3
TSI 3333 Digital Image Processing 3
TSI 3343 Knowledge-based Systems 3
TSI 3353 Knowledge Acquisition Method 3
15
JUMLAH KREDIT
145
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
KURSUS ELEKTIF
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER (SISTEM CERDAS) (ZC20)
Bagi kursus Elektif Program, pelajar perlu memilih sebanyak 12 kredit sahaja. Kursus-kursus
Elektif Program adalah seperti berikut:
KOD KURSUS NAMA KURSUS KREDIT
TSI 3713 Multimedia 3
TSI 3723 Human-Computer Interaction 3
TSI 3733 Virtual Reality 3
TSI 3743 Operational Research 3
TSI 3753 Neural Network 3
TSS 3333 Information Security Management 3
146
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
STRUKTUR KURIKULUM
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER (SISTEM CERDAS) (ZC20)
TAHUN PERTAMA
KOD SEMESTER 1 KREDIT KOD SEMESTER 2 KREDIT
KURSUS 2 KURSUS 2
DUM 3022 NAMA KURSUS 2 MPU 3132 NAMA KURSUS 1
2
MPU 3142 Military Leadership 1 LLF 3XX1 Appreciation of Ethics (+1)
and Civilizations 2
LLE 3012 Philosophy and Currents (+1) LLA 3XX1 3
Issues Foreign Language II
LLF 3XX1 English for Academic 2 LLE 3032 3
Writing Foreign Language II
LLA 3XX1 3 TSJ 3223 (Audit) 3
MPU 3412 / Foreign Language I 3 Al-Ghazali’s Dialogue: 3
MPU 3422 English Communication 2
Foreign Language I 3 1
(Audit) 1 Statistics 1
Human Movement 1
Science / 2 TSP 3223 Object-oriented *20
Community Service *19/21 Programming **19
**20/22 ***19
TSJ 3213 Discrete Mathematics ***20/22 TST 3223 Database Systems
TSP 3213
Fundamentals of TST 3233 Computer Networks
TST 3213 Programming ALK 3112*
PLS 3111** Latihan Ketenteraan
Computer Organisation Umum*
and Architecture
PLS 3121** PALAPES 2**
PALAPES 1**
QKA 3111*** Kesatria Al-Fateh 1*** QKA 3121*** Kesatria Al-Fateh 2***
LLE 3042**** Basic Grammar and
Vocabulary****
JUMLAH KREDIT JUMLAH KREDIT
KOD SEMESTER PENDEK KREDIT
KURSUS NAMA KURSUS
TST 3283 Ethics and Professionalism in ICT 3
TST 3253 Systems Analysis and Design 3
JUMLAH KREDIT 6
147
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
TAHUN KEDUA
SEMESTER 3 SEMESTER 4
KOD NAMA KURSUS KREDIT KOD NAMA KURSUS KREDIT
KURSUS 2 KURSUS 2
Introduction to
DUS 3022 Strategic Studies DUS 3012 Military History 2
MPU 3312 / Nationhood in 2 DUS 3032 Military Law and Law of 2
MPU 3332 / World Politics / Armed Conflict 3
MPU 3342 Fiqh Keutamaan/ 3
Integrity and Anti - 3
Corruption 3
2
TST 3243 Operating Systems 3 MPU 3212 Basic Entrepreneurship
2
TST 3293 Software 3 TSI 3313 Computational 1
Engineering Intelligence *20
**19
TSP 3233 Data Structures 3 TSI 3323 Data Mining ***20
TSP 3243 Web Programming 3 TST 3273 Artificial Intelligence
TST 3263 and Development
ALK 3122* 3 TSX 3XX3 Elective I
Computer and
Network Security 2 QKS 3172* Tempur Tanpa
Senjata*
Latihan Ketenteraan
Umum*
PLS 3131** PALAPES 3** 1 QXX Kokurikulum***
YYY2***
QKA 3132*** Kesatria Al-Fateh 2 PLS 3141** PALAPES 4**
3*** JUMLAH KREDIT
*21/
JUMLAH KREDIT **20/
***21
KOD SEMESTER PENDEK KREDIT
KURSUS NAMA KURSUS 3
3
TSI 3343 Knowledge-based Systems
Elective II 6
TSX 3XX3
JUMLAH KREDIT
148
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
TAHUN KETIGA
SEMESTER 5 SEMESTER 6
NAMA KURSUS
KOD NAMA KURSUS KREDIT KOD Industrial Training KREDIT
KURSUS 3 KURSUS 12
Digital Image
TSI 3333 Processing TSK 330C 12
TSX 3XX3 Elective III 3
TSI 3353 Knowledge Acquisition 3
Method
TSK 3306 Project 6
TSX 3XX3 Elective IV 3
PLS 3151** PALAPES 5** 1
PLS 3161** PALAPES 6** 1 JUMLAH KREDIT
JUMLAH KREDIT
*18/
**20
***18
Nota:
* Diambil oleh Pegawai Kadet
** Diambil oleh Pelajar PALAPES
*** Diambil oleh Pelajar Awam
**** Diambil oleh pelajar yang mendapat Band 1 dan 2 dalam peperiksaan MUET
149
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
SINOPSIS KURSUS TERAS
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER (SISTEM CERDAS) (ZC20)
PERKOMPUTERAN PINTAR - TSI 3313
COMPUTATIONAL INTELLIGENCE - TSI 3313
3 Credit Hours
Prerequisite: None
Course Synopsis
Computational Intelligence is a software program that can sense its environment, choose
rational actions based on their percepts, and execute these actions. The course gives a broad
introduction to the new and rapidly expanding field of agent-based computing. It introduces the
key concepts and models of the field dealing both with the individual agents and with their
interactions.
Course Outcomes
At the end of this course, students are able to:
1. Describe and identify the concept of intelligent agents and multi-agents system.
2. Explain and compare agent-based systems with other software applications.
3. Build and produce an intelligent agent-based system for a practical application.
References
1. Wooldridge, M. (2009). An Introduction to MultiAgent Systems. New York: Wiley and
Sons.
2. Padgham, L. & Winikoff, M. (2004). Developing Intelligent Agent Systems: A Practical
Guide. New York: John Wiley & Sons.
3. Bui, T.D., Tuong, V.H. & Quang, T.H. (2008). Intelligent Agents and Multi-Agent
Systems. 11th. Pacific Rim International Conference on Multi-Agents. PRIMA 2008,
Hanoi, Vietnam, December 15-16, Proceedings.
4. Dignum, F., Bradshaw, J., Silverman, B.G. & Doesburg, W.V. (2010). Agents for Games
and Simulations: Trends in Techniques, Concepts and Design. London: Springer.
5. Pechoucek, M., Thompson, S.G. & Voos, H. (2008). Defence Industry Applications of
Autonomous Agents and Multi-Agent Systems. London: Springer.
150
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PERLOMBONGAN DATA - TSI 3323
DATA MINING - TSI 3323
3 Credit Hours
Prerequisite: None
Course Synopsis
The course introduces the concept and techniques of data mining. The main topics discussed
include knowledge discovery process, data preprocessing and data mining techniques such as
decision tree, regression, neural network, and clustering. The course will teach the students to
find hidden pattern of information from large volume of data using selected data mining tools.
Course Outcomes
At the end of this course, students are able to:
1. Describe and identify basic concepts of a knowledge discovery process, data
preprocessing and data mining techniques.
2. Explain and summarise data preprocessing steps, and data mining techniques.
3. Apply the data mining techniques for a given data set.
4. Analyse the data mining model and output values correctly.
References
1. Han, J. & Kamber, M. (2011). Data Mining: Concepts and Techniques. Third Edition.
Massachusetts: Morgan Kaufmann Publisher.
2. Georges, J. (2008). Applied Analytics using SAS Enterprise Miner Course Notes. Cary,
NC: SAS Institute Inc.
3. Tan, P.N., Steinbach, M. & Kumar, V. (2006). Introduction to Data Mining. Boston:
Pearson Addison-Wesley.
4. Cerrito, P.B. (2007). Introduction to Data Mining using SAS Enterprise Miner. Cary, NC:
SAS Institute Inc.
5. Roiger, R.J. & Geatz, M.W. (2003). Data Mining: A Tutorial-based Primer. Boston:
Pearson Addison-Wesley.
151
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PEMPROSESAN IMEJ DIGITAL - TSI 3333
DIGITAL IMAGE PROCESSING - TSI 3333
3 Credit Hours
Prerequisite: None
Course Synopsis
The course is designed to introduce students to theoretical concepts and practical issues
associated with image processing. The following topics are covered: image preprocessing,
image enhancement, image segmentation and analysis. A special effort will be made to develop
students' problem solving skills and engineering intuition in the subject area. Upon completion of
the course, the students should be knowledgeable and competent in applying the concepts, and
should be capable of reading advanced textbooks and research literature in the image-
processing field.
Course Outcomes
At the end of this course, students are able to:
1. Describe concepts and techniques of digital image processing through the study of the
most important digital image models.
2. Construct sufficient knowledge to be able to reason about various techniques of digital
image.
3. Build a complete digital image processing system
References
1. Gonzales, R.C. and Woods, R.E. (2017). Digital Image Processing. 4th Edition. New
Jersey: Prentice Hall.
2. Gonzales, R.C. , Woods, R.E. & Eddins, S.L. (2012). Digital Image Processing Using
MATLAB 2nd Edition. New Jersey: Prentice Hall.
3. McAndrew, A. (2015). A Computational Introduction to Digital Image Processing 2nd
Edition. Chapman and Hall/CRC.
4. Norliza, M.N. & Omar, M.R. (2009). Pemprosesan Imej untuk Pengguna Baru
Menggunakan MATLAB. Kuala Lumpur: Universiti Teknologi Malaysia.
5. Solomon, C. and Breckon, T. (2011). Fundamentals of Digital Image Processing: A
Practical Approach with Examples in MATLAB. Prentice Hall. 1st Edition. Wiley.
152
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
SISTEM BERASASKAN PENGETAHUAN - TSI 3343
KNOWLEDGE-BASED SYSTEMS - TSI 3343
3 Credit Hours
Prerequisite: None
Course Synopsis
This course provides the students with the knowledge and understanding of knowledge-based
systems and their applications, in particular expert systems, Such systems are platforms for the
use of fuzzy logic to handle uncertainties. This course introduces the concept of fuzzy logic and
fuzzy theory sets including fuzzy relations, construction of membership functions and fuzzy
arithmetic. This course will discuss the three important phases in Fuzzy Logic – fuzzification,
fuzzy rules/inference, and defuzzification, culminating in a fuzzy system development.
Course Outcomes
At the end of this course, students are able to:
1. Explain the structure and design of Knowledge-based Systems, in particular expert
systems, and identifying their strengths and shortcomings.
2. Understand and construct Knowledge Base or Expert System applications.
3. Explain and analyse the fundamental concepts of fuzzy logic, and Identify the
appropriate techniques in fuzzy logic problem solving.
4. Construct fuzzy rule-based systems, in particular using MATLAB.
References
1. Joseph, G. & Gary, R. (2005). Expert Systems: Principles and Programming. Boston:
PWS Publishing Company.
2. Durkin, J. (1994). Expert Systems: Design and Development. New Jersey: Prentice Hall.
3. Padhy, N. (2006). Artificial Intelligence and Intelligent Systems. Third Edition. Oxford:
Oxford University Press.
4. Jones, T. (2008). Artificial Intelligence: A System Approach. Sudbury: Infinity Science
Press.
5. Belohlavek, R. & Klir, G.J. (2011). Concepts and Fuzzy Logic. Boston: The MIT Press.
153
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
KAEDAH PEROLEHAN PENGETAHUAN - TSI 3353
KNOWLEDGE ACQUISITION METHOD - TSI 3353
3 Credit Hours
Prerequisite: None
Course Synopsis
This course covers various forms of knowledge representation to be used as the goal for
knowledge acquisition. The various methods for knowledge acquisition are then covered,
manual and semi-automated, leading towards fully-automated.
Course Outcomes
At the end of this course, students are able to:
1. Know the fundamentals of knowledge representation and the formalisms.
2. Convert knowledge into various forms of knowledge representation.
3. Apply at least one method of knowledge acquisition.
References
1. Jakus G., Milutinovic, V., Omerovic, S., Tomazic, S. (2013). Concepts, Ontologies, and
Knowledge Representation. Austria: Springer.
2. Milton, N.R. (2007). Knowledge Acquisition in Practice: A Step-By-Step Guide. Austria:
Springer.
3. Brachman, R.J. & Levesque, H.J. (2003). Knowledge Representation and Reasoning.
Burlington: Morgan Kaufman Publishers, Elsevier.
154
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
SINOPSIS KURSUS ELEKTIF PROGRAM
SARJANA MUDA SAINS KOMPUTER (SISTEM CERDAS) (ZC20)
MULTIMEDIA - TSI 3713
MULTIMEDIA - TSI 3713
3 Credit Hours
Prerequisite: None
Course Synopsis
Students need to master this course well because it Identifies all multimedia elements and
distinguishes the appropriate audio and video techniques in a multimedia project development.
The students will also apply the proper techniques of multimedia knowledge in developing a
multimedia project. Students from other specialisations will also find this course attractive
because multimedia technology has many applications in various fields such as advertising,
education, marketing, industrial and social.
Course Outcomes
At the end of this course, students are able to:
1. Define concepts and techniques of multimedia computing and its importance.
2. Gain sufficient knowledge on the multimedia elements and its application.
3. Distinguish the appropriate multimedia techniques in a multimedia project development.
4. Apply the proper techniques of multimedia knowledge in developing a multimedia
project.
References
1. Gerald, F. & Ramesh, J. (2014). Multimedia Computing. Boston: Cambridge University
Press.
2. Cancellero, J. (2006). Exploring Sound Design for Interactive Media. Canada: Thomson
Delmar Learning.
3. Shaner, P. & Jone, G.E. (2004). Real World Digital Video. Second Edition. San
Francisco: Peachpit Press.
4. Ozer, J. (2004). Guide to Digital Video. New York: Wiley Publishing.
155
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
INTERAKSI MANUSIA-KOMPUTER - TSI 3723
HUMAN-COMPUTER INTERACTION - TSI 3723
3 Credit Hours
Prerequisite: None
Course Synopsis
This course is an introduction to the fundamentals of human-computer interaction, user interface
design and usability analysis. Students will learn principles and guidelines for usability,
quantitative and qualitative analysis methods besides apply them through critiques of existing
interfaces and development of new ones. Topics covered will also include cognitive models and
visual models. Students will learn the principles of visual design and prototyping methods that
inform effective interaction design.
Course Outcomes
At the end of this course, students are able to:
1. Distinguish between the types of knowledge produced in science, engineering and
design.
2. Explain the theoretical perspectives on cognition and human behaviour that are relevant
to the design of interactive systems.
3. Design an experimental study.
4. Develop one or more prototypes of a design by using prototypes in the design process.
References
1. Sharp, H., Rogers, Y. & Preece, J. (2015). Interaction Design: Beyond Human-Computer
Interaction. Fourth Edition. West Sussex: John Wiley & Sons.
2. Shneiderman, B., Plaisant, C., Cohen, M. & Jacobs, S. (2016). Designing the User
Interface: Strategies for Effective Human-Computer Interaction. Sixth Edition. Boston:
Addison-Wesley.
3. Don, N. (2013). The Design of Everyday Things. Revised and Expanded Edition. New
York: Basic Books.
4. Solis, T. (2016). Human-Computer Interaction: The Fundamentals Made Easy!
Charleston: CreateSpace Independent Publishing.
156
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
REALITI MAYA - TSI 3733
VIRTUAL REALITY - TSI 3733
3 Credit Hours
Prerequisite: None
Course Synopsis
The course teaches the fundamentals of Virtual Reality and provides laboratory experiences
where students learn how to develop immersive, interactive and animated 3D computer.
Authoring tools like 3D Studio Max, VirTools and VRML will introduced and allow for creating
unique applications in the arts, engineering, humanities, medicine, science or any other areas.
The course emphasises cross-discipline collaboration and teamwork in group projects. Each
team will develop a complete virtual reality application in the area of interest.
Course Outcomes
At the end of this course, students are able to:
1. Describe and identify Virtual Reality Technology, the application and implications of
Virtual Reality (VR) in variety fields.
2. Explain the functionality of VR Technology and Human Senses that are related to VR
Technology.
3. Build and produce a VR application system in diversity fields.
References
1. LaValle, S.M. (2016). Virtual Reality. Boston: Cambridge University Press.
2. Blascovich, J. & Bailenson, J. (2012). Infinite Reality: The Hidden Blueprint of our Virtual
Lives. New York: William Morrow Paperbacks.
3. Jerald, J. (2015). The VR Book: Human-Centered Design for Virtual Reality. New York:
Morgan & Claypool Publishers, ACM Books.
157
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PENYELIDIKAN OPERASI – TSI 3743
OPERATIONAL RESEARCH - TSI 3743
3 Credit Hours
Prerequisite: None
Course Synopsis
This course is designed to expose students with modelling, solution and analysis of such
optimisation problems that are found in various industries and application areas. The use of
optimisation is common in computer science especially in artificial intelligence and computer
security. Examples of applications are widely encountered in transportation and logistics,
manufacturing environments, service operations, product design and development and so forth.
Topics include linear programming, transportation model, network model, project management,
and analytic hierarchy process.
Course Outcomes
At the end of this course, students are able to:
1. Understand and identify basic concepts of objectives, decision variables and constraints
correctly.
2. Demonstrate and apply their knowledge with the basic notions and techniques to
develop the algorithmal and basic operations research.
3. Analyse a simple Operational Research problem using linear programming, network
model, transportation model and simulation model.
4. Identify, formulate and solve transportation, assignment, networks, queuing models and
simulation.
References
1. Anderson, S. & Williams, M. (2008). An Introduction to Management Science. Twelfth
Edition. Washington: Cengage Learning.
2. Frederick, S.H. & Gerald, J.L. (2009). Introduction to Operations Research. Seventh
Edition. New York: McGraw-Hill.
3. Hamdy, A.T. (2010). Operations Research: An Introduction. Ninth Edition. New Jersey:
Prentice Hall.
4. Stevenson, O. (2007). An Introduction to Management Science with Spreadsheets.
International Edition. New York: McGraw-Hill.
5. Wayne, L.W. (2004). Operations Research: Applications and Algorithms. Fourth Edition.
California: Duxbury Press.
158
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
RANGKAIAN NEURAL - TSI 3753
NEURAL NETWORKS - TSI 3753
3 Credit Hours
Prerequisite: None
Course Synopsis
This course covers the theoretical and practical aspects of Artificial Neural Network (ANN) that
starts with the introduction of ANN, followed by discussions of ANN types that include neural
network with supervised learning, neural network with unsupervised learning and recurrent
neural networks. For each type of ANN, several popular learning algorithms are taught and
implemented. At the end of this course, a number of ANN applications are also studied and
discussed. In addition, students are also guided to design and develop suitable ANN
application based on given problems.
Course Outcomes
At the end of this course, students are able to:
1. Understand the concepts and techniques of neural networks through the study of most
important neural network models.
2. Gain sufficient theoretical knowledge to be able to reason about the behaviour of neural
networks.
3. Evaluate whether neural networks are appropriate to a particular application.
4. Apply neural networks to a particular application such as for character recognition or
signal restoration.
References
1. Callan, R. (1999). The Essence of Neural Networks. New Jersey: Prentice Hall.
2. Fausset, L. (1993). Fundamentals of Neural Networks: Architecture, Algorithm and
Application. New Jersey: Prentice Hall.
3. Haykin, S. (2009). Neural Networks and Learning Machines. Third Edition. New Jersey:
Prentice Hall.
4. Haykin, S. (1998). Neural Networks: A Comprehensive Foundation. Third Edition. New
Jersey: Prentice Hall.
5. Kumar, S. (2010). Neural Networks: A Classroom Approach. Tenth Reprint. New Delhi:
McGraw-Hill.
159
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PENGURUSAN KESELAMATAN MAKLUMAT - TSS 3333
INFORMATION SECURITY MANAGEMENT - TSS 3333
3 Credit Hours
Prerequisite: None
Course Synopsis
The course introduces an understanding of information security management concepts,
including planning for security, security policy, risk management, law and ethics and advanced
cryptography. It will also provide the knowledge and skills needed to plan the implementation of
an information security management system that provides efficient, effective safeguards and
responds to the organisation’s needs.
Course Outcomes
At the end of this course, students are able to:
1. Understand the concepts of information security management.
2. Identify the issues and risks related to information security.
3. Provide understanding on security policy and resources involved in identifying secure
networks.
4. Understand standard methods and metrics in managing information security.
References
1. Whitman, M. & Mattord, H. (2010). Management of Information Security. Third Edition.
Boston: Thomson Course Technology.
2. Purser, S. (2004). A Practical Guide to Managing Information Security. London: Artech
House.
3. Krause, M. & Harold, F.T. (2012). Security Handbook of Information Management. Sixth
Edition. Boca Raton: Auerbach Publications.
4. Dhillon, G. (2007). Principles of Information System Security. New York: Wiley.
5. Andress, J. (2011). The Basics of Information Security: Understanding the
Fundamentals of Informaton Security in Theory and Practice. Maryland Heights:
Syngress.
160
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
OBJEKTIF DAN HASIL PEMBELAJARAN
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER
(KESELAMATAN SISTEM KOMPUTER) (ZC27)
Matlamat:
Matlamat program Ijazah Sarjana Muda Sains Komputer (Keselamatan Sistem Komputer)
adalah untuk melahirkan graduan yang mempunyai kepimpinan intelektual yang berkarakter
dalam bidang Sains Komputer khususnya dalam pengkhususan bidang Keselamatan Sistem
Komputer.
Objektif Pembelajaran Program
Programme Educational Objectives (PEO)
PEO 1 Graduan berupaya mengaplikasikan pengetahuan, prinsip,
kemahiran dan teknik asas terkini dalam reka bentuk,
pembangunan dan penyelidikan dalam bidang keselamatan
sistem komputer.
Graduates are able to apply the latest knowledge, principles, skills
and techniques in the design, development and research of
computer systems security.
PEO 2 Graduan berupaya memikul kepimpinan, peranan profesional dan
pengurusan secara berkesan dalam memberi khidmat kepada
organisasi di mana mereka bekerja dan juga kepada Negara
dalam bidang keselamatan sistem komputer.
Graduates are able to effectively take on leadership, professional
and management roles in serving the organisations in which they
work and for the Nation in computer systems security.
PEO 3 Graduan berupaya menyediakan perkhidmatan dalam bidang
keselamatan sistem komputer kepada masyarakat dan juga
keperluan pengkomputeran Negara.
Graduates are able to provide services in the field of computer
systems security to the public as well as the Nation’s computing
needs.
161
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PEO 4 Graduan yang berupaya menunjukkan kemahiran keusahawanan
dan keperluan pembelajaran sepanjang hayat untuk
pembangunan karier dalam bidang keselamatan sistem komputer
yang berjaya.
Graduates who are capable of demonstrating entrepreneurship
skills and lifelong learning requirements for successful career
development in the field of computer systems security.
Hasil Pembelajaran Program
Programme Learning Outcomes (PLO)
PLO 1 Graduan berupaya mengaplikasikan pengetahuan dalam prinsip,
teori dan teknik keselamatan sistem komputer dalam pelbagai
bidang aplikasi.
Graduates are able to apply knowledge in the principles, theories
and techniques of computer systems security in a variety of
applications.
PLO 2 Graduan berkebolehan dari segi teknikal dan praktikal dalam
mengaplikasikan pendekatan saintifik dan alatan secara cekap
dan efektif dalam mereka bentuk dan membina atur cara
komputer yang berkualiti tinggi khususnya dalam bidang
keselamatan sistem komputer.
Graduates are technically and practically capable of applying
scientific approaches and tools efficiently and effectively in
designing and building high quality computer programs,
particularly in the field of computer systems security.
PLO 3 Graduan berupaya berfikir secara kritikal dan analitik dalam
merancang, menganalisis, mereka bentuk dan melaksanakan
keselamatan sistem komputer dalam menyelesaikan masalah
dunia sebenar.
Graduates are able to think critically and analytically in designing,
analysing, designing and implementing computer system security
in real-world problems.
162
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PLO 4 Graduan berupaya berkomunikasi dan bekerja sama ada secara
individu atau/dan berkumpulan secara efektif dalam bidang
keselamatan sistem komputer merentasi pelbagai konteks dan
pengguna.
Graduates are able to effectively communicate and work either
individually or / and in a group, in the field of computer systems
security across multiple contexts and users.
PLO 5 Graduan yang bertanggungjawab dan berdedikasi untuk
berkhidmat dalam bidang keselamatan sistem komputer kepada
masyarakat dan Negara.
Graduates who are responsible and dedicated to serve in the field
of computer systems security to the community and the Ntate.
PLO 6 Graduan berupaya mengekalkan pembangunan profesional dan
etika selaras dengan prinsip etika dan undang-undang dalam
bidang keselamatan sistem komputer.
Graduates are capable of maintaining professional and ethical
development in accordance with ethical and legal principles in the
field of computer systems security.
PLO 7 Graduan berupaya melibatkan diri dan menjalankan pembelajaran
sepanjang hayat secara kendiri untuk pembangunan akademik
dan kerjaya khususnya dalam bidang keselamatan sistem
komputer.
Graduates are capable of engaging and conducting lifelong
learning for academic and career development especially in the
field of computer systems security.
PLO 8 Graduan berkeupayaan membangunkan kemahiran
keusahawanan khususnya dalam bidang keselamatan sistem
komputer.
Graduates have the potential to develop entrepreneurial skills
especially in computer systems security.
163
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
PLO 9 Graduan yang berupaya menunjukkan kemahiran kepimpinan
dalam bidang keselamatan sistem komputer ke arah
pembangunan Negara.
Graduates who are capable of demonstrating leadership skills in
the field of computer systems towards National development.
164
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
STRUKTUR KURSUS DAN JUMLAH KREDIT KEPERLUAN
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER
(KESELAMATAN SISTEM KOMPUTER) (ZC27)
JUMLAH KREDIT
Jumlah keperluan kredit yang perlu dipenuhi untuk bergraduat adalah seperti mana jadual di
bawah dan tempoh pengajian yang perlu diikuti adalah enam semester lazim dan dua semester
pendek. Pecahan kursus yang perlu diambil adalah seperti berikut:
KURSUS KREDIT
Kursus Universiti: 24 (+2)
i. Kursus Teras Universiti 6
ii. Kursus Elektif Universiti
63
Kursus Teras Program: 15
i. Teras Jabatan 12
ii. Teras Program 120 (+2)
Kursus Elektif Program
JUMLAH KREDIT UNTUK BERGRADUAT
KURSUS TERAS PROGRAM
SARJANA MUDA SAINS KOMPUTER
(KESELAMATAN SISTEM KOMPUTER) (ZC27)
KURSUS TERAS JABATAN
Kursus-kursus Teras Jabatan adalah wajib diambil oleh semua pelajar di Jabatan Sains
Komputer seperti berikut:
KOD KURSUS NAMA KURSUS KREDIT
TSJ 3213 Discrete Mathematics 3
TSJ 3223 Statistics 3
TSK 3306 Project 6
TSK 330C Industrial Training 12
TSP 3213 Fundamentals of Programming 3
TSP 3223 Object-oriented Programming 3
TSP 3233 Data Structures 3
TSP 3243 Web Programming and Development 3
165
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
TST 3213 Computer Organisation and Architecture 3
TST 3223 Database Systems 3
TST 3233 Computer Networks 3
TST 3243 Operating Systems 3
TST 3253 Systems Analysis and Design 3
TST 3263 Computer and Network Security 3
TST 3273 Artificial Intelligence 3
TST 3283 Ethics and Professionalism in ICT 3
TST 3293 Software Engineering 3
63
JUMLAH KREDIT
KURSUS TERAS PROGRAM
Kursus-kursus Teras Program adalah wajib diambil oleh semua pelajar program Ijazah Sarjana
Muda Sains Komputer (Keselamatan Sistem Komputer) seperti berikut:
KOD KURSUS NAMA KURSUS KREDIT
TSS 3313 Cryptography 3
TSS 3323 Digital Forensics 3
TSS 3333 Information Security Management 3
TSS 3343 Wireless Network Security 3
TSS 3353 Ethical Hacker 3
15
JUMLAH KREDIT
166
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
KURSUS ELEKTIF
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER
(KESELAMATAN SISTEM KOMPUTER) (ZC27)
Bagi kursus Elektif Program, pelajar perlu memilih sebanyak 12 kredit sahaja. Kursus-kursus
Elektif Program adalah seperti berikut:
KOD KURSUS NAMA KURSUS KREDIT
TSI 3713 Multimedia 3
TSI 3723 Human-Computer Interaction 3
TSS 3713 Firewalls and Virtual Private Networks 3
TSS 3733 Defensive Programming 3
TSS 3743 Network Intrusion Detection System 3
TSS 3753 Digital Certificates and Public Key Infrastructure 3
167
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
STRUKTUR KURIKULUM
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER
(KESELAMATAN SISTEM KOMPUTER) (ZC27)
TAHUN PERTAMA
KOD SEMESTER 1 KREDIT KOD SEMESTER 2 KREDIT
KURSUS NAMA KURSUS KURSUS 2
MPU 3132 NAMA KURSUS 1
DUM 3022 Military Leadership 2 LLF 3XX1
Appreciation of Ethics (+1)
MPU 3142 Philosophy and Currents 2 LLA 3XX1 and Civilizations 3
Issues TSJ 3223 3
LLE 3012 English for Academic 2 TSP 3223 Foreign Language II
LLF 3XX1 Writing 1 3
LLA 3XX1 Foreign Language I (+1) TST 3223 Foreign Language II 3
MPU 3412 / Foreign Language I TST 3233 (Audit) 2
MPU 3422 (Audit) 2 LLE 3032 Statistics
TSJ 3213 3 Object-oriented 2
TSP 3213 Human Movement Science 3 ALK 3112* Programming 1
/ Community Service PLS 3121** 1
TST 3213 Discrete Mathematics 3 QKA 3121*** Database Systems
PLS 3111** Fundamentals of 1 *21
QKA 3111*** Programming 1 Computer Networks **20
Computer Organisation Al-Ghazali’s Dialogue: ***20
and Architecture English Communication
PALAPES 1** Latihan Ketenteraan
Kesatria Al-Fateh 1*** Umum*
PALAPES 2**
Kesatria Al-Fateh 2***
LLE 3042**** Basic Grammar and 2 JUMLAH KREDIT
Vocabulary****
*19/21
JUMLAH KREDIT **20/22
***20/22
KOD SEMESTER PENDEK KREDIT
KURSUS NAMA KURSUS 3
TST 3253 Systems Analysis and Design
TST 3283 Ethics and Professionalism in ICT 3
JUMLAH KREDIT 6
168
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
TAHUN KEDUA
SEMESTER 3 SEMESTER 4
KOD NAMA KURSUS KREDIT KOD NAMA KURSUS KREDIT
KURSUS 2 KURSUS 2
Introduction to 2
DUS 3022 Strategic Studies 3 DUS 3012 Military History
MPU 3312 / Nationhood in
World Politics / DUS 3032 Military Law and Law of 2
MPU 3332 Fiqh Keutamaan Armed Conflict
TST 3243 Operating Systems MPU 3212 Basic Entrepreneurship 2
TSP 3233 Data Structures 3 TSS 3313 Cryptography 3
3 TSS 3353 Ethical Hacker 3
TSP 3243 Web Programming 3 TST 3273 Artificial Intelligence 3
TST 3263 and Development 3 TSS 3323 Digital Forensics 3
TST 3293
ALK 3122* Computer and 2 QKS 3172* Tempur Tanpa Senjata* 2
Network Security
1
Software 2
Engineering *20
**19
Latihan ***20
Ketenteraan
Umum*
PLS 3131** PALAPES 3** 1 PLS 3141** PALAPES 4**
QKA 3132*** Kesatria Al-Fateh 2 QXX Kokurikulum***
3*** YYY2***
JUMLAH KREDIT *20 JUMLAH KREDIT
**19
***20
KOD SEMESTER PENDEK KREDIT
KURSUS NAMA KURSUS 3
3
TSX 3XX3 Elective I 6
TSX 3XX3 Elective II
JUMLAH KREDIT
169
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
TAHUN KETIGA
SEMESTER 5 SEMESTER 6
KOD NAMA KURSUS KREDIT KOD NAMA KURSUS KREDIT
KURSUS KURSUS
TSK 3306 Project 6 TSK 330C Industrial Training 12
TSX 3XX3 Elective III 3
3
TSS 3333 Information Security 3
Management
TSS 3343 Wireless Network Security
TSX 3XX3 Elective IV 3
PLS 3151** PALAPES 5** 1
PLS 3161** PALAPES 6** 1 JUMLAH KREDIT 12
JUMLAH KREDIT
*18
**20
***18
Nota:
* Diambil oleh Pegawai Kadet
** Diambil oleh Pelajar PALAPES
*** Diambil oleh Pelajar Awam
**** Diambil oleh pelajar yang mendapat Band 1 dan 2 dalam peperiksaan MUET
170
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
SINOPSIS KURSUS TERAS
PROGRAM IJAZAH SARJANA MUDA SAINS KOMPUTER
(KESELAMATAN SISTEM KOMPUTER) (ZC27)
KRIPTOGRAFI - TSS 3313
CRYPTOGRAPHY - TSS 3313
3 Credit Hours
Prerequisite: None
Course Synopsis
This is a course in modern cryptography emphasising formal definitions and proofs of security.
Core topics include private- and public-key schemes for encryption and message authentication,
cryptographic hash functions, and authenticated encryption schemes. Additionally, the course
includes some analyses of the Data Encryption Standard (DES) block cipher, Rivest Cipher 4
(RC4) stream cipher, and real world security protocol such as Secure Sockets Layer (SSL).
Course Outcomes
At the end of this course, students are able to:
1. Understand the general concept of Cryptography.
2. Apply the concept of Cryptography.
3. Analyse security requirements and to apply cryptographic techniques and principles
such as symmetric encryption, asymmetric encryption, key management, hashing and
message digest.
4. Analyse a secure web server requirement and to configure a secure web server with
Hypertext Transfer Protocol Secure (HTTPS).
References
1. Kahn, D. (1996). The Codebreakers: The Story of Secret Writing. New York: Scribner.
2. Krutz, R.L. & Vines, R.D. (2007). The CISSP Prep Guide: Mastering CISSP and CAP.
Hoboken, NJ: Wiley.
3. Piper, F.C. & Murphy, S. (2002). Cryptography: A Very Short Introduction. Oxford:
Oxford University Press.
4. Stallings, W. (2011). Cryptography and Network Security: Principles and Practice. Fifth
Edition. Boston: Prentice Hall.
5. Viega, J, Messier, M. & Chandra, P. (2002). Network Security with OpenSSL.
Sebastopol, CA: O'Reilly.
171
BUKU PANDUAN AKADEMIK SARJANA MUDA SESI AKADEMIK 2022/2023
FAKULTI SAINS DAN TEKNOLOGI PERTAHANAN
FORENSIK DIGITAL - TSS 3323
DIGITAL FORENSICS - TSS 3323
3 Credit Hours
Prerequisite: None
Course Synopsis
This course takes a detailed, hands-on approach to the investigation of incidents, detection
hacking attacks and extracting evidence to report the crime and conduct audits to prevent future
attacks in which computers or computer technology play a significant role. Students completing
this course will be familiar with the core computer science theory and practical skills necessary
to perform rudimentary computer forensic investigations: discovering data, recovering deleted
data or damaged file information, understand the role of technology in investigating computer-
based crime: tracing the originator of defamatory e-mails to recover signs of fraud, and be
prepared to deal with investigative bodies at elementary level to prosecute the necessary
evidence in the court of law. This course will incorporate significant components of industrial
and technical training, which includes certifications from EC Council.
Course Outcomes
At the end of this course, students are able to:
1. Understand the concepts and techniques of digital forensics and its importance.
2. Gain sufficient knowledge on the legal matters pertaining digital forensics.
3. Conduct a proper digital forensic investigation.
References
1. Bunting, S. (2007). EnCase Computer Forensics: The Official EnCE - EnCase Certified
Examiner Study Guide. New York: John Wiley & Sons.
2. Casey, E. (2009). Handbook of Digital Forensics and Investigation. London: Elsevier Inc.
3. Cowen, D. (2012). Computer Forensics: A Beginner’s Guide. New York: McGraw-Hill
Osborne.
4. Vacca, J.C. (2005). Computer Forensics: Computer Crime Scene Investigation. Second
Edition. New Jersey: Charles River Media.
5. Wiles, J., Cardwell, K. & Reyes, A. (2007). The Best Damn Cybercrime and Digital
Forensics Book Period. Maryland Heights: Syngress.
172