ICoRAST2021 PROGRAM BOOK

SK09 ABSTRACT
Computer Science

A COMPARATIVE REVIEW OF DNA TECHNIQUES USED IN DNA BASED CRYPTOGRAPHY

NIK AZURA NIK ABDULLAH1*, NUR HAFIZA ZAKARIA1, AZNI HAZLIZAN AB HALIM1

1 Faculty of Science and Technology, Universiti Sains Islam Malaysia,
Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan, Malaysia

*Corresponding author email: [email protected]; [email protected]; [email protected]

ABSTRACT

Cryptography has been extensively employed in the field of information security for protecting and providing security to
confidential data. In recent years, the field of cryptography has emerged to consider a hybrid cryptographic implementation

that combines conventional cryptographic techniques with the knowledge of DNA technologies to formulate DNA
cryptography. DNA based cryptography is considered as one branch of sustainability science as it combines a
transdisciplinary structure of natural sciences (biology) and technological sciences (information security). This paper
discussed various DNA techniques implemented in recent DNA cryptographic algorithms. Among them are Watson-Crick

Complementary Rules, DNA Encoding / Decoding Rules, DNA Operation Rules, DNA Triple Codon Code, DNA Segmentation,
DNA Hybridization (DNA Annealing), and DNA Transcription and DNA Replication from the Central Dogma Molecular Biology
process. Algorithms description and theoretical comparative analysis of these DNA cryptographic algorithms are also
presented. Comparisons are made based on the following parameters; conventional cryptographic techniques and DNA

techniques used by these DNA cryptographic algorithms, the algorithm’s application, limitation and security analysis
conducted.

Keywords: Cryptography, DNA cryptography, DNA computing, DNA techniques, comparative analysis

Organiz1e9d/1b0y/2F0a2c1ulty of Science & Technology, USIM 51 | 51

SK10 ABSTRACT
Computer Science

OSCILLATION DETECTION OF A QUADROTOR SYSTEM CARRYING SUSPENDED PAYLOAD
USING IMAGE PROCESSING TECHNIQUE

LIYANA RAMLI1*, AMALIN AISYA MOHD AWI1 AND IZZUDDIN LAZIM1

1 Department of Electrical and Electronic Engineering, Faculty of Engineering and Built Environment,
Universiti Sains Islam Malaysia, Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan, Malaysia

*Corresponding author email: [email protected]

ABSTRACT

This paper proposes an image processing technique to detect the oscillation deflection of a quadrotor system carrying a

suspended payload. A wireless smart camera is attached underneath the quadrotor to capture the payload oscillation during
the transportation from one place to another. The image processing technique is utilised to measure the oscillation response
based on the output signal captured by the smart camera. A parrot BEPOP quadrotor drone is used for the experiment, and
the image processing technique is realised using MATLAB software. Experiments are carried out to detect and analyse the
payload oscillation response under different payload masses. The experiment results demonstrate the effectiveness of the
image processing technique in detecting the payload oscillation under different payload masses.

Keywords: Sustainability, image processing, Payload Swing Suppression, quadrotor, vibration

Organiz1e9d/1b0y/2F0a2c1ulty of Science & Technology, USIM 52 | 52

ABSTRACT
Computer Science

SK12

PERFORMANCE EVALUATION OF MACHINE LEARNING CLASSIFICATION MODELS FOR CONTACT TRACING
OF INFECTIOUS DISEASES USING WIFI SIGNALS

ANVAR NARZULLAEV1*, MADIHAH MOHD SAUDI1, ZAHRIDDIN MUMINOV 2 AND MAVLUTDIN NARZULLAEV 3

1 Faculty of Science and Technology, Universiti Sains Islam Malaysia,
Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan, Malaysia

2 Uzbek-Israel Faculty of High Technology, National University of Uzbekistan, Tashkent, Uzbekistan

3 Faculty of Applied Mathematics and Intelligent Technologies, National University of Uzbekistan, Tashkent, Uzbekistan

*Corresponding author email: [email protected]

ABSTRACT

There is just a handful of interventions proven to curb the spread of infectious diseases. One of them is contact tracing that
involves reaching infected people to investigate where they might have been infected and whom they might have exposed to
the virus. Contact tracing has been identified as a core disease control measure by the World Health Organization and has
been exercised by state health agencies for decades. In this research, we will evaluate existing machine learning classification
models using various performance metrics for contact tracing of infectious diseases, such as COVID-19. We will use the Wi-Fi
signals data from a possible contact and a confirmed patient’s smartphone to detect whether the two shared the same
physical space.

Keywords: machine learning, classification, covid-19, contact tracing, wi-fi

Organiz1e9d/1b0y/2F0a2c1ulty of Science & Technology, USIM 53 | 53

SK13 ABSTRACT
Computer Science

OPTIMIZED COVER SELECTION FOR LSB BASED AUDIO STEGANOGRAPHY USING
MULTI-OBJECTIVE EVOLUTIONARY ALGORITHM

MUHAMMAD HARITH NOOR AZAM 1*, FARIDA RIDZUAN 1 AND M NORAZIZI SHAM MOHD SAYUTI 2

1 Faculty of Science and Technology, Universiti Sains Islam Malaysia,
Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan, Malaysia

2 Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia,
Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan, Malaysia

*Corresponding author email: [email protected]

ABSTRACT

Audio steganography is implemented for people to communicate secretly by camouflaging secret message inside audio file.
For any audio steganography to achieve good performance, it must comply with three main characteristics, capacity,
imperceptibility, and robustness. The common practice of implementing any existing algorithms is the end-user is expected to
choose audio and insert a secret text message without considering any effects on any of these characteristics. This may lead

to users choosing bad cover audio which will cause communication failure between sender and receiver as part of message is
gone or the stego-file produced is vulnerable towards visual and statistical steganalysis attack. The main idea of this research
is to provide suggestions for the users to select good cover audio in audio steganography using Multi-objective Evolutionary
Algorithm (MOEA). MOEA can be implemented to find the cover audio for the audio steganography as it is capable to generate

a list of solutions in a single run. This research proposes a new framework for optimized cover audio selection in audio
steganography based on imperceptibility and robustness features. In addition, an evaluation is conducted to compare the
performance of the solution(s) given by MOEA against all the cover(s) in the database. Based on the result given by this
experiment, it can be concluded that the proposed framework fulfills its objective to select optimized cover audio used for

LSB audio steganography based on imperceptibility and robustness features.

Keywords: Audio Steganography; LSB; Cover Selection

Organiz1e9d/1b0y/2F0a2c1ulty of Science & Technology, USIM 54 | 54

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ACKNOWLEDGEMENTS

ICoRAST2021 would like to thank:
♥ Prof. Dato’ Dr. Mohamed Ridza Bin Wahiddin, Vice Chancellor of USIM (Patron);
♥ Prof. Dr. Rosalina Abdul Salam, Dean of Faculty of Science And Technology, USIM (Advisor);
♥ Sponsors: Sugar Bomb Worldwide Malaysia and Personal (Unname);
♥ Keynote Speakers:

✓ Prof. Dr. Ford Lumban Gaol, Professor Informatics Engineering And Information System,
Bina Nusantara University, Indonesia;

✓ Ts. Elman bin Mustafa El-Bakri, Executive Director, Damansara PMC Services Sdn. Bhd.
Malaysia;

♥ All participants of ICORAST 2021;

and those directly and indirectly supported our effort and event.

Thank you | Terima kasih

Organiz1e9d/1b0y/2F0a2c1ulty of Science & Technology, USIM 56 | 56

SPONSORS

Organiz1e9d/1b0y/2F0a2c1ulty of Science & Technology, USIM 57 | 57

OOrgragnaizneidz1eb9yd/1Fba0cy/u2lFt0ya2oc1fuSltcyienocfeS&cTieecnhcneolo&gyT, UeScIhMnology, USIM 58