Warusia Yassin | Cybersecurity | Best Researcher Award

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Dr. Warusia Yassin | Cybersecurity | Best Researcher Award

Senior Lecturer at Universiti Teknikal Malaysia Melaka, Malaysia

Ts. Dr. Warusia Mohamed Yassin is a Senior Lecturer (DS51) at Universiti Teknikal Malaysia Melaka (UTeM), specializing in Security in Computing. With a professional background in system programming, engineering, and cybersecurity analysis, she has contributed significantly to academia and industry in the fields of anomaly detection, intrusion prevention, and cyber risk management. She is a certified professional technologist (Ts.) and an active researcher with numerous national and international publications and research projects.

🔹Professional Profile:

Scopus Profile

Orcid Profile

Google Scholar Profile

🎓Education Background

  • PhD in Computer Science (Security in Computing) – Universiti Putra Malaysia, 2015
    Thesis: An Integrated Anomaly Intrusion Detection Scheme Using Statistical, Hybridized Classifier and Signature Approach.

  • Master of Science in Computer Science (Security in Computing) – Universiti Putra Malaysia, 2011
    Thesis: An Improved Hybrid Learning Approach For Better Anomaly Detection.

  • Bachelor of Computer Science (Computer System) – Universiti Putra Malaysia, 2008

💼 Professional Development

  • Senior Lecturer, Universiti Teknikal Malaysia Melaka (2015 – Present)

  • Security Analyst, 2009

  • System Engineer, 2007

  • Lab Demonstrator, 2007

  • System Programmer, 2004

She has taught various undergraduate and postgraduate courses including Computer Programming, Intrusion Detection and Prevention, Cyber Threat Intelligence, and Risk Management.

🔬Research Focus

Her main research interests lie in Security in Computing, particularly:

  • Intrusion Detection Systems

  • Malware Analysis

  • Deep Learning and Machine Learning

  • Deepfake Detection

  • Biometric Authentication

  • Cybersecurity Risk Management

  • Blockchain-based Authentication

  • IoT Security and Forensics

📈Author Metrics:

Dr. Warusia has co-authored numerous high-impact publications in journals and conference proceedings. Key contributions include works on hybrid learning methods, anomaly detection, K-Means clustering with Naïve Bayes, and genetic algorithm applications for cybersecurity. Some notable journals include Information Technology Journal, Journal of Information Assurance and Security, and CyberSec Conference Proceedings.

🏆Awards and Honors:

  • Recipient of multiple industrial research grants including from CyberSecurity Malaysia, APNIC, and UTeM PJP.

  • Recognized consultant for national-level cybersecurity projects, including railway infrastructure security.

  • Active supervisor for PhD and Master students, with several completions under her mentorship.

  • Holds the Professional Technologist (Ts.) title in Malaysia, signifying certified expertise in technology application and innovation.

📝Publication Top Notes

1. Ransomware Early Detection using Machine Learning Approach and Pre-Encryption Boundary Identification

Authors: W. Zanoramy, M.F. Abdollah, O. Abdollah, S.M.W.M. S.M.M
Journal: Journal of Advanced Research in Applied Sciences and Engineering Technology
Volume: 6
Year: 2025
DOI: [Not provided]
Abstract: Proposes a machine learning-based ransomware detection model that identifies pre-encryption behavior to enable proactive intervention and minimize system damage.

2. Routing Protocols Performance on 6LoWPAN IoT Networks

Authors: P.S. Chia, N.H. Kamis, S.F. Abdul Razak, S. Yogarayan, W. Yassin, et al.
Journal: IoT
Volume: 6(1), Page 12
Year: 2025
DOI: [Not provided]
Abstract: Compares multiple routing protocols in 6LoWPAN-based IoT environments to determine optimal performance in terms of energy efficiency, packet delivery, and delay.

3. An Enhanced Integrated Deep Learning Method to Overcome Dehazing Issues on Intelligent Vehicles

Authors: W.M. Yassin, A.I. Hajamydeen, M.F. Abdollah, K. Raja, N. Farzana
Book Title: Sustainable Smart Cities and the Future of Urban Development
Pages: 487–502
Year: 2025
DOI: [Not provided]
Abstract: Introduces an integrated deep learning framework to enhance dehazing in vision systems of intelligent vehicles, contributing to safer navigation in urban smart environments.

4. Optimizing Android Malware Detection Using Neural Networks and Feature Selection Method

Authors: J. Bintoro, F.A. Rafrastara, I.A. Latifah, W. Ghozi, W. Yassin
Journal: Jurnal Teknik Informatika (JUTIF)
Volume: 5(6), Pages 1663–1672
Year: 2024
DOI: [Not provided]
Abstract: Combines neural networks with a tailored feature selection method to boost the accuracy and efficiency of Android malware detection.

5. Enhancing XGBoost Performance in Malware Detection through Chi-Squared Feature Selection

Authors: S. Rosyada, F.A. Rafrastara, A. Ramadhani, W. Ghozi, W. Yassin
Journal: Jurnal Sisfokom (Sistem Informasi dan Komputer)
Volume: 13(3), Pages 396–402
Year: 2024
DOI: [Not provided]
Abstract: Employs Chi-squared feature selection to enhance XGBoost’s ability to detect malware, streamlining the model and improving classification results.

.Conclusion:

Dr. Warusia Mohamed Yassin is undoubtedly a deserving candidate for the Best Researcher Award. Her significant academic achievements, coupled with her active involvement in high-impact research and industry projects, demonstrate her contribution to advancing cybersecurity. Her innovative research in anomaly detection, malware analysis, and deep learning makes her a leader in the field, and her continued success in mentoring and supervising graduate students ensures that her expertise will benefit the next generation of cybersecurity professionals.

Lakshmanaprakash  S | Cybersecurity | Best Researcher Award

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Dr. Lakshmanaprakash  S | Cybersecurity | Best Researcher Award

Associate Professor at Bannari Amman Institute of Technology, India

Dr. S. Lakshmanaprakash is a distinguished academician and researcher with over 15 years of experience in the field of computer science and engineering. Holding a Ph.D. in Wireless Networks from Curtin University, Malaysia, Dr. Lakshmanaprakash has made significant contributions to the domains of cybersecurity, wireless networks, and machine learning. He currently serves as an Associate Professor at Bannari Amman Institute of Technology, Sathyamangalam. His extensive research experience spans both teaching and research roles, including a notable four-year research tenure at Curtin University. Dr. Lakshmanaprakash is passionate about advancing technology in critical areas such as data security, healthcare monitoring, and network protocols.

🔹Professional Profile:

Google Scholar Profile

🎓Education Background

  • Ph.D. in Wireless Networks – Curtin University, Sarawak, Malaysia (2019 – Present)

  • M.E. in Computer Science and Engineering – PSNA College of Engineering & Technology, Dindigul, Anna University, Chennai (2007) – First Class

  • B.E. in Computer Science and Engineering – Sri Padmavathy College of Engineering, Madras University (2004) – First Class

💼 Professional Development

Dr. Lakshmanaprakash has served as a faculty member in several prestigious engineering colleges. Currently, he is an Associate Professor at Bannari Amman Institute of Technology, Sathyamangalam, where he has been teaching since 2020. Prior to this, he served as Assistant Professor at Vivekanandha College of Technology for Women and St. Peter’s College of Engineering & Technology. His career began as a Lecturer at RVS College of Engineering & Technology. He has handled various subjects such as Data Structures, Algorithms, Cryptography, and Network Security. With a rich background in both teaching and research, he has demonstrated excellence in educating future engineers while contributing to cutting-edge research in his field.

🔬Research Focus

Dr. Lakshmanaprakash’s primary research interests lie in wireless networks, cybersecurity, machine learning, and deep learning. He focuses on improving data dissemination techniques in vehicular networks, enhancing cybersecurity through machine learning, and developing efficient algorithms for healthcare monitoring. His work on vehicular ad hoc networks (VANETs) and his innovative contributions to the Internet of Medical Things (IoMT) have garnered significant academic attention. Additionally, he explores applications of machine learning in healthcare diagnostics and emergency response systems.

📈Author Metrics:

Dr. Lakshmanaprakash has authored several notable publications in peer-reviewed journals and conferences. His recent work includes articles in high-impact journals such as Measurement and Network: Computation in Neural Systems by Taylor & Francis. He has also contributed to numerous international conferences, presenting papers on machine learning, healthcare systems, and network security. His book chapters, including those on biometric security and quantum computing, have been well-received in the academic community. Additionally, Dr. Lakshmanaprakash serves as a reviewer for reputable journals like the Journal of Cyber Security Technology.

🏆Awards and Honors:

Dr. Lakshmanaprakash has earned several accolades for his contributions to academia and research. Some of his notable honors include:

  • Expert in Cybersecurity at the BRICS Skill Competition 2022.

  • Advisor Board Member of the Tamil Nadu Cyber Crime Awareness Organization (TANCCAO).

  • Recognition for his research work in healthcare monitoring systems and machine learning techniques.

  • Successful collaboration with Hackup Technology and Xplore IT Corp., leading to the establishment of cyber security cells at Bannari Amman Institute of Technology.

  • Member of various professional organizations, including ISTE and IACSIT.

  • Coordinator for placement activities and NBA-related tasks within the department.

  • Leadership in organizing National-Level Technical Symposiums at Bannari Amman Institute of Technology.

📝Publication Top Notes

1. Effective Heart Disease Prediction Using Hybrid Machine Learning

  • Authors: A Pandiaraj, SL Prakash, PR Kanna
  • Published: 2021, Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV 2021)
  • Focus: This paper discusses the application of hybrid machine learning algorithms for predicting heart disease, enhancing the accuracy of predictions using an integrated approach.

2. Artificial Intelligent Techniques for Wireless Communication and Networking

  • Authors: R Kanthavel, K Anathajothi, S Balamurugan, RK Ganesh
  • Publisher: John Wiley & Sons
  • Published: 2022
  • Focus: This work delves into the use of artificial intelligence techniques in wireless communication, providing insights into how AI can improve the efficiency and performance of networking systems.

3. Generating Art and Music Using Deep Neural Networks

  • Authors: A Pandiaraj, SL Prakash, R Gopal, PR Kanna
  • Published: Artificial Intelligent Techniques for Wireless Communication and Networking (2022)
  • Focus: This paper explores the use of deep neural networks in generating art and music, demonstrating the capability of AI in creative domains and the intersection of technology with the arts.

4. Edge Computing and Deep Learning Based Urban Street Cleanliness Assessment System

  • Authors: P Nagaraj, S Lakshmanaprakash, V Muneeswaran
  • Published: 2022, International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI 2022)
  • Focus: This study integrates edge computing and deep learning techniques to develop a system for assessing urban street cleanliness, showcasing the application of AI and IoT for smart city management.

5. Quantum Computation, Quantum Information, and Quantum Key Distribution

  • Authors: D Mohanaprabhu, SP Monish Kanna, J Jayasuriya, S Lakshmanaprakash, et al.
  • Published in: Automated Secure Computing for Next-Generation Systems, 2024 (pp. 345-366)
  • Focus: This chapter focuses on quantum computation, quantum information, and quantum key distribution, exploring their potential in enhancing cybersecurity and secure computing systems for next-generation technology.

Conclusion:

Dr. Lakshmanaprakash S has demonstrated an exceptional blend of academic excellence, research innovation, and real-world impact. His ability to bridge the gap between theoretical research and practical applications, particularly in cybersecurity, wireless networks, and machine learning, makes him a strong contender for the Best Researcher Award.

His continued dedication to teaching, researching emerging fields, and expanding cross-disciplinary collaborations, alongside his influential publications and leadership roles, positions him as one of the leading researchers in his domain. With a few more collaborations and expansions into cutting-edge areas like quantum computing and AI ethics, his research can reach even greater heights, making a transformative impact on society.

Overall, Dr. Lakshmanaprakash’s well-rounded contributions, innovative research, and leadership in technology and education are commendable, and he deserves to be considered for the Best Researcher Award