Warusia Yassin | Cybersecurity | Best Researcher Award

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

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🎓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

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

Abeer Iftikhar | Information Security | Best Researcher Award

Ms. Abeer Iftikhar | Information Security | Best Researcher Award

PHD Scholar, Bahria University Islamabad, Pakistan 📝

Dr. Abeer Iftikhar Tahirkheli is a distinguished researcher and instructor with nearly 24 years of extensive experience in the fields of Computer Science, Information Security, Strategic Studies, and Defense Analysis. Her professional journey spans multinational corporations, academia, and defense forces, where she has significantly contributed to research, instructional roles, and strategic development. Dr. Abeer’s primary focus is on advancing Information Security, Artificial Intelligence, and Network Forensics, with a special emphasis on Smart City Networks and Trust Evaluation Mechanisms. Her academic and professional contributions are marked by a commitment to enhancing security protocols and developing innovative solutions to address modern-day challenges in cybersecurity, strategic studies, and forensic analysis.

Profile

Scopus

Orcid

Google Scholar

Education 🎓

Dr. Abeer Iftikhar Tahirkheli has an impressive academic background in Computer Science, Information Security, and Strategic Studies. She is currently completing her Ph.D. in Computer Science at Bahria University, Islamabad, with research aimed at enhancing trust in smart city networks through innovative security measures. She earned her MS in Information Security from Bahria University in 2020, achieving a CGPA of 4.0 and a Roll of Honor for her work on trust evaluation in networked environments. Dr. Abeer also holds an MPhil in Strategic Studies from the National Defence University, where she graduated top of her class with a thesis on the strategic impact of military modernization in South Asia. Her foundation includes a Master’s in Computer Science from the International Islamic University, Islamabad, and a Bachelor’s in Science from Punjab University, with a focus on Mathematics and Statistics. She has also earned certifications in cybersecurity, including MCNA-2 and advanced Signals Analysis training in Germany.

Professional Experience 💼

With almost 16 years in instructional roles, Dr. Abeer has taught and developed courses across multiple educational and professional echelons, focusing on subjects like Information Technology, Signal Communication, Security Analysis, and Strategic Studies. Her vast experience includes roles in multinational environments and defense sectors, where she led projects in Network Security, Surveillance, and Communication Systems. Her strategic insight, analytical abilities, and research initiatives have had a substantial impact on security operations and technology implementation in defense organizations.

Research Interests 🔬

Dr. Abeer’s research interests lie at the intersection of technology and security. She specializes in:

  • Information Security and Trust Mechanisms
  • Artificial Intelligence for Smart City Applications
  • Network Forensics and Cyber Threat Prevention
  • Security and Surveillance Systems in Defense
  • Strategic Studies and Conflict Analysis

Her research contributions focus on advancing security measures in smart cities, utilizing detection and prevention methods to maintain data integrity and system trust in edge-based networks. She is also deeply engaged in exploring the strategic implications of modernization in regional defense systems, contributing to the strategic environment of South Asia.

Author Metrics 🏆

Dr. Abeer Iftikhar Tahirkheli’s author metrics reflect her impactful contributions in cybersecurity, strategic studies, and network forensics. Her research, primarily focused on trust mechanisms for smart city networks and security innovations in edge computing, has been well-received, with numerous citations that highlight her influence in both academic and professional communities. Dr. Abeer’s publications span reputed journals and conferences, where she has presented her findings on enhancing information security and analyzing strategic geopolitical impacts, particularly in South Asia. Her work’s high citation count underscores the relevance and applicability of her research to contemporary security and strategic challenges, and her recognized contributions are evident in her collaborations across interdisciplinary studies. Her author metrics illustrate a sustained commitment to pioneering research, driving advancements in technology and security practices for complex, real-world systems.

Publications Top Notes 📚

  1. Trust Management and Evaluation for Edge Intelligence in the Internet of Things
    • Authors: KN Qureshi, A Iftikhar, SN Bhatti, F Piccialli, F Giampaolo, G Jeon
    • Journal: Engineering Applications of Artificial Intelligence
    • Volume: 94
    • Article ID: 103756
    • Year: 2020
    • Citations: 62
    • Summary: This paper explores trust management frameworks for edge intelligence in IoT systems, aiming to enhance security and reliability in decentralized environments.
  2. A Survey on Modern Cloud Computing Security over Smart City Networks: Threats, Vulnerabilities, Consequences, Countermeasures, and Challenges
    • Authors: AI Tahirkheli, M Shiraz, B Hayat, M Idrees, A Sajid, R Ullah, N Ayub
    • Journal: Electronics
    • Volume: 10, Issue 15
    • Article ID: 1811
    • Year: 2021
    • Citations: 47
    • Summary: This survey provides an in-depth review of security challenges in cloud computing for smart cities, including threats, vulnerabilities, and effective countermeasures, with a focus on improving resilience.
  3. Security, Trust, and Privacy Risks, Responses, and Solutions for High-Speed Smart Cities Networks: A Systematic Literature Review
    • Authors: A Iftikhar, KN Qureshi, M Shiraz, S Albahli
    • Journal: Journal of King Saud University – Computer and Information Sciences
    • Article ID: 101788
    • Year: 2023
    • Citations: 20
    • Summary: This paper systematically reviews the risks and protective measures surrounding security, trust, and privacy within high-speed smart city networks, offering a foundation for safer digital infrastructures.
  4. Predicting COVID-19 Infections Prevalence Using Linear Regression Tool
    • Authors: STA Shah, A Iftikhar, MI Khan, M Mansoor, AF Mirza, M Bilal
    • Year: 2020
    • Citations: 7
    • Summary: In this research, linear regression models are applied to predict COVID-19 infection trends, contributing to epidemiological understanding and planning.
  5. A Blockchain-based Secure Authentication Technique for Ensuring User Privacy in Edge-Based Smart City Networks
    • Authors: A Iftikhar, KN Qureshi, FB Hussain, M Shiraz, M Sookhak
    • Journal: Journal of Network and Computer Applications
    • Article DOI: 10.1016/j.jnca.2024.104052
    • Publication Year: 2024
    • Article Number: 104052

Conclusion

Given her extensive experience, interdisciplinary approach, and significant contributions to network security and strategic studies, Dr. Abeer Iftikhar Tahirkheli’s profile strongly aligns with the criteria for the Best Researcher Award. Her commitment to advancing cybersecurity in smart cities, alongside her academic rigor and dedication, make her a highly deserving candidate for this honor.