Warusia Yassin | Cybersecurity | Best Researcher Award

Posted on by Network Science

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.

Abeer Iftikhar | Information Security | Best Researcher Award

Posted on by Network Science

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.