Warusia Yassin | Cybersecurity and Cryptography | Innovative Research Award

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Innovative Research Award

Warusia Yassin
Universiti Teknikal Malaysia Melaka, Malaysia

Warusia Yassin
Affiliation Universiti Teknikal Malaysia Melaka
Country Malaysia
Scopus ID 36912990900
Documents 49
Citations 740
h-index 14
Subject Area Cybersecurity and Cryptography
Event International Forensic Scientist Awards
ORCID 0000-0001-9601-2572

Warusia Yassin is a Malaysian academic researcher recognized for scholarly contributions in cybersecurity, intrusion detection systems, machine learning applications, and network security analytics. Her research portfolio demonstrates a sustained focus on improving intrusion detection methodologies through clustering algorithms, classification models, and hybrid computational techniques.[1] Her work has been indexed in Scopus and cited across cybersecurity literature for its practical relevance in reducing false alarms and improving detection accuracy in digital environments.[2]

Abstract

This article summarizes the academic contributions of Warusia Yassin in the field of cybersecurity and digital forensic intelligence. Her published studies primarily investigate intrusion detection frameworks that integrate machine learning, clustering algorithms, and probabilistic classification techniques. Through publications indexed in Scopus, her work has contributed to the advancement of intelligent cybersecurity monitoring systems and data-driven anomaly detection methodologies.[3]

Keywords

Cybersecurity, Intrusion Detection, Machine Learning, Cryptography, Random Forest, K-Means Clustering, Digital Forensics, Network Security, Hybrid Classification

Introduction

The increasing complexity of cyber threats has intensified the demand for intelligent intrusion detection systems capable of identifying malicious activities with higher precision and lower false alarm rates. Academic researchers in cybersecurity continue to investigate scalable approaches that combine statistical learning, data mining, and behavioral analysis. Within this research context, Warusia Yassin has contributed to the development of hybrid intrusion detection frameworks designed to improve classification accuracy in large-scale digital infrastructures.[4]

Research Profile

Warusia Yassin is affiliated with Universiti Teknikal Malaysia Melaka and has established a publication record focused on cybersecurity analytics and intrusion detection methodologies. Her Scopus profile indicates sustained academic activity, including journal articles and conference proceedings related to digital security technologies. Her research output includes 49 indexed documents with an h-index of 14 and over 740 citations, reflecting scholarly engagement within the cybersecurity research community.[1]

Research Contributions

A significant portion of Yassin’s research has examined the integration of clustering and classification algorithms for intrusion detection optimization. Her studies investigated the use of K-Means clustering combined with Naïve Bayes and OneR classification techniques to improve threat identification performance in network systems.[5] Additional research explored the application of genetic algorithms and random forest classifiers to reduce false positives in anomaly detection environments.[2]

Her conference publications also addressed cloud-based intrusion detection service frameworks, emphasizing scalable cybersecurity infrastructures for modern computing ecosystems. These studies contributed to discussions surrounding adaptive security architectures and automated cyber defense systems.[3]

Publications

  • “Reducing false alarm using hybrid intrusion detection based on x-means clustering and random forest classification” — Journal of Theoretical and Applied Information Technology (2014).
  • “Improving intrusion detection using genetic algorithm” — Information Technology Journal (2013).
  • “A Cloud-based Intrusion Detection Service framework” — CyberSec 2012 Proceedings.
  • “A K-Means and Naive Bayes learning approach for better intrusion detection” — Information Technology Journal (2011).
  • “Intrusion detection based on K-Means clustering and Naïve Bayes classification” — CITA’11 Proceedings.

Research Impact

The research contributions of Warusia Yassin have supported ongoing advancements in cybersecurity analytics and intelligent network defense systems. Her publications demonstrate methodological approaches that combine machine learning algorithms with practical intrusion detection applications. Citation activity associated with her work suggests continued academic relevance in areas connected to cyber threat monitoring, classification accuracy, and adaptive detection systems.[6]

Award Suitability

The International Forensic Scientist Awards recognizes researchers whose work contributes to technological innovation, forensic intelligence, and scientific advancement. Warusia Yassin’s research aligns with these objectives through her scholarly investigations into intrusion detection, cyber defense frameworks, and machine learning-based cybersecurity methodologies. Her publication record and citation metrics reflect measurable academic engagement and interdisciplinary relevance within digital forensic and cybersecurity domains.[1]

Conclusion

Warusia Yassin has contributed to cybersecurity research through studies focused on intelligent intrusion detection systems, hybrid machine learning frameworks, and scalable cyber defense mechanisms. Her work continues to support academic discussions surrounding network security optimization and computational threat analysis. The recognition associated with the Innovative Research Award reflects her documented scholarly contributions within cybersecurity and digital forensic research environments.

References

  1. Elsevier. (n.d.). Scopus author details: Warusia Yassin, Author ID 36912990900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=36912990900
  2. Yassin, W. (2014). Reducing false alarm using hybrid intrusion detection based on x-means clustering and random forest classification. Journal of Theoretical and Applied Information Technology.
  3. Yassin, W. (2012). A Cloud-based Intrusion Detection Service framework. Proceedings of CyberSec 2012.
    https://doi.org/10.1109/CyberSec.2012.6246098
  4. Yassin, W. (2013). Improving intrusion detection using genetic algorithm. Information Technology Journal.
    https://doi.org/10.3923/itj.2013.2167.2173
  5. Yassin, W. (2011). A K-Means and Naive Bayes learning approach for better intrusion detection. Information Technology Journal.
    https://doi.org/10.3923/itj.2011.648.655
  6. Yassin, W. (2011). Intrusion detection based on K-Means clustering and Naïve Bayes classification. Proceedings of CITA’11.
    https://doi.org/10.1109/CITA.2011.5999520

Ahlem Aboud | Computer Science | Research Excellence Award

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Dr. Ahlem Aboud | Computer Science | Research Excellence Award

Université de Picardie Jules Verne | France

Dr. Ahlem Aboud is a researcher in Artificial Intelligence and bio-inspired optimization, with a strong focus on dynamic and multi-objective optimization problems. Her research integrates population-based metaheuristics such as Particle Swarm Optimization, Crow Search Algorithm, and Whale Optimization Algorithm with machine learning and deep learning frameworks. According to Scopus, she has published 5 indexed research articles, received 59 citations, and holds an h-index of 4. Her work is published in high-impact venues including Applied Soft Computing, Applied Sciences, and IEEE flagship conferences. She has contributed novel dynamic Pareto bi-level optimization strategies applied to feature selection, big data fusion, and intelligent decision systems. Her research advances adaptive optimization for complex, evolving environments and interdisciplinary AI applications.

                            Citation Metrics (Scopus)

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View Scopus Profile  View Google Scholar Profile  View ORCID Profile  View LinkedIn Profile

Featured Publications


DPb-MOPSO: a dynamic pareto bi-level multi-objective particle swarm optimization algorithm

– A. Aboud, N. Rokbani, R. Fdhila, et al. · Applied Soft Computing, 2022 · Cited by 36


MOPSO for dynamic feature selection problem based big data fusion

– A. Aboud, R. Fdhila, A.M. Alimi · IEEE SMC, 2016 · Cited by 15


A Distributed Bi-behaviors Crow Search Algorithm for Dynamic Multi-Objective Optimization and Many-Objective Optimization

– A. Aboud, N. Rokbani, S. Mirjalili, A. Alimi · Applied Sciences, 2021 · Cited by 8


A novel Dynamic Pareto bi-level Multi-Objective Particle Swarm Optimization (DPb-MOPSO) algorithm

– A. Aboud, R. Fdhila, A. Hussain, et al. · Authorea Preprints, 2023 · Cited by 5

Sam Clarke | Computer Science | Best Researcher Award

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Mr. Sam Clarke | Computer Science | Best Researcher Award

Canterbury Christ Church University | United Kingdom

Sam Clarke is a dynamic and forward-thinking educator with over eight years of experience as a class teacher across Key Stages 1 and 2, and a key contributor to senior leadership teams. With a career rooted in both classroom practice and strategic educational leadership, Sam has transitioned seamlessly into higher education as a Lecturer of Primary Education at Canterbury Christ Church University. His expertise spans teaching, mentoring, research, and academic innovation, particularly in the realm of artificial intelligence (AI) in education. A passionate advocate for equity and ethical innovation, Sam combines classroom experience with pioneering research, curriculum design, and community outreach. His professional philosophy echoes Nelson Mandela’s powerful belief that “Education is the most powerful weapon to change the world.”

Professional profile👤

ORCID

Strengths for the Awards✨

  1. Innovative Research in AI and Education
    Sam Clarke’s work sits at the intersection of two rapidly evolving fields: education and artificial intelligence. His research addresses critical questions about GenAI’s impact on pedagogy, curriculum design, and interdisciplinary learning. His publication “Education in the Age of GenAI” and his co-edited journal BQIL demonstrate a commitment to pioneering research.

  2. Leadership in Academic Initiatives
    Sam is not just a participant but a leader in several academic and professional settings. As Founding Co-Editor of BQIL, Peer Reviewer for research funding, and Lecturer at CCCU, he has shown initiative and scholarly leadership.

  3. Policy-Relevant Contributions
    His guest lectures at UCL, Cambridge, and the Association of Citizenship Teaching suggest his work resonates beyond academia. He connects research to practice, influencing national discourse on AI in education.

  4. Community Engagement and Equity
    Through outreach in underprivileged schools and staff CPD on AI literacy, Sam applies his research to reduce educational inequities, making a tangible social impact.

  5. Collaborative and Interdisciplinary Work
    Clarke’s collaboration with prestigious institutions like the University of Oxford and his emphasis on interdisciplinary knowledge building demonstrate a wide-ranging and cooperative research ethos.

  6. Strong Publication Record with Open Access & Accessibility
    His commitment to knowledge dissemination is evident in his open-access publications and engagement in practitioner journals, ensuring that research reaches a diverse audience.

🎓 Education

Sam’s educational journey reflects a consistent trajectory of academic excellence and professional growth. He holds a Bachelor of Arts in Education Studies and Geography (First Class, 2014), a Postgraduate Certificate in Education with QTS (Distinction, 2015), and a Master of Arts in Education (Merit, 2024)—all from Canterbury Christ Church University. Most recently, he achieved a University Certificate of Advanced Practice (Distinction, 2025), further cementing his commitment to lifelong learning and pedagogical excellence.

👨‍🏫 Experience

Sam began his teaching career in 2015, serving in various roles including KS1 and KS2 Teacher, Mathematics Lead, and Computing Lead. His leadership capabilities emerged early, culminating in a place on the Senior Leadership Team at Sussex Road Primary School, where he managed appraisals, led curriculum initiatives, and coached newly qualified teachers. From 2017 to 2019, Sam also contributed as a School Improvement Facilitator for the Education Development Trust. Transitioning into higher education in 2024, he now lectures at Canterbury Christ Church University, shaping future educators with research-informed teaching and innovation-driven curriculum design.

🔬 Research Interests On Computer Science

Sam’s primary research interests lie in the ethical and educational implications of Generative AI within primary and higher education settings. He is especially passionate about exploring how AI can foster interdisciplinary learning, democratize access to education, and promote epistemic insight. His involvement with the Professoriate Group on AI and as a board member of the AI Ethics Committee at UCL underscores his commitment to ethical innovation. Sam also co-founded the academic journal Big Questions and Interdisciplinary Learning, promoting complex thinking and boundary-crossing knowledge creation.

🏆 Awards

Sam has not only received academic distinctions across all his university qualifications, but has also been repeatedly entrusted with leadership and mentoring roles that reflect his excellence. His invitation to prestigious conferences and involvement in ethics committees, editorial boards, and university strategic roles stands as a testament to the recognition of his thought leadership within the educational community.

📄 Publications

Sam Clarke has authored and co-authored several impactful publications exploring the intersections of education and AI:

  • Clarke, S. and Billingsley, B. (2024). Education in the Age of GenAI. Cambridge Generative AI in Education Conference Booklet of Abstracts.
    Published in 2024 | Cited by 3 articles

  • Clarke, S. (2024). A General Election and My Classroom in the Age of AI. Teaching Citizenship, Issue 59, pp. 8–9.
    Published in 2024 | Cited by 1 article

  • Clarke, S., Billingsley, B., & Heath, L. (Eds.) (2024). Big Questions and Interdisciplinary Learning. Zenodo.
    Published in 2024 | Cited by 2 articles

  • Clarke, S., Billingsley, B. and O’Leary, S. (2024). Using Generative Artificial Intelligence to Catalyse Further Interdisciplinarity Across Higher Education. Graduate College Working Papers, CCCU. Read paper
    Published in 2024 | Cited by 4 articles

✅ Conclusion

Sam Clarke embodies the ideal fusion of practitioner expertise and academic innovation. His contributions to AI in education—through teaching, research, publication, and community outreach—are both timely and transformative. With a consistent record of academic achievement, leadership, and ethical vision, Sam is poised to continue shaping the future of education at the intersection of pedagogy and technology. His work reflects a profound dedication to empowering educators and learners alike in a rapidly evolving digital world. 🌟

Dong Yang | Technologies | Best Researcher Award

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Prof. Dong Yang | Technologies | Best Researcher Award

Dalian Institute of Chemical Physics Chinese Academy of Sciences | China

Dong Yang is currently a professor at the Dalian Institute of Chemical Physics, Chinese Academy of Sciences. He also serves as the Deputy Director of the State Key Laboratory of Photoelectric Conversion and Utilization of Solar Energy. His research focuses on advancing solar energy technologies, particularly in perovskite photovoltaics and renewable energy applications.

Profile👤

Google Scholar

Strengths for the Awards✨

  • Extensive Research Experience – Professor Dong Yang has a well-rounded academic and research background, spanning China and the United States, with positions at Dalian Institute of Chemical Physics (CAS), Virginia Tech, and Pennsylvania State University.
  • Leadership & Innovation – As a Deputy Director of a State Key Laboratory, he plays a pivotal role in advancing solar energy research, which is highly impactful in the field of sustainable energy.
  • Cutting-Edge Research – His work in perovskite photovoltaics, flexible electronics, tandem solar cells, and renewable energy harvesters is at the forefront of energy research, addressing critical global challenges.
  • Industrial Applications – His research is not just theoretical but has strong potential for real-world applications, bridging the gap between academia and industry.
  • International Collaborations – Having worked in China and the United States, he brings a global perspective to research, fostering international partnerships.

🎓 Education

Dong Yang earned his Ph.D. in Physical Chemistry from the Dalian Institute of Chemical Physics in 2014. His academic journey has been instrumental in shaping his expertise in solar energy conversion and flexible electronics.

🏆 Experience

Following his Ph.D., Dr. Yang expanded his research through postdoctoral positions at Shaanxi Normal University in China and Virginia Tech in the United States. From 2018 to 2022, he served as an Assistant Research Professor at Pennsylvania State University, contributing significantly to solar cell innovation. Currently, he leads a research group specializing in next-generation photovoltaics and energy-harvesting technologies.

🔬 Research Interests On Technologies

Dr. Yang’s research interests include perovskite photovoltaics, flexible electronics, tandem solar cells, and renewable energy devices. His work aims to enhance the efficiency, stability, and industrial scalability of solar energy solutions.

🏅 Awards

Dr. Yang has received several prestigious awards for his contributions to solar energy research. His innovations in perovskite solar cells and flexible electronics have been recognized internationally.

📚 Publications

Dr. Yang has authored numerous high-impact publications in esteemed journals. Below are some of his notable works:

  • High efficiency planar-type perovskite solar cells with negligible hysteresis using EDTA-complexed SnO2

    • Authors: D Yang, R Yang, K Wang, C Wu, X Zhu, J Feng, X Ren, G Fang, S Priya, …
    • Year: 2018
    • Citations: 1358

  • Surface optimization to eliminate hysteresis for record efficiency planar perovskite solar cells

    • Authors: D Yang, X Zhou, R Yang, Z Yang, W Yu, X Wang, C Li, SF Liu, …
    • Year: 2016
    • Citations: 993

  • Stable high efficiency two-dimensional perovskite solar cells via cesium doping

    • Authors: X Zhang, X Ren, B Liu, R Munir, X Zhu, D Yang, J Li, Y Liu, DM Smilgies, …
    • Year: 2017
    • Citations: 668

  • High efficiency flexible perovskite solar cells using superior low temperature TiO2

    • Authors: D Yang, R Yang, J Zhang, Z Yang, SF Liu, C Li
    • Year: 2015
    • Citations: 579

  • Record efficiency stable flexible perovskite solar cell using effective additive assistant strategy

    • Authors: J Feng, X Zhu, Z Yang, X Zhang, J Niu, Z Wang, S Zuo, S Priya, S Liu, …
    • Year: 2018
    • Citations: 490

  • Hysteresis‐suppressed high‐efficiency flexible perovskite solar cells using solid‐state ionic‐liquids for effective electron transport

    • Authors: D Yang, R Yang, X Ren, X Zhu, Z Yang, C Li, S Liu
    • Year: 2016
    • Citations: 436

  • 20‐mm‐Large single‐crystalline formamidinium‐perovskite wafer for mass production of integrated photodetectors

    • Authors: Y Liu, J Sun, Z Yang, D Yang, X Ren, H Xu, Z Yang, S Liu
    • Year: 2016
    • Citations: 390

  • Recent advances in flexible perovskite solar cells: fabrication and applications

    • Authors: D Yang, R Yang, S Priya, S Liu
    • Year: 2019
    • Citations: 378

  • Thinness-and shape-controlled growth for ultrathin single-crystalline perovskite wafers for mass production of superior photoelectronic devices

    • Authors: Y Liu, Y Zhang, Z Yang, D Yang, X Ren, L Pang, SF Liu
    • Year: 2016
    • Citations: 373

  • Solution-Processed Nb:SnO2 Electron Transport Layer for Efficient Planar Perovskite Solar Cells

    • Authors: X Ren, D Yang, Z Yang, J Feng, X Zhu, J Niu, Y Liu, W Zhao, SF Liu
    • Year: 2017
    • Citations: 356

🔚 Conclusion

Dr. Dong Yang is a distinguished researcher in solar energy and flexible electronics. His pioneering work continues to drive advancements in photovoltaic technology, bridging the gap between scientific discovery and industrial application.