Chao Wang | Computer Science | Research Excellence Award

Mr. Chao Wang | Computer Science | Research Excellence Award

North China University of Technology | China

Mr. Chao Wang is an accomplished researcher whose work spans vehicular networks, IoT security, blockchain mechanisms, and food engineering applications, reflecting a multidisciplinary impact. With 809 citations, an h-index of 12, and 16 i10-index publications, he has established a strong scholarly presence supported by numerous high-impact journal articles and competitive conference papers. His research contributions include advanced blockchain-based frameworks for secure communication, innovative privacy-preserving data-sharing models, anomaly detection algorithms for intelligent vehicles, and distributed system security. He has also co-authored influential studies on anti-glycation mechanisms, food bioactive compounds, and cellular protection. His publications from 2021 to 2025 demonstrate consistent output across IEEE Transactions, Future Generation Computer Systems, Food Biomacromolecules, and other reputable venues. His work on collaborative quality control, CAN bus anomaly detection, distributed GAN attack resistance, and multi-party payment channels represents notable advancements in secure systems. He has also contributed to reviews on AGEs inhibition, IoV security, NGS applicability, and blockchain-enabled vehicular applications. Beyond technical innovation, his research extends to biologically focused studies that explore glycation inhibition, fermentation mechanisms, and cellular oxidative protection. Across domains, his scholarly contributions continue to advance secure intelligent systems, data integrity solutions, and interdisciplinary applications, reinforcing his role as a productive and influential researcher.

Profiles : Orcid | Google Scholar

Featured Publications

Bao, C., Niu, Z., He, B., Li, Y., Han, S., Feng, N., Huang, H., Wang, C., Wang, J., & others. (2025). A novel high‐protein composite rice with anti‐glycation properties prepared with crushed rice flour, whey protein and lotus seed proanthocyanidins. Food Biomacromolecules, 2(1), 23–34.

He, Y., Zhou, Z., Wu, B., Xiao, K., Wang, C., & Cheng, X. (2024). Game-theoretic incentive mechanism for collaborative quality control in blockchain-enhanced carbon emissions verification. IEEE Transactions on Network Science and Engineering.

Li, Q., Xiao, K., Yi, C., Yu, F., Wang, W., Rao, J., Liu, M., Zhang, L., Mu, Y., Wang, C., & others. (2024). Inhibition and mechanism of protein nonenzymatic glycation by Lactobacillus fermentum. Foods, 13(8), 1183.

Wang, C., Xu, X., Xiao, K., He, Y., & Yang, G. (2024). Traffic anomaly detection algorithm for CAN bus using similarity analysis. High-Confidence Computing, 4(3), 100207.

Xiao, K., Li, J., He, Y., Wang, X., & Wang, C. (2024). A secure multi-party payment channel on-chain and off-chain supervisable scheme. Future Generation Computer Systems, 154, 330–343.

Feng, N., Feng, Y., Tan, J., Zhou, C., Xu, J., Chen, Y., Xiao, J., He, Y., Wang, C., & others. (2023). Inhibition of advance glycation end products formation, gastrointestinal digestion, absorption and toxicity: A comprehensive review. International Journal of Biological Macromolecules, 249, 125814.

Wu, Q., Kong, Y., Liang, Y., Niu, M., Feng, N., Zhang, C., Qi, Y., Guo, Z., Xiao, J., & others. (2023). Protective mechanism of fruit vinegar polyphenols against AGEs-induced Caco-2 cell damage. Food Chemistry: X, 19, 100736.

Wang, C., Liu, X., He, Y., Xiao, K., & Li, W. (2023). Poisoning the competition: Fake gradient attacks on distributed generative adversarial networks. In Proceedings of the IEEE International Conference on Mobile Ad Hoc and Smart Systems.

Xu, X., Wang, L., Wang, C., Zhu, H., Zhao, L., Yang, S., & Xu, C. (2023). Intelligent connected vehicle security: Threats, attacks and defenses. Journal of Information Science & Engineering, 39(6).

Wang, C., Jiang, L., He, Y., Yang, G., & Xiao, K. (2023). Age of information-based channel scheduling policy in IoT networks under dynamic channel conditions. In China Conference on Wireless Sensor Networks (pp. 88–98).

Zhou, J., Wang, C., Luo, M., Liu, X., Xu, X., & Chen, S. (2023). Spatial-temporal based multi-head self-attention for in-vehicle network intrusion detection system. SSRN 4581213.

Wang, C., Wang, S., Cheng, X., He, Y., Xiao, K., & Fan, S. (2022). A privacy and efficiency-oriented data sharing mechanism for IoTs. IEEE Transactions on Big Data, 9(1), 174–185.

Li, Q., Li, L., Zhu, H., Yang, F., Xiao, K., Zhang, L., Zhang, M., Peng, Y., Wang, C., & others. (2022). Lactobacillus fermentum as a new inhibitor to control advanced glycation end-product formation during vinegar fermentation. Food Science and Human Wellness, 11(5), 1409–1418.

Wu, Q., Liang, Y., Kong, Y., Zhang, F., Feng, Y., Ouyang, Y., Wang, C., Guo, Z., & others. (2022). Role of glycated proteins in vivo: Enzymatic glycated proteins and non-enzymatic glycated proteins. Food Research International, 155, 111099.

Wang, C., Cheng, X., Li, J., He, Y., & Xiao, K. (2021). A survey: Applications of blockchain in the Internet of Vehicles. EURASIP Journal on Wireless Communications and Networking, 2021(1), 77.

Xu, S., Chen, X., Wang, C., He, Y., Xiao, K., & Cao, Y. (2021). A lattice-based ring signature scheme to secure automated valet parking. In Wireless Algorithms, Systems, and Applications.

Aman Bin Jantan | Computer Science | Best Researcher Award

Assoc. Prof. Dr. Aman Bin Jantan | Computer Science | Best Researcher Award

Universiti Sains Malaysia | Malaysia

Author Profile

Scopus

Orcid

Google Scholar

Early Academic Pursuits 🎓

Assoc. Prof. Dr. Aman Bin Jantan's academic journey is rooted in a strong foundation in computer science. He earned his Bachelor’s degree (1993) and Master’s in Computer Science (AI) (1996) from Universiti Sains Malaysia (USM), where he laid the groundwork for his expertise in artificial intelligence and software engineering. His research on FrameLog Compiler Construction during his MSc reflected an early inclination toward programming languages and AI-driven system development. His PhD in Software Engineering (2002) from USM further solidified his prowess, focusing on the redefinition of expert system development languages—a groundbreaking contribution to the field.

Professional Endeavors 🏢

Dr. Aman has had an extensive career in both academia and industry. His professional journey began as a Research Officer at USM’s AI Lab in 1993, followed by roles as a Graduate Assistant and Lecturer. His passion for education saw him taking up lecturing positions at Stamford College, UiTM Shah Alam, and USM. Apart from academia, he ventured into the tech industry by establishing his own ICT business, offering software solutions, IT services, and computer training. Since 2002, he has been an integral part of USM’s School of Computer Sciences, where he now serves as an Associate Professor.

Contributions and Research Focus 🔬

Dr. Aman’s research spans across multiple domains, including:
Information Security – Intrusion Detection, Cyberwarfare, Encryption, Steganography, and Electronic Forensics.
Software Engineering – Fault Tolerance, Component-Based System Development, and Software Quality Assurance.
Artificial Intelligence – Machine Learning, Neuro-Fuzzy Systems, and Expert Systems.

His work on network security, intrusion detection, and machine learning-driven cybersecurity solutions has significantly impacted the field. His innovative Honeybee Intelligent Model for Network Zero-Day Attack Detection is a notable contribution that has been widely recognized.

Accolades and Recognition 🏆

Dr. Aman’s excellence in teaching and research has earned him multiple Excellent Service Awards (2007, 2011, 2020). His publications in high-impact journals, including those on financial crime prevention, AI-driven profiling, and cybersecurity measures, have established him as a thought leader in his domain.

Impact and Influence 🌍

As an academic and researcher, Dr. Aman has shaped the next generation of cybersecurity experts and software engineers. His workshops, mentorship, and leadership in the field of information security have influenced policy-making and corporate cybersecurity strategies. His Security and Forensic Research Group Laboratory at USM is a hub for cutting-edge research in cyber defense technologies.

Legacy and Future Contributions 🚀

Dr. Aman’s contributions to artificial intelligence, cybersecurity, and software engineering will continue to shape the landscape of digital security and computing. His commitment to advancing cybersecurity education and research ensures that future professionals will be well-equipped to tackle emerging threats in an increasingly digital world. With a strong portfolio of research, industry collaborations, and mentorship, Dr. Aman remains a driving force in the evolution of AI-driven security solutions. His future work is expected to redefine the intersection of AI and cybersecurity, making digital systems safer and more resilient.

Publications


  • 📄 Enhancing Neighborhood-Based Co-Clustering Contrastive Learning for Multi-Entity Recommendation

    • Authors: J. Liao, Juan; A.B. Jantan, Aman Bin; Z. Liu, Zhe

    • Journal: Engineering Applications of Artificial Intelligence

    • Year: 2025


  • 📄 Digital Forensic Investigation on Social Media Platforms: A Survey on Emerging Machine Learning Approaches

    • Authors: A.A. Kazaure, Abdullahi Aminu; A.B. Jantan, Aman Bin; M.N. Yusoff, Mohd Najwadi

    • Journal: Journal of Information Science Theory and Practice

    • Year: 2024


  • 📄 Digital Forensics Investigation Approaches in Mitigating Cybercrimes: A Review

    • Authors: A.A. Kazaure, Abdullahi Aminu; A.B. Jantan, Aman Bin; M.N. Yusoff, Mohd Najwadi

    • Journal: Journal of Information Science Theory and Practice

    • Year: 2023


  • 📄 A Machine Learning Classification Approach to Detect TLS-Based Malware Using Entropy-Based Flow Set Features (Open Access)

    • Authors: K. Keshkeh, Kinan; A.B. Jantan, Aman Bin; K. Alieyan, Kamal

    • Journal: Journal of Information and Communication Technology

    • Year: 2022


  • 📄 Multi-Behavior RFM Model Based on Improved SOM Neural Network Algorithm for Customer Segmentation (Open Access)

    • Authors: J. Liao, Juan; A.B. Jantan, Aman Bin; Y. Ruan, Yunfei; C. Zhou, Changmin

    • Journal: IEEE Access

    • Year: 2022