• AVITECH Research Group

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    IoT Cyber-Attack Detection and Secure Communications

    A main driver for smart city development is Industry 4.0, in which ICT helps connect physical systems to the cyber-world, thereby enabling supply chain market more efficient, agile, and customer-focused. However, cyber-security risks become a key concern due to open systems with IP addresses, creating more avenues for cyber-attacks.

    Information and communication technology (ICT) is expected to play an increasingly pivotal role in deepening economic integration and community building across the Association of Southeast Asian Nations (ASEAN), transitioning towards a digitally-enabled economy that is secure, sustainable, and transformative. This project considers the development of connected smart cities for a smart ASEAN society in general and in Vietnam in particular.

    The project aims to provide tools to enhance cyber-security in Industry 4.0, contributing to the enhancement of information reliability for smart society. In particular, it will develop (i) an innovative method to detect cyber-security threats in Industry 4.0 using advanced deep learning technology, (ii) an unprecedented framework to protect massive Industry 4.0 data from cyber-attacks using blockchain technology, and (iii) novel security solutions at the physical interface of information transmission using physical-layer security technology.

    Selected Publications

    Bui Minh Tuan, Van-Dinh Nguyen, Diep N. Nguyen, Nguyen Linh Trung, Nguyen Van Huynh, Dinh Thai Hoang, Marwan Krunz, and Eryk Dutkiewicz. Deep learning-driven friendly jamming for secure multicarrier ISAC under channel uncertainty. IEEE Transactions on Communications, November 2025 [under revision].

    Tran Viet Khoa, Do Hai Son, Chi-Hieu Nguyen, Dinh Thai Hoang, Diep N. Nguyen, Tran Thi Thuy Quynh, Trong-Minh Hoang, Nguyen Viet Ha, Eryk Dutkiewicz, Mohammad Abu Alsheikh, and Nguyen Linh Trung. Collaborative learning framework to detect attacks in transactions and smart contracts. IEEE Transactions on Cognitive Communications and Networking, November 2025 [early access]

    Tran Viet Khoa, Do Hai Son, Dinh Thai Hoang, Nguyen Linh Trung, Tran Thi Thuy Quynh, Nguyen Viet Ha, Diep N Nguyen, and Eryk Dutkiewicz. Collaborative learning for cyberattack detection in blockchain networks. IEEE Transactions on Systems, Man, Cybernetics: Systems, vol. 54, no 7, pages 3920-3933, July 2024.

    Bui Minh Tuan, Diep N. Nguyen, Nguyen Linh Trung, Van-Dinh Nguyen, Nguyen Van Huynh, Dinh Thai Hoang,
    Marwan Krunz, and Eryk Dutkiewicz. Securing MIMO wiretap channel with learning-based friendly jamming under imperfect CSI. IEEE Internet of Things Journal, vol. 12, no. 11, pages 16009-16022, June 2025.

    Tran Viet Khoa, Do Hai Son, Dinh Thai Hoang, Nguyen Linh Trung, Tran Thi Thuy Quynh, Nguyen Viet Ha, Diep N Nguyen, and Eryk Dutkiewicz. Collaborative learning for cyberattack detection in blockchain networks. IEEE Transactions on Systems, Man, Cybernetics: Systems, vol. 54, no 7, pages 3920-3933, July 2024.

    Bui Minh Tuan, Tran Viet Khoa, Do Hai Son, Nguyen Linh Trung, Tran Thi Thuy Quynh, Nguyen Viet Ha, Nguyen Ngoc Hoa, Nguyen Dai Tho, and Le Quang Minh. A new framework for cyber risk assessment for Industry 4.0 and recommendations for Vietnam. REV Journal on Electronics and Communications, vol. 13, no. 3-4, July-December 2023.

    Tran Viet Khoa, Dinh Thai Hoang, Nguyen Linh Trung, Cong T. Nguyen, Tran Thi Thuy Quynh, Diep N. Nguyen, Nguyen Viet Ha, and Eryk Dutkiewicz. Deep Transfer Learning: A Novel Collaborative Learning Model for Cyberattack Detection Systems in IoT Networks. IEEE Internet of Things Journal, vol. 10, no. 10, pp. 8578-8589, 2023.

    Do Hai Son, Tran Thi Thuy Quynh, Tran Viet Khoa, Dinh Thai Hoang, Nguyen Linh Trung, Nguyen Viet Ha, Dusit Niyato, Diep N. Nguyen, and Eryk Dutkiewicz. An effective framework of private Ethereum blockchain network for smart grid. International Conference on Advanced Technologies for Communications (ATC), Ho Chi Minh city, Vietnam, 2021. [Best paper award]

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