AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can expand the Abstract, Links and BibTex record for each paper.
2025
Ahmed, Y.; Eissa, A.; Harb, O.; Miniesy, O.; Miniesy, Z.; Noureldin, M.; Mougy, A. E.
From Abstract Prompts to Cybersecurity Labs: Automating Virtual Environment Design and Deployment with Multi-Agent Systems and LLM-Driven Orchestration Proceedings Article
In: Alsmirat, M.; Alkhabbas, F.; Al-Abdullah, M.; Jararweh, Y. (Ed.): pp. 99–107, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798350392920 (ISBN).
Abstract | Links | BibTeX | Tags: Automated scenario generation, Containerization, Containers, Cybe range, cyber ranges, Cyber security, Cybersecurity, Cybersecurity training, Docker, Environment generation cybe range lab generation, environment generation cyber range lab generation, Intelligent Agents, Language Model, Large language model, large language models (LLMs), Multi agent systems, Multi-agent systems, Multiagent systems (MASs), Network Security, Personnel training, Quality assurance, Scalability, Scenarios generation, Virtual Reality
@inproceedings{ahmed_abstract_2025,
title = {From Abstract Prompts to Cybersecurity Labs: Automating Virtual Environment Design and Deployment with Multi-Agent Systems and LLM-Driven Orchestration},
author = {Y. Ahmed and A. Eissa and O. Harb and O. Miniesy and Z. Miniesy and M. Noureldin and A. E. Mougy},
editor = {M. Alsmirat and F. Alkhabbas and M. Al-Abdullah and Y. Jararweh},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105016685428&doi=10.1109%2FICSC65596.2025.11140357&partnerID=40&md5=053515e92d70c5c694cc8ba888f39afa},
doi = {10.1109/ICSC65596.2025.11140357},
isbn = {9798350392920 (ISBN)},
year = {2025},
date = {2025-01-01},
pages = {99–107},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Cyber ranges are essential for cybersecurity training, but current systems face challenges like resource-intensive infrastructures, static configurations, and laborious setups, limiting scalability and accessibility, especially for educational institutions with fewer resources. To address these issues, this paper introduces a containerized multi-agent system that automates the design and deployment of cybersecurity training environments. Using large language models (LLMs) for scenario orchestration, the system transforms natural language prompts into fully functional environments through Docker containerization. It features three specialized agents: a master agent for scenario planning, machine worker agents for environment and vulnerability generation, and a quality assurance agent for validation and debugging, ensuring modularity, scalability, and precision. Evaluated across 14 diverse attack scenarios, the system demonstrates high accuracy in generating web vulnerabilities, network exploits, and multi-step attacks. By automating scenario creation and deployment, this system enhances cybersecurity education and training, bridging critical gaps and offering a scalable, adaptive, and resource-efficient solution to meet the growing demand for skilled cybersecurity professionals. © 2025 Elsevier B.V., All rights reserved.},
keywords = {Automated scenario generation, Containerization, Containers, Cybe range, cyber ranges, Cyber security, Cybersecurity, Cybersecurity training, Docker, Environment generation cybe range lab generation, environment generation cyber range lab generation, Intelligent Agents, Language Model, Large language model, large language models (LLMs), Multi agent systems, Multi-agent systems, Multiagent systems (MASs), Network Security, Personnel training, Quality assurance, Scalability, Scenarios generation, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
Cyber ranges are essential for cybersecurity training, but current systems face challenges like resource-intensive infrastructures, static configurations, and laborious setups, limiting scalability and accessibility, especially for educational institutions with fewer resources. To address these issues, this paper introduces a containerized multi-agent system that automates the design and deployment of cybersecurity training environments. Using large language models (LLMs) for scenario orchestration, the system transforms natural language prompts into fully functional environments through Docker containerization. It features three specialized agents: a master agent for scenario planning, machine worker agents for environment and vulnerability generation, and a quality assurance agent for validation and debugging, ensuring modularity, scalability, and precision. Evaluated across 14 diverse attack scenarios, the system demonstrates high accuracy in generating web vulnerabilities, network exploits, and multi-step attacks. By automating scenario creation and deployment, this system enhances cybersecurity education and training, bridging critical gaps and offering a scalable, adaptive, and resource-efficient solution to meet the growing demand for skilled cybersecurity professionals. © 2025 Elsevier B.V., All rights reserved.
2024
Williams, R.
Deep HoriXons - 3D Virtual Generative AI Assisted Campus for Deep Learning AI and Cybersecurity Proceedings Article
In: M., Blowers; B.T., Wysocki (Ed.): Proc SPIE Int Soc Opt Eng, SPIE, 2024, ISBN: 0277786X (ISSN); 978-151067434-9 (ISBN).
Abstract | Links | BibTeX | Tags: 3D virtual campus, AI and cybersecurity education, AI talent pipeline, ChatGPT digital tutor, CompTIA Security+, Computer aided instruction, Cyber security, Cyber-security educations, Cybersecurity, Deep learning, E-Learning, Immersive, Learning systems, Virtual campus, Virtual learning environments, Virtual Reality
@inproceedings{williams_deep_2024,
title = {Deep HoriXons - 3D Virtual Generative AI Assisted Campus for Deep Learning AI and Cybersecurity},
author = {R. Williams},
editor = {Blowers M. and Wysocki B.T.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196555361&doi=10.1117%2f12.3011374&partnerID=40&md5=ff7392a37a51044c79d4d2824c9cf46b},
doi = {10.1117/12.3011374},
isbn = {0277786X (ISSN); 978-151067434-9 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc SPIE Int Soc Opt Eng},
volume = {13058},
publisher = {SPIE},
abstract = {This abstract outlines two significant innovations in AI and cybersecurity education within the "Deep HoriXons" 3D virtual campus, addressing the urgent need for skilled professionals in these domains. First, the paper introduces "Deep HoriXons," an immersive 3D virtual learning environment designed to democratize and enhance the educational experience for AI and cybersecurity. This innovation is notable for its global accessibility and ability to simulate real-world scenarios, providing an interactive platform for experiential learning, which is a marked departure from traditional educational models. The second innovation discussed is the strategic integration of ChatGPT as a digital educator and tutor within this virtual environment. ChatGPT's role is pivotal in offering tailored, real-time educational support, making complex AI and cybersecurity concepts more accessible and engaging for learners. This application of ChatGPT is an innovation worth noting for its ability to adapt to individual learning styles, provide interactive scenario-based learning, and support a deeper understanding of technical subjects through dynamic, responsive interaction. Together, these innovations represent a significant advancement in the field of AI and cybersecurity education, addressing the critical talent shortage by making high-quality, interactive learning experiences accessible on a global scale. The paper highlights the importance of these innovations in creating a skilled workforce capable of tackling the evolving challenges in AI and cybersecurity, underscoring the need for ongoing research and development in this area. © 2024 SPIE.},
keywords = {3D virtual campus, AI and cybersecurity education, AI talent pipeline, ChatGPT digital tutor, CompTIA Security+, Computer aided instruction, Cyber security, Cyber-security educations, Cybersecurity, Deep learning, E-Learning, Immersive, Learning systems, Virtual campus, Virtual learning environments, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
This abstract outlines two significant innovations in AI and cybersecurity education within the "Deep HoriXons" 3D virtual campus, addressing the urgent need for skilled professionals in these domains. First, the paper introduces "Deep HoriXons," an immersive 3D virtual learning environment designed to democratize and enhance the educational experience for AI and cybersecurity. This innovation is notable for its global accessibility and ability to simulate real-world scenarios, providing an interactive platform for experiential learning, which is a marked departure from traditional educational models. The second innovation discussed is the strategic integration of ChatGPT as a digital educator and tutor within this virtual environment. ChatGPT's role is pivotal in offering tailored, real-time educational support, making complex AI and cybersecurity concepts more accessible and engaging for learners. This application of ChatGPT is an innovation worth noting for its ability to adapt to individual learning styles, provide interactive scenario-based learning, and support a deeper understanding of technical subjects through dynamic, responsive interaction. Together, these innovations represent a significant advancement in the field of AI and cybersecurity education, addressing the critical talent shortage by making high-quality, interactive learning experiences accessible on a global scale. The paper highlights the importance of these innovations in creating a skilled workforce capable of tackling the evolving challenges in AI and cybersecurity, underscoring the need for ongoing research and development in this area. © 2024 SPIE.
Chandrashekar, N. Donekal; Lee, A.; Azab, M.; Grǎcanin, D.
Understanding User Behavior for Enhancing Cybersecurity Training with Immersive Gamified Platforms Journal Article
In: Information (Switzerland), vol. 15, no. 12, 2024, ISSN: 20782489 (ISSN), (Publisher: Multidisciplinary Digital Publishing Institute (MDPI)).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Critical infrastructures, Cyber attacks, Cyber security, Cyber systems, Cyber-attacks, Cybersecurity, Decisions makings, Digital infrastructures, digital twin, Extended reality, Gamification, Immersive, Network Security, simulation, Technical vulnerabilities, Training, user behavior, User behaviors
@article{donekal_chandrashekar_understanding_2024,
title = {Understanding User Behavior for Enhancing Cybersecurity Training with Immersive Gamified Platforms},
author = {N. Donekal Chandrashekar and A. Lee and M. Azab and D. Grǎcanin},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213435167&doi=10.3390%2Finfo15120814&partnerID=40&md5=9e015d2d280ef872e30ad46db0781ce8},
doi = {10.3390/info15120814},
issn = {20782489 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {Information (Switzerland)},
volume = {15},
number = {12},
abstract = {In modern digital infrastructure, cyber systems are foundational, making resilience against sophisticated attacks essential. Traditional cybersecurity defenses primarily address technical vulnerabilities; however, the human element, particularly decision-making during cyber attacks, adds complexities that current behavioral studies fail to capture adequately. Existing approaches, including theoretical models, game theory, and simulators, rely on retrospective data and static scenarios. These methods often miss the real-time, context-specific nature of user responses during cyber threats. To address these limitations, this work introduces a framework that combines Extended Reality (XR) and Generative Artificial Intelligence (Gen-AI) within a gamified platform. This framework enables continuous, high-fidelity data collection on user behavior in dynamic attack scenarios. It includes three core modules: the Player Behavior Module (PBM), Gamification Module (GM), and Simulation Module (SM). Together, these modules create an immersive, responsive environment for studying user interactions. A case study in a simulated critical infrastructure environment demonstrates the framework’s effectiveness in capturing realistic user behaviors under cyber attack, with potential applications for improving response strategies and resilience across critical sectors. This work lays the foundation for adaptive cybersecurity training and user-centered development across critical infrastructure. © 2024 Elsevier B.V., All rights reserved.},
note = {Publisher: Multidisciplinary Digital Publishing Institute (MDPI)},
keywords = {Artificial intelligence, Critical infrastructures, Cyber attacks, Cyber security, Cyber systems, Cyber-attacks, Cybersecurity, Decisions makings, Digital infrastructures, digital twin, Extended reality, Gamification, Immersive, Network Security, simulation, Technical vulnerabilities, Training, user behavior, User behaviors},
pubstate = {published},
tppubtype = {article}
}
In modern digital infrastructure, cyber systems are foundational, making resilience against sophisticated attacks essential. Traditional cybersecurity defenses primarily address technical vulnerabilities; however, the human element, particularly decision-making during cyber attacks, adds complexities that current behavioral studies fail to capture adequately. Existing approaches, including theoretical models, game theory, and simulators, rely on retrospective data and static scenarios. These methods often miss the real-time, context-specific nature of user responses during cyber threats. To address these limitations, this work introduces a framework that combines Extended Reality (XR) and Generative Artificial Intelligence (Gen-AI) within a gamified platform. This framework enables continuous, high-fidelity data collection on user behavior in dynamic attack scenarios. It includes three core modules: the Player Behavior Module (PBM), Gamification Module (GM), and Simulation Module (SM). Together, these modules create an immersive, responsive environment for studying user interactions. A case study in a simulated critical infrastructure environment demonstrates the framework’s effectiveness in capturing realistic user behaviors under cyber attack, with potential applications for improving response strategies and resilience across critical sectors. This work lays the foundation for adaptive cybersecurity training and user-centered development across critical infrastructure. © 2024 Elsevier B.V., All rights reserved.
Baldry, M. K.; Happa, J.; Steed, A.; Smith, S.; Glencross, M.
From Embodied Abuse to Mass Disruption: Generative, Inter-Reality Threats in Social, Mixed-Reality Platforms Journal Article
In: Digital Threats: Research and Practice, vol. 5, no. 4, 2024, ISSN: 25765337 (ISSN), (Publisher: Association for Computing Machinery).
Abstract | Links | BibTeX | Tags: Abuse, Augmented Reality, Cyber security, Cybersecurity, Extended reality, Game, Games, Generative adversarial networks, Harassment, Harm, harms, Mixed reality, risk, Social engineering, Social gaming, Social platform, social platforms, Social psychology, Virtual environments, Virtual Reality
@article{baldry_embodied_2024,
title = {From Embodied Abuse to Mass Disruption: Generative, Inter-Reality Threats in Social, Mixed-Reality Platforms},
author = {M. K. Baldry and J. Happa and A. Steed and S. Smith and M. Glencross},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212265918&doi=10.1145%2F3696015&partnerID=40&md5=3365120749356b35e6a5d947a2c42e11},
doi = {10.1145/3696015},
issn = {25765337 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {Digital Threats: Research and Practice},
volume = {5},
number = {4},
abstract = {Extended Reality (XR) platforms can expose users to novel attacks including embodied abuse and/or AI attacks-at-scale. The expanded attack surfaces of XR technologies may expose users of shared online platforms to psychological/social and physiological harms via embodied interactions with potentially millions of other humans or artificial humans, causing what we define as an inter-reality attack. The past 20 years have demonstrated how social and other harms (e.g., bullying, assault and stalking) can and do shift to digital social media and gaming platforms. XR technologies becoming more mainstream has led to investigations of ethical and technical consequences of these expanded input surfaces. However, there is limited literature that investigates social attacks, particularly towards vulnerable communities, and how AI technologies may accelerate generative attacks-at-scale. This article employs human-centred research methods and a harms-centred Cybersecurity framework to co-design a testbed of socio-technical attack scenarios in XR social gaming platforms. It uses speculative fiction to further extrapolate how these could reach attacks-at-scale by applying generative AI techniques. It develops an Inter-Reality Threat Model to outline how actions in virtual environments can impact on the real-world. As AI capability continues to rapidly develop, this article articulates the urgent need to consider a future where XR-AI attacks-at-scale could become commonplace. © 2024 Elsevier B.V., All rights reserved.},
note = {Publisher: Association for Computing Machinery},
keywords = {Abuse, Augmented Reality, Cyber security, Cybersecurity, Extended reality, Game, Games, Generative adversarial networks, Harassment, Harm, harms, Mixed reality, risk, Social engineering, Social gaming, Social platform, social platforms, Social psychology, Virtual environments, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
Extended Reality (XR) platforms can expose users to novel attacks including embodied abuse and/or AI attacks-at-scale. The expanded attack surfaces of XR technologies may expose users of shared online platforms to psychological/social and physiological harms via embodied interactions with potentially millions of other humans or artificial humans, causing what we define as an inter-reality attack. The past 20 years have demonstrated how social and other harms (e.g., bullying, assault and stalking) can and do shift to digital social media and gaming platforms. XR technologies becoming more mainstream has led to investigations of ethical and technical consequences of these expanded input surfaces. However, there is limited literature that investigates social attacks, particularly towards vulnerable communities, and how AI technologies may accelerate generative attacks-at-scale. This article employs human-centred research methods and a harms-centred Cybersecurity framework to co-design a testbed of socio-technical attack scenarios in XR social gaming platforms. It uses speculative fiction to further extrapolate how these could reach attacks-at-scale by applying generative AI techniques. It develops an Inter-Reality Threat Model to outline how actions in virtual environments can impact on the real-world. As AI capability continues to rapidly develop, this article articulates the urgent need to consider a future where XR-AI attacks-at-scale could become commonplace. © 2024 Elsevier B.V., All rights reserved.