![Amir Javed BEng FHEA PhD(Cardiff) MSc(Information security and Privacy - Cardiff)](https://profiles-cardiff.imgix.net/attachments/1581?w=200&h=200&auto=format&crop=faces&fit=crop&q=90")
Dr Amir Javed
(he/him)
BEng FHEA PhD(Cardiff) MSc(Information security and Privacy - Cardiff)
- Available for postgraduate supervision
Teams and roles for Amir Javed
Senior Lecturer
Overview
I am a CISSP-certified cybersecurity professional, co-founder of Kesintel, and Senior Lecturer at Cardiff University, with a PhD in Cybersecurity and over a decade of combined academic and industry experience. My expertise includes malware behaviour, cyber analytics, risk management, and AI-driven threat detection. I currently lead the MSc programs in Cybersecurity and have previously collaborated with leading organisations such as GCHQ, Airbus, PwC, and Thaleson projects addressing cybercrime and social media threats. As a Domain Knowledge Expert at the Wales Cyber Innovation Hub, I support start-ups in developing innovative cybersecurity solutions. Prior to academia, I spent over eight years in the banking sector, which gives me a practical, interdisciplinary perspective on solving real-world cybersecurity challenges.
Publication
2025
- Briliyant, O. , Javed, A. and Cherdantseva, Y. 2025. Beyond automation gap: a survey on continuous compliance audit for IoT security. Computers and Security
- Briliyant, O. , Javed, A. and Cherdantseva, Y. 2025. Enhancing cybersecurity log analysis through Retrieval-Augmented Generation. Presented at: 3rd International Conference on Foundation and Large Language Model (FLLM) Vienna, Austria 25-28 November 2025.
- Briliyant, O. , Javed, A. and Cherdantseva, Y. 2025. Network packet security analysis chatbot using SQL-RAG approach and cybersecurity-tuned LLM. Presented at: 6th International Conference on Electrical, Communication and Computer Engineering (ICECCE) Istanbul, Turkey 27-28 August 2025. ieeexplore.
- Briliyant, O. , Javed, A. and Cherdantseva, Y. 2025. Physical tells digital threats: supervised ML-IDS for multimodal IoT telemetry in smart buildings. Presented at: International Conference on Cryptography, Informatics, and Cybersecurity 2025 Depok, Indonesia 22-23 October, 2025.
- Chaudhary, A. et al. 2025. Exploring the safe integration of generative AI in cybersecurity education: Addressing challenges in transparency, accuracy, and security. Presented at: 4th Annual Advances in Teaching and Learning for Cyber Security Education Bristol, UK 2 July 2024. Published in: Legg, P. , Coull, N. and Clarke, C. eds. Advances in Teaching and Learning for Cyber Security Education. Vol. 1213.Lecture Notes in Networks and Systems Vol. 1. Springer Cham. (10.1007/978-3-031-77524-6_1)
2024
- Al Lelah, T. et al. 2024. Detecting the abuse of cloud services for C&C infrastructure through dynamic analysis and machine learning. Presented at: 2024 International Symposium on Networks, Computers and Communications (ISNCC) Washington DC, USA 22-25 October 2024. 2024 International Symposium on Networks, Computers and Communications (ISNCC). IEEE. , pp.1-7. (10.1109/isncc62547.2024.10758940)
- Aloraini, F. and Javed, A. 2024. Adversarial attacks in intrusion detection systems: Triggering false alarms in connected and autonomous vehicles. Presented at: IEEE International Conference on Cyber Security and Resilience (CSR) London, UK 2-4 September 2024. 2024 IEEE International Conference on Cyber Security and Resilience (CSR). IEEE. , pp.714-719. (10.1109/csr61664.2024.10679419)
- Aloraini, F. , Javed, A. and Rana, O. 2024. Adversarial attacks on intrusion detection systems in in-vehicle networks of connected and autonomous vehicles. Sensors 24 (12) 3848. (10.3390/s24123848)
- Althunayyan, M. , Javed, A. and Rana, O. 2024. A robust multi-stage intrusion detection system for in-vehicle network security using hierarchical federated learning. Vehicular Communications 49 100837. (10.1016/j.vehcom.2024.100837)
- Althunayyan, M. , Javed, A. and Rana, O. 2024. An innovative feature selection approach for CAN bus data leveraging constant value analysis. Presented at: AI Applications in Cyber Security and Communication Networks Cardiff, UK 1–12 December 2023. Published in: Hewage, C. , Nawaf, L. and Kesswari, N. eds. Proceedings of Ninth International Conference on Cyber Security, Privacy in Communication Networks. Vol. 1032.Lecture Notes in Networks and Systems Singapore: Springer. , pp.69. (10.1007/978-981-97-3973-8_5)
- Althunayyan, M. et al. 2024. Hierarchical federated learning-based intrusion detection for in-vehicle networks. Future Internet 16 (12) 451. (10.3390/fi16120451)
- Williams, L. et al. 2024. Leveraging gamification and game-based learning in cybersecurity education: Engaging and inspiring non-cyber students. Journal of The Colloquium for Information Systems Security Education 11 (1)(10.53735/cisse.v11i1.186)
2023
- Ahmed, R. N. , Javed, A. and Bedewi, W. 2023. Is Covid-19 being used to spread Malware. SN Computer Science (4) 398. (10.1007/s42979-023-01838-6)
- Al lelah, T. et al. 2023. Machine learning detection of cloud services abuse as C&C Infrastructure. Journal of Cybersecurity and Privacy 3 (4), pp.858-881. (10.3390/jcp3040039)
- Al lelah, T. et al. 2023. Abuse of cloud-based and public legitimate services as command-and-control (C&C) infrastructure: a systematic literature review. Journal of Cybersecurity and Privacy 3 (3), pp.558-590. (10.3390/jcp3030027)
- Ikwu, R. et al. 2023. Digital fingerprinting for identifying malicious collusive groups on Twitter. Journal of Cybersecurity 9 (1) tyad014. (10.1093/cybsec/tyad014)
2022
- Aloraini, F. et al. 2022. Adversarial machine learning in IoT from an insider point of view. Journal of Information Security and Applications 70 103341. (10.1016/j.jisa.2022.103341)
- Javed, A. et al. 2022. Disrupting drive-by download networks on Twitter.. Social Network Analysis and Mining 12 (117)
- Javed, A. et al. 2022. Security analytics for real-time forecasting of cyberattacks. Software: Practice and Experience 52 (3), pp.788-804. (10.1002/spe.2822)
2021
- Aaisha, M. et al., 2021. A fuzzy-based approach to enhance cyber defence security for next-generation IoT. IEEE Internet of Things (10.1109/JIOT.2021.3053326)
- Anthi, E. et al. 2021. Hardening machine learning Denial of Service (DoS) defences against adversarial attacks in IoT smart home networks. Computers and Security 108 102352. (10.1016/j.cose.2021.102352)
- Lakoju, M. et al. 2021. "Chatty Devices” and edge-based activity classification. Discover Internet of Things 1 5. (10.1007/s43926-021-00004-9)
2020
- Javed, A. et al. 2020. Emotions behind drive-by download propagation on Twitter. ACM Transactions on the Web 14 (4) 16. (10.1145/3408894)
- Williams, M. L. et al. 2020. Hate in the machine: anti-black and anti-Muslim social media posts as predictors of offline racially and religiously aggravated crime. British Journal of Criminology 60 (1), pp.93-117. (10.1093/bjc/azz049)
2019
- Balakrishnan, V. et al., 2019. A comparative analysis of detection mechanisms for emotion detection. Presented at: International Conference Computer Science and Engineering (IC2SE 2019) Padang, Indonesia 26-27 April 2019. Vol. 1339.IOP Publishing. , pp.012016. (10.1088/1742-6596/1339/1/012016)
- Javed, A. 2019. Understanding malware behaviour in online social networks and predicting cyber attack. PhD Thesis , Cardiff University.
- Javed, A. , Burnap, P. and Rana, O. 2019. Prediction of drive-by download attacks on Twitter. Information Processing and Management 56 (3), pp.1133-1145. (10.1016/j.ipm.2018.02.003)
2018
- Alorainy, W. et al. 2018. Suspended accounts: A source of Tweets with disgust and anger emotions for augmenting hate speech data sample. Presented at: International Conference on Machine Learning and Cybernetics Chengdu, China 15-18 July 2018. 2018 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE. , pp.581-586. (10.1109/ICMLC.2018.8527001)
2017
- Anthi, E. et al. 2017. Secure data sharing and analysis in cloud-based energy management systems. Presented at: Second EAI International Conference, IISSC 2017 and CN4IoT 2017 Brindisi, Italy 20-21 April 2017. Published in: Longo, A. et al., IISSC 2017, CN4IoT 2017: Cloud Infrastructures, Services, and IoT Systems for Smart Cities. Vol. 189.Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Springer. , pp.228-242. (10.1007/978-3-319-67636-4_24)
- Javed, A. et al. 2017. Fog paradigm for local energy management systems. Presented at: Second EAI International Conference, IISSC 2017 and CN4IoT 2017 Brindisi, Italy 20-21 April 2017. Published in: Longo, A. et al., Cloud Infrastructures Services and IoT Systems for Smart Cities. Vol. 189.Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Cham: Springer. , pp.162-176. (10.1007/978-3-319-67636-4_18)
- Javed, A. et al. 2017. Scalable local energy management systems. Energy Procedia 142 , pp.3069-3074. (10.1016/j.egypro.2017.12.446)
- Marmaras, C. et al. 2017. Predicting the energy demand of buildings during triad peaks in GB. Energy and Buildings 141 , pp.262-273. (10.1016/j.enbuild.2017.02.046)
- Marmaras, C. et al., 2017. A cloud-based energy management system for building managers. Presented at: 8th ACM/SPEC on International Conference on Performance Engineering Companion L'Aquila, Italy 22-26 April 2017. ICPE '17: Companion Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion. Association for Computing Machinery. , pp.61-66. (10.1145/3053600.3053613)
2015
- Awan, M. S. K. et al. 2015. Continuous monitoring and assessment of cybersecurity risks in large computing infrastructures. Presented at: 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on High Performance Computing and Communications (HPCC New York City, NY, USA 24-26 August 2015. High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on. IEEE. , pp.1442-1447. (10.1109/HPCC-CSS-ICESS.2015.224)
- Burnap, P. et al. 2015. Real-time classification of malicious URLs on Twitter using Machine Activity Data. Presented at: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Paris, France 25-27 August 2015. 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). ACM. , pp.970-977. (10.1145/2808797.2809281)
Articles
- Aaisha, M. et al., 2021. A fuzzy-based approach to enhance cyber defence security for next-generation IoT. IEEE Internet of Things (10.1109/JIOT.2021.3053326)
- Ahmed, R. N. , Javed, A. and Bedewi, W. 2023. Is Covid-19 being used to spread Malware. SN Computer Science (4) 398. (10.1007/s42979-023-01838-6)
- Al lelah, T. et al. 2023. Machine learning detection of cloud services abuse as C&C Infrastructure. Journal of Cybersecurity and Privacy 3 (4), pp.858-881. (10.3390/jcp3040039)
- Al lelah, T. et al. 2023. Abuse of cloud-based and public legitimate services as command-and-control (C&C) infrastructure: a systematic literature review. Journal of Cybersecurity and Privacy 3 (3), pp.558-590. (10.3390/jcp3030027)
- Aloraini, F. , Javed, A. and Rana, O. 2024. Adversarial attacks on intrusion detection systems in in-vehicle networks of connected and autonomous vehicles. Sensors 24 (12) 3848. (10.3390/s24123848)
- Aloraini, F. et al. 2022. Adversarial machine learning in IoT from an insider point of view. Journal of Information Security and Applications 70 103341. (10.1016/j.jisa.2022.103341)
- Althunayyan, M. , Javed, A. and Rana, O. 2024. A robust multi-stage intrusion detection system for in-vehicle network security using hierarchical federated learning. Vehicular Communications 49 100837. (10.1016/j.vehcom.2024.100837)
- Althunayyan, M. et al. 2024. Hierarchical federated learning-based intrusion detection for in-vehicle networks. Future Internet 16 (12) 451. (10.3390/fi16120451)
- Anthi, E. et al. 2021. Hardening machine learning Denial of Service (DoS) defences against adversarial attacks in IoT smart home networks. Computers and Security 108 102352. (10.1016/j.cose.2021.102352)
- Briliyant, O. , Javed, A. and Cherdantseva, Y. 2025. Beyond automation gap: a survey on continuous compliance audit for IoT security. Computers and Security
- Ikwu, R. et al. 2023. Digital fingerprinting for identifying malicious collusive groups on Twitter. Journal of Cybersecurity 9 (1) tyad014. (10.1093/cybsec/tyad014)
- Javed, A. , Burnap, P. and Rana, O. 2019. Prediction of drive-by download attacks on Twitter. Information Processing and Management 56 (3), pp.1133-1145. (10.1016/j.ipm.2018.02.003)
- Javed, A. et al. 2020. Emotions behind drive-by download propagation on Twitter. ACM Transactions on the Web 14 (4) 16. (10.1145/3408894)
- Javed, A. et al. 2022. Disrupting drive-by download networks on Twitter.. Social Network Analysis and Mining 12 (117)
- Javed, A. et al. 2022. Security analytics for real-time forecasting of cyberattacks. Software: Practice and Experience 52 (3), pp.788-804. (10.1002/spe.2822)
- Javed, A. et al. 2017. Scalable local energy management systems. Energy Procedia 142 , pp.3069-3074. (10.1016/j.egypro.2017.12.446)
- Lakoju, M. et al. 2021. "Chatty Devices” and edge-based activity classification. Discover Internet of Things 1 5. (10.1007/s43926-021-00004-9)
- Marmaras, C. et al. 2017. Predicting the energy demand of buildings during triad peaks in GB. Energy and Buildings 141 , pp.262-273. (10.1016/j.enbuild.2017.02.046)
- Williams, L. et al. 2024. Leveraging gamification and game-based learning in cybersecurity education: Engaging and inspiring non-cyber students. Journal of The Colloquium for Information Systems Security Education 11 (1)(10.53735/cisse.v11i1.186)
- Williams, M. L. et al. 2020. Hate in the machine: anti-black and anti-Muslim social media posts as predictors of offline racially and religiously aggravated crime. British Journal of Criminology 60 (1), pp.93-117. (10.1093/bjc/azz049)
Conferences
- Al Lelah, T. et al. 2024. Detecting the abuse of cloud services for C&C infrastructure through dynamic analysis and machine learning. Presented at: 2024 International Symposium on Networks, Computers and Communications (ISNCC) Washington DC, USA 22-25 October 2024. 2024 International Symposium on Networks, Computers and Communications (ISNCC). IEEE. , pp.1-7. (10.1109/isncc62547.2024.10758940)
- Aloraini, F. and Javed, A. 2024. Adversarial attacks in intrusion detection systems: Triggering false alarms in connected and autonomous vehicles. Presented at: IEEE International Conference on Cyber Security and Resilience (CSR) London, UK 2-4 September 2024. 2024 IEEE International Conference on Cyber Security and Resilience (CSR). IEEE. , pp.714-719. (10.1109/csr61664.2024.10679419)
- Alorainy, W. et al. 2018. Suspended accounts: A source of Tweets with disgust and anger emotions for augmenting hate speech data sample. Presented at: International Conference on Machine Learning and Cybernetics Chengdu, China 15-18 July 2018. 2018 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE. , pp.581-586. (10.1109/ICMLC.2018.8527001)
- Althunayyan, M. , Javed, A. and Rana, O. 2024. An innovative feature selection approach for CAN bus data leveraging constant value analysis. Presented at: AI Applications in Cyber Security and Communication Networks Cardiff, UK 1–12 December 2023. Published in: Hewage, C. , Nawaf, L. and Kesswari, N. eds. Proceedings of Ninth International Conference on Cyber Security, Privacy in Communication Networks. Vol. 1032.Lecture Notes in Networks and Systems Singapore: Springer. , pp.69. (10.1007/978-981-97-3973-8_5)
- Anthi, E. et al. 2017. Secure data sharing and analysis in cloud-based energy management systems. Presented at: Second EAI International Conference, IISSC 2017 and CN4IoT 2017 Brindisi, Italy 20-21 April 2017. Published in: Longo, A. et al., IISSC 2017, CN4IoT 2017: Cloud Infrastructures, Services, and IoT Systems for Smart Cities. Vol. 189.Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Springer. , pp.228-242. (10.1007/978-3-319-67636-4_24)
- Awan, M. S. K. et al. 2015. Continuous monitoring and assessment of cybersecurity risks in large computing infrastructures. Presented at: 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on High Performance Computing and Communications (HPCC New York City, NY, USA 24-26 August 2015. High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on. IEEE. , pp.1442-1447. (10.1109/HPCC-CSS-ICESS.2015.224)
- Balakrishnan, V. et al., 2019. A comparative analysis of detection mechanisms for emotion detection. Presented at: International Conference Computer Science and Engineering (IC2SE 2019) Padang, Indonesia 26-27 April 2019. Vol. 1339.IOP Publishing. , pp.012016. (10.1088/1742-6596/1339/1/012016)
- Briliyant, O. , Javed, A. and Cherdantseva, Y. 2025. Enhancing cybersecurity log analysis through Retrieval-Augmented Generation. Presented at: 3rd International Conference on Foundation and Large Language Model (FLLM) Vienna, Austria 25-28 November 2025.
- Briliyant, O. , Javed, A. and Cherdantseva, Y. 2025. Network packet security analysis chatbot using SQL-RAG approach and cybersecurity-tuned LLM. Presented at: 6th International Conference on Electrical, Communication and Computer Engineering (ICECCE) Istanbul, Turkey 27-28 August 2025. ieeexplore.
- Briliyant, O. , Javed, A. and Cherdantseva, Y. 2025. Physical tells digital threats: supervised ML-IDS for multimodal IoT telemetry in smart buildings. Presented at: International Conference on Cryptography, Informatics, and Cybersecurity 2025 Depok, Indonesia 22-23 October, 2025.
- Burnap, P. et al. 2015. Real-time classification of malicious URLs on Twitter using Machine Activity Data. Presented at: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Paris, France 25-27 August 2015. 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). ACM. , pp.970-977. (10.1145/2808797.2809281)
- Chaudhary, A. et al. 2025. Exploring the safe integration of generative AI in cybersecurity education: Addressing challenges in transparency, accuracy, and security. Presented at: 4th Annual Advances in Teaching and Learning for Cyber Security Education Bristol, UK 2 July 2024. Published in: Legg, P. , Coull, N. and Clarke, C. eds. Advances in Teaching and Learning for Cyber Security Education. Vol. 1213.Lecture Notes in Networks and Systems Vol. 1. Springer Cham. (10.1007/978-3-031-77524-6_1)
- Javed, A. et al. 2017. Fog paradigm for local energy management systems. Presented at: Second EAI International Conference, IISSC 2017 and CN4IoT 2017 Brindisi, Italy 20-21 April 2017. Published in: Longo, A. et al., Cloud Infrastructures Services and IoT Systems for Smart Cities. Vol. 189.Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Cham: Springer. , pp.162-176. (10.1007/978-3-319-67636-4_18)
- Marmaras, C. et al., 2017. A cloud-based energy management system for building managers. Presented at: 8th ACM/SPEC on International Conference on Performance Engineering Companion L'Aquila, Italy 22-26 April 2017. ICPE '17: Companion Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion. Association for Computing Machinery. , pp.61-66. (10.1145/3053600.3053613)
Thesis
- Javed, A. 2019. Understanding malware behaviour in online social networks and predicting cyber attack. PhD Thesis , Cardiff University.
Research
Since completing my PhD, my research has centred on understanding cybercriminal behaviour, leading to the development of pioneering techniques for the early detection and mitigation of cyber-attacks—efforts that ultimately led to the co-founding of Kesintel. My work bridges human and machine behavioural analysis, uncovering how adversaries exploit human vulnerabilities to propagate malware, particularly across online social networks (OSNs).
I have developed predictive models for drive-by-download attacks, intelligent node removal strategies, and behaviour-based detection systems, with findings published in top-tier cybersecurity journals. Collaborations with experts in social science, criminology, and industry have extended the real-world impact of my research, contributing to the identification of organised criminal networks on OSNs and enhancing the resilience of machine learning models against evolving cyber threats.
International recognition of my work includes funded research collaborations across India, New Zealand, and the USA, as well as keynote invitations and the deployment of AI-powered cyber incident reporting platforms for law enforcement agencies.
Collectively, my research advances both the theoretical foundations and practical applications of cybersecurity, contributing to the development of safer digital ecosystems through behavioural insight, cross-disciplinary collaboration, and technical innovation.
Teaching
CMT116- Cyber Security and Risk - Module lead
CMT217- Module Support.
Biography
Professional memberships
CISSP
Academic positions
- 2019-Preset: Lecturer, Cardiff University
- 2015-2019- Research Associate, Cardiff University
- *WEFO collaboration with Airbus around human security,
- The EPSRC Ebb and Flow Energy Systems project
- The ESRC HateLab project at Cardiff University
Supervisions
I am available for postgraduate supervision. However, I would expect the student to submit a proposal highlighting the below-mentioned points.
- The scope of your project (i.e. what are the research questions and problems?)
- The current state of the art (i.e. summarise the existing literature that has been published on your chosen research topic)
- Current limitations (i.e. identify the "gaps" in existing literature in relation to the scope of your project)
- Proposed methods (i.e. what computational or modelling methods will you use to tackle the current limitations and develop new knowledge?)
- Anticipated contribution to Computer Science (i.e. what will we know after your PhD that we do not know now?)
Current supervision
Turki Al Lelah Al Lelah
Contact Details
Specialisms
- AI & Machine Learning
- Cybercrime
- Cybersecurity
- cyber resilience
- Cybersecurity and privacy
