Kostas is an expert in Network Security and Threat Modelling, he holds a position as a Senior Lecturer in Digital Communications. His research interests include the application of Machine and Deep Learning techniques on next-generation communication networks, IoT and Industrial Control Systems with a focus on security, trust and privacy. For more information on his research see his website.
Prior to his current academic position, Kostas worked as a Research Associate gaining experience in cross-layer measurements on Wired and Wireless Computer Networks, Anomaly Based Intrusion Detection and Knowledge Engineering. He strongly believes that research should aim to have an impact beyond the academic world, and to this end, he licensed research output through LU's Enterprise Office, engaged in Entrepreneurial activities (ANTHEM project) and collaborates with industry in research projects.
Characterised by his interest in cross-disciplinary collaborations, Kostas is an affiliated member of the NetSys research group in Computer Science, Advanced Virtual Reality Research Center, and the Centre for Information Management in Business School. Furthermore, he has worked and collaborated with many leading universities in the UK and Internationally from his involvement in research projects.
A member of the IEEE and the IEEE Communications Society, Kostas has chaired several sessions at International conferences and has been invited to review articles in conferences and journals, including:
- IEEE Transactions on Systems, Man, and Cybernetics: Systems
- IEEE Transactions on Cybernetics
- SpringerBriefs, Springer-Verlag
- IEEE ICC
- IEEE MILCOM
- Best paper award: G. Escudero-Andreu, Konstantinos G. Kyriakopoulos, James Flint, Sangarapillai Lambotharan, “Detecting Signalling DoS Attacks on LTE Networks”, INISCOM 2019 - 5th EAI International Conference on Industrial Networks and Intelligent Systems, Ho Chi Minh, Vietnam, 19-20 August 2019, Springer.
- Full studentship from Loughborough University for the three years of my PhD research. 2004 - 2007
- State Scholarships Foundation (IKY - Greece) sponsorship and award for the induction in the ﬁrst place of my undergraduate programme and distinction throughout my undergraduate studies. 1999 - 2002
Current research areas
- Security and AIOps in converged IT/OT environments:
- Industry 4.0, smart manufacturing
- Building Management Systems
- Transportation & Logistics
- Network Security:
- Understanding adversarial behaviour:
- Multi-stage Attacks / Advanced Persistent Threats
- Threat modelling
- Network Behaviour Analysis
- Anomaly Based Intrusion Detection Systems
- Encrypted Traffic Analysis
- Decision-making and predictive analytics
- Evidence Theory (Dempster Shafer),
- Machine Learning
- Support Vector Machines
- Hidden Markov Models
- Reinforcement Learning
- (Temporal Difference, Q-Learning)
- Situational Awareness: Observe, Orient, Decide, Act (OODA) loop
- Knowledge Representation:
- Fuzzy Cognitive Maps
- Network traffic analysis with signal processing techniques (Wavelet Transformation)
- Content delivery in Fog Networks
Grants and contracts
- DASA - Autonomous Resilient Cyber Defence: Intelligent Agents [Jan. 2023 – Aug. 2023] “Causal Inference for Cyber Security”, £175K, Local PI. The project aims to produce causal models for scenarios in cyber-security and utilise these in an adversarial setting to understand how a cyber-defender can act optimally to defend a network from hostile or malicious parties.
- DCMS / Innovate UK - CyberASAP programme Phase 2 [Sep. 2022 – Feb. 2023] “AI-driven Attack Graphs for Threat Modelling (ANTHEM)”, £59.3K, PI. Continuing from Phase 1, this project develops the Proof of Concept for ANTHEM towards automating threat modelling procedures in smart manufacturing and demonstrating the key capabilities of the tool in laboratory environments.
- DASA - Autonomous Resilient Cyber Defence: Intelligent Agents [July 2022 – June 2023] “Intelligent Asset Parameterisation for Risk-based Moving Target Defence”, £300K, Local PI. Responsible for formulating a risk-oriented asset re-parameterisation system leveraging Reinforcement Learning to optimise Moving Target Defence at runtime. The system re-parameterises asset configuration based on distributed intelligent agents that capture cyber observables related to threat exposure and the efficacy of deployed controls.
- DCMS / Innovate UK - CyberASAP programme Phase 1 [April 2022 – July 2022] “AI-driven Attack Graphs for Threat Modelling (ANTHEM)”, £27K, PI. This project is about commercialising research ideas related to an autonomous threat modelling tool that enables key stakeholders to identify and address threats rooted in software applications and the underlying network infrastructure.
- An industry-funded research project, Ectivise [July 2022 – June 2028] “Digital technologies for enabling predictive analytics in Business Management Systems”, £108K, PI. Supervision of research work leveraging IT infrastructure and real-time analysis of large amounts of distributed data to transform the currently reactive maintenance Business Management Systems towards predictive maintenance.
- UKRI InnovateUK, Knowledge Transfer Partnerships (KTP) [Mar. 2022 – Feb. 2023] “Bus-MONITOR: Measuring Operationally Needed Information Through Onboard Resources”, £195K, co-investigator and KTP supervisor of KTP associate based at Vectare. Responsibilities include directing associate on the IoT sensor data to cloud transmission, storage, visualisation and forecasting with ML algorithms on AWS.
- British Council, Institutional Links [Aug. 2017 – Aug. 2019] “Cyber Security Challenges for Internet of Things and Core Networks”, £332K, co-investigator, supervising 1 post-doc for a 2-year project. I have led work packages pertaining to Evidence Theory and sequence pattern analysis (Hidden Markov Models) for detection of wireless injection and multi-stage attacks, respectively.
- Amazon Web Services Cloud Credits for Research Program Awarded “Cybersecurity Test Facility as a Service”, $1500. The project’s aim was to build a cloud-based Cyber Range environment for staging and detecting attacks through cloud-based measurements and ML techniques.
Dr. Kyriakopoulos’ teaching expertise includes subjects pertaining to Internet, Networks and Network Security. Other module participation includes modules related to programming.
Academic member of NCSC’s Industrial Control Systems, Community of Interest