An expert in Computer Networks and Network Security, Kostas holds a position as a Lecturer in Digital Communications in Signal Processing and Networks (SPN) group. His research interests includes 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 also his website.

Prior to his current position, Kostas has 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 has previously licensed research outputs through LU's Enterprise Office.

Characterised by his interest in cross-disciplinary collaborations, Kostas is an affiliated member of the Advanced Virtual Reality Research Center, led by Professor Roy Kalawsky, and the Centre for Information Management in Business School. Furthermore, he has worked and collaborated with many leading universities in UK and Internationally from his involvement in EPSRC projects.

A member of the IEEE and the IEEE Communications Society, Kostas has chaired several sessions in 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

You can also find him in GoogleScholar, view his LinkedIn account or check his ResearchGate account.

Dr. Kyriakopoulos is currently leading the networks team of the Signal Processing and Networks group. His research interests include: anomaly-based Intrusion Detection Systems, multi-stage attacks, data fusion, integrating contextual information into decision making, and content delivery. Previously, he was also in the Institute for Digital Technologies at LU’s London campus.

He received his PhD degree in Computer Networks from Loughborough University, UK, in 2008, where he worked until 2015 as a Research Associate leading or contributing on the following projects:

Network flow management using ontologies Oct. 2013 – Sep. 2015
Developed a semantically aware web application for managing multiple network monitoring sources using abstract and human intuitive terminology. Implemented ontologies for representing knowledge information, Postgres SQL databases for storing netflow data, and created an interactive GUI website using the R Shiny web framework.

EPSRC-DSTL: Signal Processing Solutions for the Networked Battlespace - £3.65M Oct. 2013 – June 2015
Collaborated in research activities towards automatically labelling datasets using unsupervised machine learning techniques. Also, leveraged contextual information to identify anomalous patterns. Particularly, the users’ Pattern-of-Life in a network environment was used to identify traffic that does not abide to normal patterns.

EPSRC: Cross Layer Techniques for Intrusion Tolerant Networks - £175K Oct. 2010 – Sep. 2013
His responsibilities included the development of an on-line wireless monitoring tool with the purpose of detecting wireless network attacks using cross-layer metrics and data fusion techniques (Dempster-Shafer). Prototype software tool has been developed for Linux and Microsoft .Net framework and licensed to an Industrial company.

EPSRC: Enhancing Networks and Wireless Research - £537K Oct. 2007 – Sep. 2010
This platform grant project researched on measuring the performance of wireless and wired converged networks with a cross-layer approach. Investigated the effect of physical layer characteristics, e.g. channel power, noise and interference, on the performance of higher layers, e.g. packet loss, congestion or QoS during video streaming.

Dr. Kyriakopoulos has been a Co-I in the British Council Founded project: “Cyber Security Challenges for Internet of Things and Core Networks”. More details in this link.

Current research areas:

• Network intrusion detection and network security for wired, wireless, virtual and cloud networks
• Intelligent decision making based on network traffic conditions and contextual information
• Performance measurement in next generation network paradigms (Fog Networks and Software Defined Networks)
• Content delivery in Fog Networks
• Security and management in Industry 4.0 environments
• 5G integration with autonomous vehicles and IoT

Research Skills/Expertise:

• Anomaly based Intrusion Detection Systems
• Machine Learning (Support Vector Machines, Hidden Markov Models)
• Data Fusion algorithms (Dempster Shafer, Basic Probability Assignment)
• Context and Knowledge Representation (Ontologies, Fuzzy Cognitive Maps)
• Network traffic analysis with signal processing techniques (Wavelet Transformation)
• Deep Reinforcement Learning (Temporal Difference, Q-Learning)

Practical Skills:

• Penetration Testing
• AWS
• ESXi virtualisation platform
• SQL databases, SPARQL
• Programming: Python, C, R, Matlab, Perl
• Website development: R Shiny
• Scripting languages: Bash, awk, sed
• Linux systems and services configuration: DHCP, DNS, SAMBA, Apache, Cisco Nexus

Dr. Kyriakopoulos’ teaching expertise includes subjects pertaining to "Internet and Communication Networks" and "Computer Network Security”.  Other module participation includes:

WSA010 Programming and Software Design

Selected Publications of the last 3 years (updated end of 2019) 

1. Ibrahim Ghafir, Konstantinos G. Kyriakopoulos, Sangarapillai Lambotharan, Francisco J. Aparicio- Navarro, Basil AsSadhan, Hamad BinSalleeh, Diab, “Hidden Markov Models and Alert Correlations for the Prediction of Advanced Persistent Threats”, IEEE Access, vol. 7, issue 1, pp 99508–99520, 2019, IEEE.

2. Timothy Chadza, Konstantinos G. Kyriakopoulos, Sangarapillai Lambotharan, “Contemporary Sequential Network Attacks Prediction using Hidden Markov Model”, “17th International Conference on Privacy, Security and Trust (PST)”, Fredericton, NB, Canada, 26-28 August 2019, IEEE.

3. Ibrahim Ghafir, Konstantinos G. Kyriakopoulos, Francisco J. Aparicio-Navarro, Sangarapillai Lambotharan, Basil AsSadhan, Hamad BinSalleeh, “A Basic Probability Assignment Methodology for Unsupervised Wireless Intrusion Detection”, IEEE Access, vol. 6, pp.40008–40023, 2018, IEEE.

4. Francisco J. Aparicio-Navarro, Konstantinos G. Kyriakopoulos, Yu Gong, David Parish, Jonathon Chambers, “Using pattern-of-life as contextual information for anomaly-based intrusion detection systems”, IEEE Access, vol. 5, pp.22177–22193, 2017, IEEE.

5. G. Escudero-Andreu, K. G. Kyriakopoulos, F.J. Aparicio-Navarro, D.J. Parish, D. Santoro, M. Vadursi, “A Hybrid Intrusion Detection System for Virtual Jamming Attacks on Wireless Networks”, Measurement, vol. 109, pp.79–87, 2017, Elsevier.