Department of Computer Science
University of Cyprus
1 University Avenue
Office: FST01 (ΘΕΕ01) B114
Since November 2017, I am also affiliated with the RISE Research Center on Interactive Media, Smart Systems and Emerging Technologies, where I lead the Smart Networked Systems Multidisciplinary Research Group
|20 July 2020||NetRL welcomes Mr. Wagar Aziz in its ranks. Mr. Aziz completed his MSc at NUST Pakistan is a PhD Candidate in Computer Science and holds a PhD Fellowship from the RISE Research Center.|
|15 July 2020|| Congratulations to all of the recent graduates Paris Konstantinides, Christos Andreou, Christoforos Pantazis, Stefanos Kyriakou and Andreas Charalambous for the completion of their studies. We wish them all the best in their future endeavors.
Special reference needs to be made to Andreas Charalambous and Paris Konstantinides who have also been recognized as being among the best in their class (Masters and Bachelors) respectively. Keep up the good work guys!
|7 January 2020||NetRL welcomes Mr. Abdullah bin Masood in its ranks. Mr. Masood completed his MSc at NUST Pakistan and is currently a PhD Candidate in Computer Science and holds a PhD Fellowship from the RISE Research Center.|
|13 December 2019||Congratulations to Dr. Christiana Ioannou for receiving a Research Grant for two years under the University of Cyprus' ONISILOS Post-Doctoral Funding Grants for her project "IDS4IoT - Computational and Artificial Intelligence Solutions for Intrusion Detection in Internet of Things!"|
|10 December 2019||Check out this video desribing our work on IDS for IoT. Prepared by the Center for Entrepreneurship (C4E) of UCY for their "Shaping the future: Featuring selected UCY Innovations 2019" series.|
My research is mainly systems and protocols oriented. I design and deploy network protocols and systems that make the Internet work better. Most of my work is used in a representative environment (test-bed or simulation) and tested with real-life values, parameters and settings. I use empirical network measurement and machine learning to understand and improve network performance, reliability, and security.
Social and Context-aware Content Distribution in 5G Networks (current): Exploit 5G dense networks and trends in using the network edge for processing and storage. Develop and integrate a framework for QoE-based dynamic adaptation of network and content. This includes the fusion of concepts from social network cascades and content dissemination, the increasing use of small high-speed cells for network communication, and the ability to group and predict users’ needs.
As D2D communications become more prevalent in 5G networks, both with the use of in-bad and out-band communication modes, we are considering the use of AI-based techniques to address the major challenges of Interference management, Cell densification and offloading, QoS/Path Selection (Routing), Handovers of D2D devices, Device Discovery and Power management. The bet is essentially to create a solution that is truly distributed and dynamic. After investigating all the D2D requirements and available solutions, we believe that using BDI (Belief, Desire, intention) agents can help at the implementation of D2D as a distributed, dynamic and autonomous control system.
protocols and algorithms for the secure and reliable operation of IoT networks. Significant opportunities exist in clearly defining the scope of security solutions and IoT-specific topologies considered. Extensions to the BLR-based anomaly detection will be defined, to cover different attacks, different topologies and different agent locations. New IDS techniques based on Computational Intelligence (Fuzzy logic, Artificial Immune System) and Machine Learning (SVM, K-NN, Q-learning) will be developed.
The introduction of robotics and UAVs in WSNs and IoT networks makes the work on mobile nodes relevant and timely. Cross-layer techniques for fault identification (energy depletion, congestion, hardware failure, malicious operation) will be developed. These events will trigger different solutions of mobile node utilization for recovery.