@inproceedings{siniosoglou2021covert,

title = {Covert Distributed Training of Deep Federated Industrial Honeypots},

author = {Ilias Siniosoglou and Vasileios Argyriou and Thomas Lagkas and Apostolos Tsiakalos and Antonios Sarigiannidis and Panagiotis Sarigiannidis},

url = {https://ieeexplore.ieee.org/abstract/document/9682162},

doi = {10.1109/GCWkshps52748.2021.9682162},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {2021 IEEE Globecom Workshops (GC Wkshps)},

pages = {1--6},

organization = {IEEE},

abstract = {Since the introduction of automation technologies in the Industrial field and its subsequent scaling to horizontal and vertical extents, the need for interconnected industrial systems, supporting smart interoperability is ever higher. Due to this scaling, new and critical vulnerabilities have been created, notably in legacy systems, leaving Industrial infrastructures prone to cyber attacks, that can some times have catastrophic results. To tackle the need for extended security measures, this paper presents a Federated Industrial Honeypot that takes advantage of decentralized private Deep Training to produce models that accumulate and simulate real industrial devices. To enhance their camouflage, SCENT, a new custom and covert protocol is proposed, to fully immerse the Federated Honeypot to its industrial role, that handles the communication between the server and honeypot during the training, to hide any clues of operation of the honeypot other that its supposed objective to the eye of the attacker.},

keywords = {Data Generation, Deep Learning, Honeypots, Industrial Control System, SCADA},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{inproceedingsb,

title = {Secure and Private Smart Grid: The SPEAR Architecture},

author = {Panagiotis Radoglou Grammatikis and Panagiotis Sarigiannidis and Eider Iturbe and Erkuden Rios and Antonios Sarigiannidis and Odysseas Nikolis and Dimosthenis Ioannidis and Vasileios Machamint and Michalis Tzifas and Alkiviadis Giannakoulias and Michail Angelopoulos and Anastasios Papadopoulos and Francisco Ramos},

url = {https://www.researchgate.net/publication/343621502_Secure_and_Private_Smart_Grid_The_SPEAR_Architecture},

doi = {10.1109/NetSoft48620.2020.9165420},

year  = {2020},

date = {2020-01-01},

booktitle = {2020 6th IEEE International Conference on Network Softwarization (NetSoft)},

pages = {450-456},

abstract = {Information and Communication Technology (ICT) is an integral part of Critical Infrastructures (CIs), bringing both significant pros and cons. Focusing our attention on the energy sector, ICT converts the conventional electrical grid into a new paradigm called Smart Grid (SG), providing crucial benefits such as pervasive control, better utilisation of the existing resources, self-healing, etc. However, in parallel, ICT increases the attack surface of this domain, generating new potential cyberthreats. In this paper, we present the Secure and PrivatE smArt gRid (SPEAR) architecture which constitutes an overall solution aiming at protecting SG, by enhancing situational awareness, detecting timely cyberattacks, collecting appropriate forensic evidence and providing an anonymous cybersecurity information-sharing mechanism. Operational characteristics and technical specifications details are analysed for each component, while also the communication interfaces among them are described in detail.},

keywords = {Anomaly Detection, Anonymity, Cybersecurity, Forensics, Honeypots, Intrusion detection, Privacy, Smart Grid},

pubstate = {published},

tppubtype = {inproceedings}

}