@inproceedings{10.1145/3407023.3409314,

title = {DIDEROT: An Intrusion Detection and Prevention System for DNP3-Based SCADA Systems},

author = {Panagiotis Radoglou-Grammatikis and Panagiotis Sarigiannidis and George Efstathopoulos and Paris-Alexandros Karypidis and Antonios Sarigiannidis},

url = {https://doi.org/10.1145/3407023.3409314},

doi = {10.1145/3407023.3409314},

isbn = {9781450388337},

year  = {2020},

date = {2020-01-01},

booktitle = {Proceedings of the 15th International Conference on Availability, Reliability and Security},

publisher = {Association for Computing Machinery},

address = {Virtual Event, Ireland},

series = {ARES '20},

abstract = {In this paper, an Intrusion Detection and Prevention System (IDPS) for the Distributed Network Protocol 3 (DNP3) Supervisory Control and Data Acquisition (SCADA) systems is presented. The proposed IDPS is called DIDEROT (Dnp3 Intrusion DetEction pReventiOn sysTem) and relies on both supervised Machine Learning (ML) and unsupervised/outlier ML detection models capable of discriminating whether a DNP3 network flow is related to a particular DNP3 cyberattack or anomaly. First, the supervised ML detection model is applied, trying to identify whether a DNP3 network flow is related to a specific DNP3 cyberattack. If the corresponding network flow is detected as normal, then the unsupervised/outlier ML anomaly detection model is activated, seeking to recognise the presence of a possible anomaly. Based on the DIDEROT detection results, the Software Defined Networking (SDN) technology is adopted in order to mitigate timely the corresponding DNP3 cyberattacks and anomalies. The performance of DIDEROT is demonstrated using real data originating from a substation environment.},

keywords = {Anomaly Detection, Autonencoder, Intrusion detection, Machine Learning, SCADA, SDN, Smart Grid},

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}

}