Papafotikas, Stefanos; Kakarountas, Athanasios A Machine-Learning Clustering Approach for Intrusion Detection to IoT Devices Proceedings Article In: 2019 4th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), pp. 1–6, IEEE 2019. BibTeX | Tags: Anomaly Detection, Intrusion Detection, IoT, Machine Learning, security, Smart Devices Myridakis, Dimitrios; Spathoulas, Georgios; Kakarountas, Athanasios Supply current monitoring for anomaly detection on iot devices Proceedings Article In: Proceedings of the 21st Pan-Hellenic Conference on Informatics, pp. 1–2, 2017. BibTeX | Tags: Anomaly Detection, Intrusion Detection, IoT, security "Dimitrios, Myridakis; Georgios, Spathoulas; Athanasios, Kakarountas; Schoinianakis, Dimitrios; Lueken, Joachim" "Mimicking Biometrics on Smart Devices and Its Application in IoT Security for Health Systems" Book Chapter In: "Gupta, Nishu; Paiva, Sara" (Ed.): "IoT and ICT for Healthcare Applications", pp. "175–189", "Springer International Publishing", "Cham", 0000, ISBN: "978-3-030-42934-8". Abstract | Links | BibTeX | Tags: Anomaly Detection, biometrics, Hardware Security, Health Applications, Intrusion Detection, IoT, Smart Device
2019
@inproceedings{papafotikas2019machine,
title = {A Machine-Learning Clustering Approach for Intrusion Detection to IoT Devices},
author = {Stefanos Papafotikas and Athanasios Kakarountas},
year = {2019},
date = {2019-01-01},
booktitle = {2019 4th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)},
pages = {1--6},
organization = {IEEE},
keywords = {Anomaly Detection, Intrusion Detection, IoT, Machine Learning, security, Smart Devices},
pubstate = {published},
tppubtype = {inproceedings}
}
2017
@inproceedings{myridakis2017supplyb,
title = {Supply current monitoring for anomaly detection on iot devices},
author = {Dimitrios Myridakis and Georgios Spathoulas and Athanasios Kakarountas},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings of the 21st Pan-Hellenic Conference on Informatics},
pages = {1--2},
keywords = {Anomaly Detection, Intrusion Detection, IoT, security},
pubstate = {published},
tppubtype = {inproceedings}
}
0000
@inbook{Dimitrios2020b,
title = {"Mimicking Biometrics on Smart Devices and Its Application in IoT Security for Health Systems"},
author = {Myridakis "Dimitrios and Spathoulas Georgios and Kakarountas Athanasios and Dimitrios Schoinianakis and Joachim" Lueken},
editor = {Nishu "Gupta and Sara" Paiva},
url = {"https://doi.org/10.1007/978-3-030-42934-8_10"},
doi = {"10.1007/978-3-030-42934-8_10"},
isbn = {"978-3-030-42934-8"},
booktitle = {"IoT and ICT for Healthcare Applications"},
pages = {"175--189"},
publisher = {"Springer International Publishing"},
address = {"Cham"},
abstract = {"The Internet of Things (IoT) encompasses cyber and physical objects in multidisciplinary applications such as home automation, industrial process, environmental monitoring, and human health, to mention a few. Especially the latter systems have seen rapid growth in hospitals and health centers over the last decade. The wireless healthcare monitoring devices of various technologies are presenting global interest, since they offer valuable health metrics to users and physicians and also they are easy to use on a day-to-day basis. This chapter refers to security issues associated to IoT devices in general and how a technique of bio-mimicking on smart devices may reveal potential attacks or malfunctions. The case of systems for healthcare and health monitoring is considered, in order to highlight the techniques' benefits in this topic. The approach is bio-inspired by human biometrics and adopted to fit the cyber world, referring to a device's state; specifically the paradigm of side channel attack is exploited. This introduces the notion that to secure devices for healthcare, the designer has to consider the ``health status'' of the device itself. Taking into consideration that these devices are limited by their functionality and functional characteristics, it is expected that any deviation from the expected normal operation would result in a similar deviation in any operational parameter."},
keywords = {Anomaly Detection, biometrics, Hardware Security, Health Applications, Intrusion Detection, IoT, Smart Device},
pubstate = {published},
tppubtype = {inbook}
}
A Machine-Learning Clustering Approach for Intrusion Detection to IoT Devices Proceedings Article In: 2019 4th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), pp. 1–6, IEEE 2019. Supply current monitoring for anomaly detection on iot devices Proceedings Article In: Proceedings of the 21st Pan-Hellenic Conference on Informatics, pp. 1–2, 2017. "Mimicking Biometrics on Smart Devices and Its Application in IoT Security for Health Systems" Book Chapter In: "Gupta, Nishu; Paiva, Sara" (Ed.): "IoT and ICT for Healthcare Applications", pp. "175–189", "Springer International Publishing", "Cham", 0000, ISBN: "978-3-030-42934-8".
2019
2017
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