Publications

@article{myridakis2021power,

title = {A Power Dissipation Monitoring Circuit for Intrusion Detection and Botnet Prevention on IoT Devices},

author = {Dimitrios Myridakis and Paul Myridakis and Athanasios Kakarountas},

year  = {2021},

date = {2021-01-01},

journal = {Computation},

volume = {9},

number = {2},

pages = {19},

publisher = {Multidisciplinary Digital Publishing Institute},

keywords = {Hardware, IoT, security, Smart Devices},

pubstate = {published},

tppubtype = {article}

}

@article{Giannoukos_Kakarountas_Chioktour_2020,

title = {Interaction between two cells based on a recurrent neural network using the impedance concept},

author = {Georgios Giannoukos and Athanasios Kakarountas and Vasileios Chioktour},

doi = {10.3233/JCM-204367},

issn = {14727978, 18758983},

year  = {2020},

date = {2020-07-01},

journal = {Journal of Computational Methods in Sciences and Engineering},

pages = {1–7},

keywords = {Hardware, Neural Networks},

pubstate = {published},

tppubtype = {article}

}

@article{myridakis2020enhancing,

title = {Enhancing Security on IoT Devices via Machine Learning on Conditional Power Dissipation},

author = {Dimitrios Myridakis and Stefanos Papafotikas and Konstantinos Kalovrektis and Athanasios Kakarountas},

year  = {2020},

date = {2020-01-01},

journal = {Electronics},

volume = {9},

number = {11},

pages = {1799},

publisher = {Multidisciplinary Digital Publishing Institute},

keywords = {Hardware, IoT, Machine Learning, security, Smart Devices},

pubstate = {published},

tppubtype = {article}

}

@article{fi12030048,

title = {Smart Devices Security Enhancement via Power Supply Monitoring},

author = {Dimitrios Myridakis and Georgios Spathoulas and Athanasios Kakarountas and Dimitrios Schinianakis},

url = {https://www.mdpi.com/1999-5903/12/3/48},

doi = {10.3390/fi12030048},

issn = {1999-5903},

year  = {2020},

date = {2020-01-01},

journal = {Future Internet},

volume = {12},

number = {3},

abstract = {The continuous growth of the number of Internet of Things (IoT) devices and their inclusion to public and private infrastructures has introduced new applciations to the market and our day-to-day life. At the same time, these devices create a potential threat to personal and public security. This may be easily understood either due to the sensitivity of the collected data, or by our dependability to the devices' operation. Considering that most IoT devices are of low cost and are used for various tasks, such as monitoring people or controlling indoor environmental conditions, the security factor should be enhanced. This paper presents the exploitation of side-channel attack technique for protecting low-cost smart devices in an intuitive way. The work aims to extend the dataset provided to an Intrusion Detection Systems (IDS) in order to achieve a higher accuracy in anomaly detection. Thus, along with typical data provided to an IDS, such as network traffic, transmitted packets, CPU usage, etc., it is proposed to include information regarding the device’s physical state and behaviour such as its power consumption, the supply current, the emitted heat, etc. Awareness of the typical operation of a smart device in terms of operation and functionality may prove valuable, since any deviation may warn of an operational or functional anomaly. In this paper, the deviation (either increase or decrease) of the supply current is exploited for this reason. This work aimed to affect the intrusion detection process of IoT and proposes for consideration new inputs of interest with a collateral interest of study. In parallel, malfunction of the device is also detected, extending this work’s application to issues of reliability and maintainability. The results present 100% attack detection and this is the first time that a low-cost security solution suitable for every type of target devices is presented.},

keywords = {Anomaly Detection, Hardware, IoT, security, smart device; current monitoring; physical characteristics},

pubstate = {published},

tppubtype = {article}

}