Abnormal Detection of Wireless Power Terminals in Untrusted Environment Based on Double Hidden Markov Model

The wireless power terminals are deployed in harsh public places and lack strict control, facing security problems. Thus, they are faced with security problems such as illegal and counterfeit terminal access, unlawful control of connected terminals, etc. The intrusion detection system based on machi...

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Autores principales:	Kehe Wu, Jiawei Li, Bo Zhang
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	HMM abnormal detection power IoT device Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/c055737541be4aac87f532bb871f9530
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spelling	oai:doaj.org-article:c055737541be4aac87f532bb871f95302021-11-19T00:06:13ZAbnormal Detection of Wireless Power Terminals in Untrusted Environment Based on Double Hidden Markov Model2169-353610.1109/ACCESS.2020.3040856https://doaj.org/article/c055737541be4aac87f532bb871f95302021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9272342/https://doaj.org/toc/2169-3536The wireless power terminals are deployed in harsh public places and lack strict control, facing security problems. Thus, they are faced with security problems such as illegal and counterfeit terminal access, unlawful control of connected terminals, etc. The intrusion detection system based on machine learning and artificial intelligence significantly improve the terminal side’s abnormal detection capacity. In this article, we aim at identifying the abnormal behavior of wireless power terminals based on a double Hidden Markov Model (HMM), which solves the computational complexity problem caused by high dimensions in intrusion detection systems using a single HMM. The lower-layer HMM is used to identify the discrete single network abnormal behavior. Simultaneously, the upper-layer can obtain more extended period attack behavior in multiple independent abnormal events identified by the low-level. The experiment results indicate that the intrusion detection system using proposed double HMM can effectively detect the terminal’s abnormal behavior and identify the network attack behavior for an extended period.Kehe WuJiawei LiBo ZhangIEEEarticleHMMabnormal detectionpower IoT deviceElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 18682-18691 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	HMM abnormal detection power IoT device Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	HMM abnormal detection power IoT device Electrical engineering. Electronics. Nuclear engineering TK1-9971 Kehe Wu Jiawei Li Bo Zhang Abnormal Detection of Wireless Power Terminals in Untrusted Environment Based on Double Hidden Markov Model
description	The wireless power terminals are deployed in harsh public places and lack strict control, facing security problems. Thus, they are faced with security problems such as illegal and counterfeit terminal access, unlawful control of connected terminals, etc. The intrusion detection system based on machine learning and artificial intelligence significantly improve the terminal side’s abnormal detection capacity. In this article, we aim at identifying the abnormal behavior of wireless power terminals based on a double Hidden Markov Model (HMM), which solves the computational complexity problem caused by high dimensions in intrusion detection systems using a single HMM. The lower-layer HMM is used to identify the discrete single network abnormal behavior. Simultaneously, the upper-layer can obtain more extended period attack behavior in multiple independent abnormal events identified by the low-level. The experiment results indicate that the intrusion detection system using proposed double HMM can effectively detect the terminal’s abnormal behavior and identify the network attack behavior for an extended period.
format	article
author	Kehe Wu Jiawei Li Bo Zhang
author_facet	Kehe Wu Jiawei Li Bo Zhang
author_sort	Kehe Wu
title	Abnormal Detection of Wireless Power Terminals in Untrusted Environment Based on Double Hidden Markov Model
title_short	Abnormal Detection of Wireless Power Terminals in Untrusted Environment Based on Double Hidden Markov Model
title_full	Abnormal Detection of Wireless Power Terminals in Untrusted Environment Based on Double Hidden Markov Model
title_fullStr	Abnormal Detection of Wireless Power Terminals in Untrusted Environment Based on Double Hidden Markov Model
title_full_unstemmed	Abnormal Detection of Wireless Power Terminals in Untrusted Environment Based on Double Hidden Markov Model
title_sort	abnormal detection of wireless power terminals in untrusted environment based on double hidden markov model
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/c055737541be4aac87f532bb871f9530
work_keys_str_mv	AT kehewu abnormaldetectionofwirelesspowerterminalsinuntrustedenvironmentbasedondoublehiddenmarkovmodel AT jiaweili abnormaldetectionofwirelesspowerterminalsinuntrustedenvironmentbasedondoublehiddenmarkovmodel AT bozhang abnormaldetectionofwirelesspowerterminalsinuntrustedenvironmentbasedondoublehiddenmarkovmodel
_version_	1718420632909119488

Abnormal Detection of Wireless Power Terminals in Untrusted Environment Based on Double Hidden Markov Model

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