Internet of things (IoT) is considered one of the most important technologies, due to its impact on both personal and enterprise domains. However, similarly to the traditional Internet, IoT is facing many security issues, part of which caused by the presence of an astounding number of vulnerable devices. Researchers have been struggling to improve the security of IoT in many different ways, one of which concerning the employment of intrusion detection systems (IDS) in IoT environments. This paper evaluates the effectiveness of an intrusion detection technique, named PCkAD, in IoT environments. The technique exploits the spatial distribution information of payload data to identify malicious contents. PCkAD was evaluated on two datasets, containing traffic related to sensors and actuators. The experimental results show that PCkAD can be effectively employed to increase the security of IoT environments.

Effectiveness of Content Spatial Distribution Analysis in Securing IoT Environments

Angiulli, Fabrizio;Argento, Luciano;Furfaro, Angelo
2018

Abstract

Internet of things (IoT) is considered one of the most important technologies, due to its impact on both personal and enterprise domains. However, similarly to the traditional Internet, IoT is facing many security issues, part of which caused by the presence of an astounding number of vulnerable devices. Researchers have been struggling to improve the security of IoT in many different ways, one of which concerning the employment of intrusion detection systems (IDS) in IoT environments. This paper evaluates the effectiveness of an intrusion detection technique, named PCkAD, in IoT environments. The technique exploits the spatial distribution information of payload data to identify malicious contents. PCkAD was evaluated on two datasets, containing traffic related to sensors and actuators. The experimental results show that PCkAD can be effectively employed to increase the security of IoT environments.
9781538675038
Cyber threats; Internet of Things; Intrusion Detection Systems; Performance Evaluation; Computer Networks and Communications; Computer Science Applications1707 Computer Vision and Pattern Recognition; Hardware and Architecture; Safety, Risk, Reliability and Quality
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/288177
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