Litcius/Paper detail

A Near Real-Time Scheme for Collecting and Analyzing IoT Malware Artifacts at Scale

Joseph Khoury, Morteza Safaei Pour, Elias Bou‐Harb

2022Proceedings of the 17th International Conference on Availability, Reliability and Security13 citationsDOIOpen Access PDF

Abstract

The chronic proliferation of Internet of Things (IoT) botnet malware activities coupled with an unprecedented rise in security vulnerabilities convene a new world of opportunities for perpetrators and unveil a new set of hurdles in deriving relevant IoT malware intelligence. Such shortfall within the IoT paradigm exacerbates the capabilities for largely identifying the prevailing IoT malware threats, the origin of the IoT attacks, as well as, the security deficit associated with the IoT paradigm. Previous work has vastly studied IoT malware activities in the wild but has not profiled at a large scale malicious activities to collect in near real-time central IoT artifacts much-needed to understand and eventually elevate the security posture of the IoT ecosystem.

Topics & Concepts

MalwareBotnetInternet of ThingsComputer scienceComputer securityScale (ratio)Set (abstract data type)Data scienceThe InternetWorld Wide WebCartographyGeographyProgramming languageNetwork Security and Intrusion DetectionAdvanced Malware Detection TechniquesAnomaly Detection Techniques and Applications