Journal ArticleOpen Access
Dependable Intrusion Detection System for IoT: A Deep Transfer Learning Based Approach
Authors
Author Affiliations
Mawlana Bhashani Science and Technology University, Deakin University, RMIT University, University of Saskatchewan, ...
Published InIEEE Transactions on Industrial Informatics
Year2022
Citations162
Abstract
Security concerns for Internet of Things (IoT) applications have been alarming because of their widespread use in different enterprise systems. The potential threats to these applications are constantly emerging and changing, and, therefore, sophisticated and dependable defense solutions are necessary against such threats. With the rapid development of IoT networks and evolving threat types, the traditional machine learning based IDS must update to cope with the security requirements of the current sustainable IoT environment. In recent years, deep learning and deep transfer learning have progressed and experienced great success in different fields and have emerged as a potential solution for dependable network intrusion detection. However, new and emerging challenges have arisen related to the accuracy, efficiency, scalability, and dependability of…
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