Integrating complex event processing and machine learning: An intelligent architecture for detecting IoT security attacks

作者：

Highlights：

• Combining CEP and ML paradigms permits detecting IoT security attacks in real time.

• A graphical tool facilitates security attack pattern definition and code generation.

• The proposed architecture has been validated in an E-health IoT network scenario.

• ML makes it possible to create accurate pattern dynamically.

摘要

•Combining CEP and ML paradigms permits detecting IoT security attacks in real time.•A graphical tool facilitates security attack pattern definition and code generation.•The proposed architecture has been validated in an E-health IoT network scenario.•ML makes it possible to create accurate pattern dynamically.

论文关键词：Complex event processing,Machine learning,Software architecture,Intelligent decision making,Internet of Things,Security attack

论文评审过程：Received 1 August 2019, Revised 22 December 2019, Accepted 25 January 2020, Available online 30 January 2020, Version of Record 15 February 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113251