Detecting security attacks in cyber-physical systems: a comparison of Mule and WSO2 intelligent IoT architectures.

ABSTRACT: The Internet of Things (IoT) paradigm keeps growing, and many different IoT devices, such as smartphones and smart appliances, are extensively used in smart industries and smart cities. The benefits of this paradigm are obvious, but these IoT environments have brought with them new challenges, such as detecting and combating cybersecurity attacks against cyber-physical systems. This paper addresses the real-time detection of security attacks in these IoT systems through the combined used of Machine Learning (ML) techniques and Complex Event Processing (CEP). In this regard, in the past we proposed an intelligent architecture that integrates ML with CEP, and which permits the definition of event patterns for the real-time detection of not only specific IoT security attacks, but also novel a

SUBMITTER: Roldan-Gomez J 

PROVIDER: S-EPMC8627230 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature