In many enterprises and the private sector, the Internet of Things (IoT) has spread globally. The... more In many enterprises and the private sector, the Internet of Things (IoT) has spread globally. The growing number of different devices connected to the IoT and their various protocols have contributed to the increasing number of attacks, such as denial-of-service (DoS) and remote-to-local (R2L) ones. There are several approaches and techniques that can be used to construct attack detection models, such as machine learning, data mining, and statistical analysis. Nowadays, this technique is commonly used because it can provide precise analysis and results. Therefore, we decided to study the previous literature on the detection of IoT attacks and machine learning in order to understand the process of creating detection models. We also evaluated various datasets used for the models, IoT attack types, independent variables used for the models, evaluation metrics for assessment of models, and monitoring infrastructure using DevSecOps pipelines. We found 49 primary studies, and the detectio...
Citation: Bahaa, A.; Abdelaziz, A.; Sayed, A.; Elfangary, L.; Fahmy, H. Monitoring Real Time Secu... more Citation: Bahaa, A.; Abdelaziz, A.; Sayed, A.; Elfangary, L.; Fahmy, H. Monitoring Real Time Security Attacks for IoT Systems Using DevSecOps: A Systematic Literature Review. Information 2021, 12, 154.
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