Fog Computing-Based Autonomic Security Approach to Internet of Things Applications

Abstract

Internet of things (IoT) security continues to be a serious problem as the number of connected devices massively increasing day by day. Autonomic security approaches are required for IoT applications to handle the exponentially growing attacks generated from the increasing number of connected devices. With the limited computational and storage capabilities of IoT devices, it is difficult to implement autonomic capability at each device. Hence, fog computing can be used to provide autonomic security characteristics to IoT applications. The proposed fog computing-based security approach has (1) attack forecasting module based on Gaussian process regression model, (2) attack detection module using cognitive approach and correlation analysis, (3) fuzzy-based incident response module to handle the attacks. The experimental results prove the effectiveness of the proposed approach in terms of detection accuracy and detection time.