Securing an Internet of Things from Distributed Denial of Service and Mirai Botnet Attacks Using a Novel Hybrid Detection and Mitigation Mechanism

Abstract

Internet of Things (IoT) has become more familiar in all applications and industrial fields such as medical, military, transportation, etc. It has some limitations because of the attack model in the transmission or communication channel. Moreover, one of the deadliest attacks is known as a Distributed Denial of Service Attack (DDoS). The Presence of DDoS in network layer cause huge damage in data transmission channel that ends in data loss or collapse. To address this issue the current research focused on an innovative detection and mitigation of Mirai and DDoS attack in IoT environment. Initially, number of IoT devices is arranged with the help of a novel Hybrid Strawberry and African Buffalo Optimization (HSBABO). Consequently, the types of DDoS attacks are launched in the developed IoT network. Moreover, the presence of strawberry and African Buffalo fitness is utilized to detect and specify the attack types. Subsequently a novel MCELIECE encryption with Cloud Shield scheme is developed to prevent the low and high rate DDoS attack in the Internet of Things. Finally, the proposed model attained 94% of attack detection accuracy, 3% of false negative rate and 5.5% of false positive rate.