Advancing IoT Security with FLAME: A Hybrid Approach Combining Fuzzy Logic and Artificial Lizard Search Optimization

Abstract

The increasing usage of Internet of Things (IoT) devices has created a need for secure and efficient solutions to protect sensitive data from unauthorized access. However, the complicated and massive structure of IoT systems poses various security risks and challenges, especially in dynamic scenarios with high signaling overhead caused by subscriber mobility. So, in this paper, a Fuzzy-based Lightweight Authentication and Management of Encryption approach called ‘FLAME’ is proposed to solve the decentralized lightweight group key management problem by measuring the degree of security using fuzzy logic (FL) based on various factors like device and user behavior, network conditions, and resource availability. For effective key-based authentication, adopted an Artificial Lizard Search Optimization (ALSO) based RSA (Rivest, Shamir, Adleman) algorithm that generates private and public keys based on security evaluation outcome. The publishers and subscribers obtain encryption keys from the group key manager based on their security level, and dissemination is optimized by the ALSO algorithm. By leveraging the FL and ALSO based RSA algorithm, the system offers secure communication with limited utilization and protects confidential data in IoT environments. According to the analysis, results signify that the FLAME approach has a faster key generation, dissemination, and revocation time compared to existing approaches, along with reduced overhead during key management operations, and increased attack detection capacity of 98.7%.