An Edge Based Attack Detection Model (EBAD) for Increasing the Trustworthiness in IoT Enabled Smart City Environment

Several massive real-time services could be offered to the residents of smart cities by incorporation collaborative applications. All such applications require latency-aware network for accomplishing various needs city environment. It requires technological enhancements existing mechanisms serve better in environments. Such prevailing approaches also opened a wide range chances intruders. Among infringes, identity-based attack is most powerful attack, which may directly affect credibility legitimate components. attackers aim steal identity other entities. Thus, trust-based cannot withstand attacks. The proposed Edge-based approach, EBAD has been designed environments, as robust prevention mechanism theft and misuse. efficient enough identify Sybil attacker nodes early identification will nullify probability performing over Cooperative blackmailing (SA-CBA). uses an accusation analysis approach assess malicious behavior major part required computations placed at edge node reducing computational overload end devices. Finally, efficiency examined under