TRUFOG: A Dynamic Trust and Energy‐Driven Security Method for Efficient Communication in Fog‐Assisted Internet of Things

ABSTRACT Internet of Things (IoT) has been diversified smart networks of connected things consisting of users, smart devices, and interwoven equipment that facilitate communication using wired and wireless mechanisms. The devices in IoT networks transfer data among each other to provide amenities to mankind. These networks have been in hot demand and use in the recent past and have scaled up to a large extent. Fog‐based IoTs have been maneuvered as a furtherance to cloud computing by accomplishing the processing of services faster and closer to end users. However, the rapid increase in the demand for services has raised various concerns like security and privacy in fog‐based IoTs, and therefore, the identification and removal of malicious devices have become a prominent challenge. To conquer this, a secure method called TRUFOG is presented in this article. TRUFOG is a task‐based dynamic trust mechanism. The proposed approach utilizes the following three major parameters: task success, task pending, and task failure ratio. Along with this recommendation credibility is used to estimate the trust of the fog node and average energy consumption is also tested. The security resistance of the TRUFOG mechanism is tested against black hole, gray hole, and energy consumption attacks. The proposed mechanism is extensively evaluated and compared with existing methods like TCF, TBMSC, and TRDTM in terms of accuracy, delivery ratio, energy consumption, and other metrics. The results have proven that TRUFOG has effectively recognized the malicious node in the network with a detection rate of 95.2%. The packet delivery ratio for TRUFOG under attack was found to be 4.5% better than TCF, 6.25% better than TBMSC, and 4.66% better than TRDTM. Furthermore, the average energy consumption of the TRUFOG method was found to be 13.6% lesser than TCF, 30.7% lesser than TBMSC, and 49.9% lesser than the TRDTM model.