Privacy Protection Offloading Algorithm Based on K-anonymity in Mobile Edge Computing Networks

With the development of mobile edge computing (MEC) and wireless power transfer (WPT), more and more computing tasks are offloaded to the MEC server for processing. The terminal equipment is powered by WPT technology to alleviate the limited computing power of the terminal equipment and high energy consumption of the terminal equipment. However, since the offloaded tasks and data often carry information such as users’ personal usage habits, tasks are offloaded to the MEC server for processing results in new privacy leakage issues. A privacy-protection computation offloading method based on k-anonymity is proposed in this paper. Firstly, the privacy of the computing task is defined, and then a k-anonymity framework that can reduce the amount of privacy accumulated by users on the MEC server is designed. Secondly, the privacy-protection offloading algorithm is proposed by considering the optimization of the privacy constraints and anonymous loss jointly. Finally, simulation results validate that the proposed offloading method can keep the cumulative privacy of user below the threshold and reduce users’ calculation delay at the same time.