Novel Privacy Awareness Task Offloading Approach Based on Privacy Entropy

Mobile edge computing provides the possibility for efficient use of mobile devices, but the disclosure of user privacy is still a huge hidden danger. In order to solve the problem of user locking caused by device usage pattern, a privacy aware computing offloading method based on privacy entropy is proposed. By quantifying privacy as privacy entropy, the problem is modeled as maximizing privacy entropy and minimizing computing offloading resource consumption. The Gaussian-Cauchy operator is proposed to improve the Harris hawks optimization algorithm, to expand the search scope of the algorithm and enhance the ability to jump out of the local optimal. Experimental results show that this method can not only ensure the confusion of user information, but also minimize resource consumption and effectively solve the problem of privacy disclosure of behavior mode.