Satisfaction-Maximized Secure Computation Offloading in Multi-Eavesdropper MEC Networks

In this paper, we consider a mobile edge computing (MEC)-based secure computation offloading system, and design practical multi-eavesdropper model including two specific scenarios of non-colluding colluding eavesdropping. Furthermore, requirement satisfaction by exploring variations in user request patterns for security provisioning, delay reduction energy saving. Based on these, propose satisfaction-maximized (SMax-SCO) scheme, then formulate an optimization problem aiming at maximizing users’ satisfactions subject to secrecy rate, tolerable delay, task workload maximum power constraints. Since the is nonconvex, present efficient successive convex approximation (SCA)-based algorithm obtain suboptimal solutions. We demonstrate that proposed SMax-SCO scheme achieves significant improvement performance compared with existing schemes. Moreover, conclude can resist eavesdropping attacks multiple eavesdroppers even eavesdroppers.