In light of the decentralized architecture inherent in cell-free massive multiple-input-multiple-output (MIMO)-enabled mobile edge computing networks, a novel computational task offloading scheme, denoted as Joint Security and Energy-based Load Balancing (JSEON), is proposed. Distinguished from existing studies of only combating passive eavesdropper, two different schemes are integrated to combat the eavesdropper for passive eavesdropping in uplink offloaded task transmission and pilot contamination attack (PCA) in downlink post-data transmission. In an endeavor to refine the portrayal of load-balancing effectiveness within access points equipped with independent edge servers (AP-ES), a novel performance metric termed the energy-based load imbalance degree (e-LoBaR) is introduced. Additionally, this study unveils a pioneering security and energy-based load-balancing (SEAGOING) algorithm, which concurrently optimizes the matching relationships between user equipment (UE) and AP-ESs, the task offloading ratio, and the jamming strategy to verify the effectiveness of proposed JSEON scheme, which can enhance security in a more load-balanced manner. Simulation results show that the proposed algorithm effectively mitigates eavesdropping threats in both uplink and downlink transmissions while improving AP-ES load balancing compared to benchmark schemes.

Physical-layer security (PLS) has become an intriguing technology to address eavesdropping issues in Internet of Things (IoT) systems owing to its low complexity and latency. As wireless communication technology and computing capabilities advance by leaps and bounds, eavesdroppers have enhanced eavesdropping capabilities. They can analyse the environment and move to find better locations for eavesdropping. To mitigate the significant impact of multiple intelligent eavesdroppers extremely close to the device-constrained transmitters in the uplink multiple-input-multiple-output IoT systems, we exploit time-domain artificial noise (AN) in the PLS design and formulate a game problem against the intelligent eavesdroppers. First, we derive the optimal closed-form solution for eavesdroppers and propose a low complexity difference of the convex (LCDC) algorithm to obtain the optimal strategy of the legitimate users and the access point equipped with a zero-forcing receiver. For general linear receivers, we propose a successive convex approximation (SCA) algorithm for the game problem. Simulations are conducted to verify the convergence and effectiveness of our proposed algorithms. The system secrecy performance of the time-domain AN is much better than that of the frequency-domain AN with single-antenna transmitters.

Physical layer security has attracted significant attention in the field of wireless communications. The application of artificial noise can reduce the eavesdropping ability of illegal eavesdroppers without affecting legitimate users. However, most current physical layer security schemes only consider static scenarios and do not account for mobility. Some schemes analyze security performance in mobile scenarios with friendly jammers but do not consider the handoff and cooperation of friendly jammers due to mobility. To address this challenge, we propose a scheme for soft-handoff-based cooperative jamming (CJSH) in mobility scenarios. Initially, we consider a common scenario where a base station communicates with a legitimate mobile user, alongside a mobile passive eavesdropper and multiple friendly jammers emitting artificial noise in the circular area covered by the base station’s signal. Next, We measure the connection outage probability (COP) and secrecy outage probability (SOP) under the influence of multiple friendly jammers in the proposed scheme. We also design two corresponding thresholds for jammers to join and exit. To balance security and energy consumption, we define the Power Average Security Gain (PASG) as a measure of system performance. Finally, we provide numerical simulation results to verify the rationality of the proposed handoff scheme, demonstrating its effective improvement of the system’s security performance and power utilization.

Physical layer security (PLS) has been widely employed in studies of computation offloading under traditional centralized networks. Distinguished from existing studies of only combating passive eavesdropper, we propose an efficient user-centric secure two-stage (UCSTS) access point (AP) selection method to combat simultaneously active and passive eaves-dropping, which is exploiting the distributed feature of cell-free massive multiple-input-multiple-output (MIMO) scenarios. Furthermore, we propose a novel secure computation task offloading (SCTO) model to guarantee the security of both uplink and downlink transmission. Aiming at reducing total energy consumption with high security, a minimum energy consumption optimization problem is solved by alternative optimization (AO) algorithm. Simulation results show that the proposed model can well combat Eve while reducing the total energy consumption, and the security of the proposed selection method is better than the AN-based scheme.