Securing OFDMA-Based Cooperative Vehicular IoT Systems From Untrusted Platooning Networks

As the Internet of Things (IoT) becomes more integrated with everyday life, Vehicle-to-Vehicle (V2V) communication is becoming increasingly crucial for intelligent transportation systems (ITSs). However, ensuring secure V2V communication is crucial to fully realize the potential and usefulness of IoT-enabled ITS. Therefore, this article proposes a novel joint optimization framework for securing orthogonal frequency division multiple access (OFDMA)-based V2V communications in untrusted vehicle platooning networks. To address this timely nonconvex optimization problem in cooperative vehicular IoT systems, we divide it into two subproblems: 1) power control and 2) subcarrier allocation. For each subproblem, we propose dual solution strategies, prioritizing low-computational cost and emphasizing high accuracy, albeit at a higher computational expense. The low-complexity approach for subcarrier allocation utilizes channel power gains within platoons. On the other hand, the high-accuracy strategy involves a branch-and-bound (BNB) algorithm to obtain the near-global optimal solution for this nondeterministic polynomial-time (NP)-hard problem. Similarly, we introduce a low-complexity strategy based on a high-signal-to-interference-plus-noise ratio (SINR) transformation, enabling closed-form solutions through fractional programming (FP) for optimal power control, which is ideal for automated vehicles. The alternative approach adopts a direct FP transformation for precise power distribution, attaining the near-global optimum numerically but with increased computational demands. Numerical simulations are conducted to validate our theoretical assertions and to offer nontrivial vital design insights. Our policy of jointly allocating BNB subcarriers and directly controlling FP power significantly increases the sum secrecy rate by more than 58% compared to conventional schemes in typical intelligent vehicle settings for IoT environments.