The security of confidential information associated with devices in the industrial Internet of Things (IIoT) network is a serious concern. This article focuses on achieving a nonorthogonal multiple access (NOMA)-enabled secure IIoT network in the presence of untrusted devices by jointly optimizing the resources, such as decoding order and power allocated to devices. Assuming that the devices are resource-constrained for performing perfect successive interference cancellation (SIC), we characterize the residual interference at receivers with the linear model. Firstly, considering all possible decoding orders in an untrusted scenario, we obtain secure decoding orders that are feasible to obtain a positive secrecy rate for each device. Then, under the secrecy fairness criterion, we formulate a joint optimization problem of maximizing the minimum secrecy rate among devices. Since the formulated problem is non-convex and combinatorial, we first obtain the optimal secure decoding order and then solve it for power allocation by analyzing Karush-Kuhn-Tucker points. Thus, we provide the closed-form global-optimal solution of the formulated optimization problem. Numerical results validate the analytical claims and demonstrate an interesting observation that the conventional decoding order and assigning more power allocation to the weak device, as presumed in many works on NOMA, is not an optimal strategy from the secrecy fairness viewpoint. Also, the average percentage gain of about 22.75%, 50.58%, 94.59%, and 98.16%, respectively, is achieved by jointly optimized solution over benchmarks ODEP (optimal decoding order, equal power allocation), ODFP (optimal decoding order, fixed power allocation), FDEP (fixed decoding order, equal power allocation), and FDFP (fixed decoding order, fixed power allocation).

翻译：工业物联网（IIoT）网络中与设备相关的机密信息安全是一个严峻挑战。本文聚焦于通过联合优化资源（如设备解码顺序与功率分配），在存在不可信设备的情况下实现基于非正交多址接入（NOMA）的安全IIoT网络。假设设备在执行完美串行干扰消除（SIC）时存在资源限制，我们采用线性模型刻画接收端残留干扰。首先，考虑不可信场景下所有可能的解码顺序，确定能使每台设备获得正保密率的可行安全解码顺序。随后，在保密公平性准则下，构建最大化设备最小保密率的联合优化问题。由于该问题具有非凸性与组合性，我们首先求解最优安全解码顺序，进而通过分析Karush-Kuhn-Tucker条件得到功率分配方案，最终给出所构建优化问题的闭式全局最优解。数值结果验证了理论分析的正确性，并揭示了一个有趣现象：与多篇NOMA文献中假设的"传统解码顺序及向弱设备分配更多功率"策略不同，在保密公平性视角下该策略并非最优。此外，相比于基准方案ODEP（最优解码顺序等功率分配）、ODFP（最优解码顺序固定功率分配）、FDEP（固定解码顺序等功率分配）和FDFP（固定解码顺序固定功率分配），联合优化方案分别实现了约22.75%、50.58%、94.59%和98.16%的平均性能增益。