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Fair Subcarrier Allocation for Securing OFDMA in IoT Against Full-Duplex Hybrid Attacker
IEEE Transactions on Information Forensics and Security ( IF 6.8 ) Pub Date : 2021-03-22 , DOI: 10.1109/tifs.2021.3067157
Bhawna Ahuja 1 , Deepak Mishra 2 , Ranjan Bose 1
Affiliation  

Secure communication with low computational resources is a critical issue in the Internet-of-Things (IoT) implementations. It is more challenging in the presence of hybrid adversary enabled with full-duplex (FD) capability to perform eavesdropping and jamming simultaneously. In this work we aim to address this issue through optimal subcarrier allocation towards combating the FD hybrid attacker. We begin with secrecy performance analysis in a multi-user IoT system considering statistical channel state information only of all attacker links. Novel analytical expression for the exact intercept probability is derived and a closed-form approximation is also provided. We further propose an optimisation framework for fair subcarrier allocation with a novel objective of minimising maximum intercept probability among multiple users. Considering the proposed optimisation framework as a non-convex combinatorial, we propose a low-complexity sub-optimal solution by leveraging the integer linear program (ILP) structure of the problem. To reduce the complexity further, the original problem is mapped to the assignment model and solved by exploiting its special structure with graph theory tools providing an optimal solution in polynomial time. Comprehensive investigations, conducted to verify the analysis and quantify the secrecy performance, demonstrate that proposed optimal solutions yield significant enhancement in secrecy performance over relevant schemes.

中文翻译:

公平的子载波分配,以确保物联网中的OFDMA免受全双工混合攻击者的攻击

低计算资源的安全通信是物联网(IoT)实施中的关键问题。在具有全双工(FD)功能的混合对手同时执行窃听和干扰的情况下,这更具挑战性。在这项工作中,我们旨在通过优化子载波分配来解决这个问题,以对抗FD混合攻击者。我们从多用户物联网系统中的保密性能分析开始,仅考虑所有攻击者链接的统计通道状态信息。推导了用于精确拦截概率的新颖解析表达式,并提供了一种封闭形式的近似值。我们进一步提出了一个公平的子载波分配优化框架,其新颖的目标是最小化多个用户之间的最大拦截概率。考虑到所提出的优化框架是一个非凸组合,我们通过利用问题的整数线性规划(ILP)结构来提出一种低复杂度的次优解决方案。为了进一步降低复杂性,将原始问题映射到分配模型,并通过使用图论工具开发其特殊的结构以在多项式时间内提供最佳解决方案来解决该问题。为验证分析结果和量化保密性能而进行的全面调查表明,与相关方案相比,提出的最佳解决方案可以显着提高保密性能。最初的问题被映射到分配模型,并通过使用图论工具开发其特殊的结构以提供多项式时间的最佳解决方案来解决。为验证分析结果和量化保密性能而进行的全面调查表明,与相关方案相比,提出的最佳解决方案可以显着提高保密性能。最初的问题被映射到分配模型,并通过使用图论工具开发其特殊的结构以提供多项式时间的最佳解决方案来解决。为验证分析结果和量化保密性能而进行的全面调查表明,与相关方案相比,提出的最佳解决方案可以显着提高保密性能。
更新日期:2021-04-20
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