引用本文: | 盛响,王少尉.在线学习的主用户仿冒攻击策略[J].国防科技大学学报,2020,42(4):12-17.[点击复制] |
SHENG Xiang,WANG Shaowei.Online learning for primary user emulation attack strategy[J].Journal of National University of Defense Technology,2020,42(4):12-17[点击复制] |
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在线学习的主用户仿冒攻击策略 |
盛响,王少尉 |
(南京大学 电子科学与工程学院, 江苏 南京 210023)
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摘要: |
在认知无线网络中,次用户通过频谱感知来学习频谱环境,从而接入那些没有被主用户占用的频谱空隙。事实上,多种恶意攻击的存在会影响次用户频谱感知的可靠性。只有深入研究恶意攻击策略,才能确保认知无线网络的安全。基于此,研究了一种认知无线网络中的欺骗性干扰策略,即主用户仿冒攻击策略,该攻击策略通过在信道上传输伪造的主用户信号来降低次用户频谱感知的性能。具体来说,将攻击策略问题建模为在线学习问题,并提出基于汤普森采样的攻击策略以实现在探索不确定信道和利用高性能信道间的权衡。仿真结果表明,与现有的攻击策略相比,提出的攻击策略能更好地通过在线学习优化攻击决策以适应非平稳的认知无线网络。 |
关键词: 认知无线电 在线学习 主用户仿冒攻击 频谱感知 汤普森采样 |
DOI:10.11887/j.cn.202004003 |
投稿日期:2019-12-25 |
基金项目:国家自然科学基金资助项目(61671233,61801208, 61931023) |
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Online learning for primary user emulation attack strategy |
SHENG Xiang, WANG Shaowei |
(School of Electronic Science and Engineering, Nanjing University, Nanjing 210023, China)
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Abstract: |
In cognitive radio system, the secondary users learn radio spectrum environment through spectrum sensing to get the spectrum holes that the primary users do not occupy. In practice, the existence of various malicious attacks can seriously affect the reliability of spectrum sensing of the secondary users. Only in-depth study of the malicious attack strategies can ensure the security of cognitive radio networks. Based on this, a spoofing jamming strategy in cognitive wireless network, called as primary user emulation attack strategy, was studied. The strategy deteriorates the spectrum sensing performance of the secondary users by transmitting the forged primary user signals over channels. More concretely, the attack strategy was modeled as an online learning problem, and a Thompson sampling based attack strategy was proposed to find an efficient tradeoff between the exploitation of high-performance channels and the exploration of uncertain channels. The simulation results show that compared with the existing attack strategy, the proposed attack strategy can better adapt to the non-stationary cognitive wireless network by optimizing the attack decision through online learning. |
Keywords: cognitive radio online learning primary user emulation attack spectrum sensing Thompson sampling |
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