Secure Joint Communication and Sensing

Secure Joint Communication and Sensing
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DOI:
10.1109/isit50566.2022.9834748
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发表时间:
2022-02
期刊:
2022 IEEE International Symposium on Information Theory (ISIT)
影响因子:
--
通讯作者:
O. Günlü;M. Bloch;Rafael F. Schaefer;A. Yener
O. Günlü;M. Bloch;Rafael F. Schaefer;A. Yener
中科院分区:
其他
文献类型:
--
作者:
O. Günlü;M. Bloch;Rafael F. Schaefer;A. Yener

文献摘要

相似文献

这项工作考虑缓解联合通信和传感系统中的通信和传感操作之间的信息泄漏。具体地说,离散无记忆状态依赖广播信道模型的研究,其中(i)反馈的存在,使发射机,以同时实现可靠的通信和信道状态估计;(ii)接收机之一被视为窃听者的状态应估计,但应保持不经意的一部分传输的信息。该模型抽象了联合通信和感测安全性背后的挑战,如果将信道状态视为接收器的特性,例如,位置。对于独立同分布(i.i.d.)状态,完美的输出反馈,以及当部分传输的消息应该保密时,开发了保密失真区域的部分表征。当广播信道物理降级或反向物理降级时,该表征是准确的。该特征也被扩展到整个传输消息应该保密的情况。一个联合的方法相比,基于分离的安全通信和状态感知方法的好处是说明了一个二进制的联合通信和传感模型。
This work considers mitigation of information leakage between communication and sensing operations in joint communication and sensing systems. Specifically, a discrete memoryless state-dependent broadcast channel model is studied in which (i) the presence of feedback enables a transmitter to simultaneously achieve reliable communication and channel state estimation; (ii) one of the receivers is treated as an eavesdropper whose state should be estimated but which should remain oblivious to a part of the transmitted information. The model abstracts the challenges behind security for joint communication and sensing if one views the channel state as a characteristic of the receiver, e.g., its location. For independent and identically distributed (i.i.d.) states, perfect output feedback, and when part of the transmitted message should be kept secret, a partial characterization of the secrecy-distortion region is developed. The characterization is exact when the broadcast channel is either physically-degraded or reversely-physically-degraded. The characterization is also extended to the situation in which the entire transmitted message should be kept secret. The benefits of a joint approach compared to separation-based secure communication and state-sensing methods are illustrated with a binary joint communication and sensing model.