EAGER: Detection and Mitigation of Pilot Contamination Attacks and Related Issues in Massive MIMO Systems

移动的数据业务继续以指数速率增长。为了满足这种数据挑战，最近提出了大规模MIMO（多输入多输出）系统技术，其中基站采用大量天线，允许同时服务许多用户。它被认为是未来5G无线系统的关键推动者之一。虽然最近的原型已经证明了其可行性，但在部署大规模MIMO之前，仍有许多重大的研究挑战有待解决。大规模MIMO的成功运行关键取决于基站和终端用户之间的信道状态信息的知识。实际上，这将在用户向基站发送单独的导频信号的训练阶段期间获得。由于大量的终端用户导致导频重用，导致导频污染，并且由于易受恶意窃听者的攻击，恶意窃听者可能通过发送相同的导频信号来欺骗合法用户，因此该阶段是具有挑战性的。该项目的重点是检测和防御飞行员污染攻击的方法。 创新的方法来检测和防御主动窃听者以及欺骗中继的导频污染攻击在这项研究中进行了调查。一个关键的变革性的想法是，自污染的导频序列的合法用户，以方便检测活跃的窃听者。这个项目探讨了这一想法的各种分支在以下研究主旨的背景下。(1)主动窃听者对导频污染攻击的检测：假设知道训练序列的集合（并且没有别的），可以检测一个或多个训练序列是否受到攻击。基于数据相关函数的源枚举方法正在开发中。(2)联合获取合法用户和窃听者的信道状态信息，以促进有效的波束成形设计，从而增强合法用户处的接收，同时降低窃听者处的接收。(3)通过欺骗中继攻击检测和缓解主动窃听，其中欺骗中继以全双工模式运行，并简单地放大来自合法用户的信号并将其转发到时分双工上行链路操作中的基站。

Mobile data traffic continues to grow at an exponential rate. To meet this data challenge, massive MIMO (multiple-input multiple-output) system technology has recently been proposed where the base station employs a large number of antennas, allowing many users to be served simultaneously. It is regarded as one of the key enablers of future 5G wireless systems. While recent prototypes have demonstrated its feasibility, many significant research challenges remain to be addressed before massive MIMO can be deployed. Successful operation of massive MIMO depends critically on knowledge of the channel state information between the base station and the end users. In practice this would be acquired during the training phase where the users send individual pilot signals to the base station. This phase is challenging due to a large number of end users which lead to pilot reuse causing pilot contamination, and due to vulnerability to attacks by malicious eavesdroppers who may spoof legitimate users by transmitting identical pilot signals. This project is focused on methods to detect and defend against pilot contamination attacks. Innovative approaches to detect and defend against pilot contamination attacks from active eavesdroppers as well as from spoofing relays are investigated in this research. A key transformative idea introduced is that of self-contamination of pilot sequences by legitimate users to facilitate detection of active eavesdroppers. This project explores various ramifications of this idea in the context of the following research thrusts. (1) Detection of pilot contamination attacks by active eavesdroppers: Assuming the knowledge of the set of training sequences (and nothing else), can one detect whether one or more training sequences are under attack. Source enumeration methods based on data correlation function are being exploited. (2) Joint acquisition of channel state information for both legitimate users and eavesdroppers to facilitate effective beamforming designs to enhance reception at legitimate users while degrading reception at eavesdroppers. (3) Detection and mitigation of active eavesdropping via spoofing relay attack where a spoofing relay operates in a full-duplex mode and simply amplifies and forwards the signal from a legitimate user to the base station in a time-division duplex uplink operation.