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

移动数据流量继续以指数级速度增长。为了应对这一数据挑战，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，允许同时为许多用户服务。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，但在大规模MIMO部署之前，仍有许多重大的研究挑战需要解决。大规模MIMO的成功运行关键取决于对基站和终端用户之间信道状态信息的了解。实际上，这将在训练阶段获得，在这个阶段，用户向基站发送个别飞行员信号。这一阶段是具有挑战性的，因为大量的最终用户会导致导频重用，从而导致导频污染，并且由于容易受到恶意窃听者的攻击，恶意窃听者可能通过传输相同的导频信号来欺骗合法用户。该项目侧重于检测和防御先导污染攻击的方法。本研究探讨了检测和防御来自主动窃听者和欺骗中继的先导污染攻击的创新方法。引入的一个关键变革思想是合法用户对导频序列的自污染，以促进主动窃听者的检测。该项目在以下研究重点的背景下探索了这一想法的各种分支。(1)主动窃听者先导污染攻击的检测：假设已知训练序列集（不知道其他），可以检测出一个或多个训练序列是否受到攻击。基于数据关联函数的源枚举方法正在被开发。(2)联合获取合法用户和窃听者的信道状态信息，以便进行有效的波束形成设计，提高合法用户的接收能力，同时降低窃听者的接收能力。(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工作，简单地以时分双工上行操作将合法用户的信号放大并转发到基站。

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.