WHACK: Adversarial Beamforming in MU-MIMO Through Compressed Feedback Poisoning

Multi-user MIMO is a key component of modern wireless networks. As such, investigating the related security weaknesses is a compelling necessity. A major issue unveiled by existing work is that adversaries can “poison” the channel information feedback reported to the beamformer to decrease the performance experienced by a legitimate user. Prior work, however, assumes that the feedback is reported in an uncompressed fashion, which is not the case in current wireless standards such as Wi-Fi or 5G. In this work, we first show that assuming uncompressed feedback leads to overestimating the attack effectiveness by up to 60%. Next, we formulate ACFP (Adversarial Compressed Feedback Problem), a novel non-convex constrained optimization problem to find the compressed feedback that maximizes a victim’s bit error rate (BER) while satisfying maximum power constraints. We propose WHACK (Wireless Harmful Adversarial Compressed feedbacK), a new algorithm to solve ACFP and find the malicious compressed feedback based on the convexity of the objective function and constraint using a nonlinear conjugate gradient method. WHACK has been prototyped and extensively evaluated with off-the-shelf Wi-Fi devices. Experimental results show that it maximizes the victim’s BER, while modifying less than 60% of the feedback. Our dataset and code are available.