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The Man-in-the-Middle (MitM) attack is a cyber-attack in which an attackerintercepts traffic, thus harming the confidentiality, integrity, andavailability of the network. It remains a popular attack vector due to itssimplicity. However, existing solutions are either not portable, suffer from ahigh false positive rate, or are simply not generic. In this paper, we proposeVesper: a novel plug-and-play MitM detector for local area networks. Vesperuses a technique inspired from impulse response analysis used in the domain ofacoustic signal processing. Analogous to how echoes in a cave capture the shapeand construction of the environment, so to can a short and intense pulse ofICMP echo requests model the link between two network hosts. Vesper uses neuralnetworks called autoencoders to model the normal patterns of the echoed pulses,and detect when the environment changes. Using this technique, Vesper is ableto detect MitM attacks with high accuracy while incurring minimal networkoverhead. We evaluate Vesper on LANs consisting of video surveillance cameras,servers, and PC workstations. We also investigate several possible adversarialattacks against Vesper, and demonstrate how Vesper mitigates these attacks.

Vesper: Using Echo-Analysis to Detect Man-in-the-Middle Attacks in LANs