Securing Wireless Broadcast Communications against Internal Attacks

Prof. Marwan Krunz

University of Arizona


Wireless communications are vulnerable to jamming attacks. Conventional anti-jamming techniques are based on spread spectrum techniques. For broadcast (one-to-many) communications, such techniques often rely on a shared secret, e.g., a shared pseudorandom-noise (PN) sequence. By compromising one or more legitimate nodes, an adversary can gain access to such a secret and can selectively jam broadcasted packets. In this work, we address the problem of securing broadcast communications against such attacks. We consider a sophisticated adversary, who has knowledge of the protocol specifics and of the cryptographic quantities used to secure network operations. First, we consider attacks on control packets in a multi-channel wireless network. We propose new security metrics to quantify the ability of the adversary to deny access to the control channel, and introduce a randomized distributed scheme that allows nodes to establish and maintain the control channel in the presence of the jammer. Our method is applicable to networks with static or dynamically allocated spectrum. Furthermore, we propose two algorithms for unique identification of the set of compromised nodes, one for independently acting nodes and one for colluding nodes. We then consider a more general broadcast communications scenario (data or control) and propose a time-delayed broadcast scheme (TDBS) that implements the broadcast operation as a series of unicast transmissions, distributed in frequency and time. TDBS does not rely on commonly shared secrets, or the existence of jamming-immune control channels for coordinating broadcasts. Instead, each node follows a unique PN hopping sequence. Contrary to conventional PN sequences designed for multi-access systems, our sequences exhibit high correlation to enable broadcast. Moreover, their design limits the information leakage due to the exposure of a subset of sequences by compromised nodes. (This work is joint with Loukas Lazos and Sisi Liu, University of Arizona).

[Prof. Marwan Krunz]
University of Arizona