Practical defenses against pollution attacks in intra-flow network coding for wireless mesh networks

Abstract

Recent studies show that network coding can provide significant benefits to network protocols, such as increased throughput, reduced network congestion, higher reliability, and lower power consumption. The core principle of network coding is that intermediate nodes actively mix input packets to produce output packets. This mixing subjects network coding systems to a severe security threat, known as a pollution attack, where attacker nodes inject corrupted packets into the network. Corrupted packets propagate in an epidemic manner, depleting network resources and significantly decreasing throughput. Pollution attacks are particularly dangerous in wireless networks, where attackers can easily inject packets or compromise devices due to the increased network vulnerability.In this paper, we address pollution attacks against network coding systems in wireless mesh networks. We demonstrate that previous solutions to the problem are impractical in wireless networks, incurring an unacceptably high degradation of throughput. We propose a lightweight scheme, DART, that uses time-based authentication in combination with random linear transformations to defend against pollution attacks. We further improve system performance and propose EDART, which enhances DART with an optimistic forwarding scheme. A detailed security analysis shows that the probability of a polluted packet passing our verification procedure is very low. Performance results using the well-known MORE protocol and realistic link quality measurements from the Roofnet experimental testbed show that our schemes improve system performance over 20 times compared to previous solutions.

Secure network coding for wireless mesh networks: Threats, challenges, and directions

“…For example, if we consider the routing problem, throughput decreases linearly with the number of attackers for simple attacks (e.g., black hole attack with randomly-placed adversaries), and it decreases much more sharply for more sophisticated attacks (e.g., wormhole attacks with strategically-placed adversaries) [4,11]. A similar effect was observed for pollution attacks in intra-flow network coding systems [14]. However, the impact of the attacks on the routing protocol is drastically reduced when security mechanisms are applied on top of the unsecure system.…”

“…We expect that provisioning a network coding system with security mechanisms will also significantly reduce the impact of attacks. Indeed, this was shown to be true for pollution attacks in intra-flow network coding systems [14]. Therefore, another important security goal is to ensure at most a graceful degradation in performance as the number of attackers increases.…”

“…Existing defense techniques are generally heavy-weighted (see Section 2), leading to a significant negative impact on the protocol performance. Recently, a lightweight solution based on efficient linear checksums and time asymmetry was proposed [14]. However, designing a lightweight pollution defense for intra-flow coding systems in wireless networks that does not rely on time synchronization is still an open problem.…”

Securing coding based distributed storage in wireless sensor networks

“…Set S is formed of the equations that have non-zero coefficient in this linear combination (lines [10][11][12][13][14]. If S has less than l elements, the last received equation is not innovative and it is dropped (line 4), and the operation continues (loop of lines [3][4][5][6][7][8][9][10][11][12][13][14][15]. If S has exactly l elements, we can assume that the last received equation is the (l + 1)-st intact equation, and S contains the first l intact equations received.…”

“…While network coding has advantages in benign environments, its performance may seriously fall in the presence of an adversary [11], [12], [13]. We present a scheme that resists pollution attacks, meaning that our scheme makes possible successful decoding even if some compromised nodes store maliciously modified data.…”