T-TRAIL: Preventing Decreased Rank Attacks in RPL-based IoT Networks

Abstract

The Routing Protocol for Low-Power and Lossy Networks (RPL) has gained in popularity since the increased connectivity of everyday items to the Internet. One of the discovered attacks on RPL is the rank attack, which opens up possibilities for attackers to control traffic in the RPL network by spoofing their priority. Many solutions have been proposed to mitigate this attack over the past few years. There is no perfect solution yet, partly because the success of a mitigation is dependent on the network configuration in which it is implemented. In some network configurations,as this paper will show, common mitigation solutions are less effective. By selecting and analyzing four well-cited mitigation and detection solutions, the effectiveness of these proposals is reviewed when the network is configured to use nonlinear objective functions (NOFs). After this, a proposal is given to defend against a rank attack when using NOFs. TRAIL was proposed as a solution for preventing decreased rank attacks and uses a challenge-response mechanism to verify the path from a node to the root. This paper proposes T-TRAIL; an extended version of TRAIL that allows the measurement of downwards-trip-time to detect outliers in the network. By doing this, the rank attack can be prevented when the network uses a NOF. Finally, an estimation of the performance impact of T-TRAIL on the network is given based on the performance measurements of TRAIL.