Communication and Distributed Systems

Thesis Topics

Data-driven Enhancement of Mobile Ad Hoc Networks’ Reliability Against Jamming Attacks

With the advent of new cellular communication technologies, applications running on mobile networks can afford to demand strict requirements and high performance from the system. To offload traffic from the core network, researchers are actively studying the potential of direct D2D communications in mobile networks.

Direct D2D exchange of information is fundamental type of operation of mobile networks, which is considered and defined by standards that regulate both licensed and non-licensed spectra. Direct D2D information exchange allows each network device to cooperatively relay traffic from other source devices to their intended destination devices, actively contributing to the distributed system's operation.

Compared to fixed-infrastructure networking services, traditionally offered by telco operators, the distributed device to device network of mobile nodes, also called a Mobile Ad Hoc Network (MANET), offers increased reliability, as it removes the common issues of centralized networking, such as single-point-of-failure.

As additional benefit, it decentralizes the ownership of the communications infrastructure, mitigating privacy leaks and metadata analysis. Ad hoc networking also accelerates the deployment of communication networks in developing countries, harsh landscapes, and military operations. Nevertheless, MANETs' topologies are highly dynamic and irregular, which could expose some network weaknesses in the form of relay nodes responsible for relaying several data traffic flows.

Besides representing a topological weakness of the MANET, these nodes are also at a higher risk of becoming congested, as their link capacity must be shared between several flows. A malicious user could easily disrupt the operation of the MANET by targeting attacks to the devices that are weak links between two partitions of the network topology.

Some studies aim to assess and enhance the topology reliability by optimizing the network topology but disregard the current traffic status on the network. This thesis project aims to design and evaluate a countermeasure to increase the MANET resiliency and neutralize jamming attacks that can take down critical MANET links in two ways. First, by immediately rerouting traffic on alternative paths. Secondly, by modifying the MANET topology through either node repositioning or transmission power adaptation.

The attacker: We start from the safe assumption that jammers do not know the global MANET topology and must estimate it locally. In more challenging scenarios, the attacker might have partial or full information about the network topology and perform an informed attack to the most important relay nodes. This allows the attacker to attack (jam) the node that would generate the maximum disruption if lost. Potential metrics of “disruption” could be targeting the node relaying the most traffic instantly. However, the MANET could easily react to this attack by rerouting traffic to a nearby, well-connected node. Therefore, a more sophisticated attacker could target a minimal set of nodes to minimize his detectability while aiming at taking down a subset of crucial nodes that would make it impossible (or hard) for the MANET to recover connectivity.

The counterattack: We assume that the MANET in our scenario adopts a method to detect an ongoing jamming attack cooperatively. Improving jammer detection and localization is not our main aim, and we adopt state-of-the-art solutions that provide excellent results. Furthermore, we also assume that the considered MANET already adopts a fast route repair mechanism that can quickly restore data delivery following the beginning of the jamming event, waiting until the topology is modified to re-establish network resiliency. This thesis project focuses on designing a cooperative and distributed algorithm/system that allows MANET nodes to collectively and immediately react to a clear, confirmed jamming attack by generating and executing a reaction plan by each node. The first step of the reaction plan is to compute an optimal physical location and transmission power of each MANET node in the “vicinity” of the detected jammer. The second step of the reaction plan is controlling the movement of each node to reach the optimal target position to re-establish connectivity. Finally, the position of the jammer should be re-measured, and a new reaction plan should be generated and executed in a loop until the menace has been neutralized. This results in modifying the MANET topology and restoring the original MANET functionality, providing high reliability under jamming attacks.

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