Biblio

With the advancement of unmanned aerial vehicles (UAV), 3D wireless mesh networks will play a crucial role in next generation mission critical wireless networks. Along with providing coverage over difficult terrain, it provides better spectral utilization through 3D spatial reuse. However, being a wireless network, 3D meshes are vulnerable to jamming/disruptive attacks. A jammer can disrupt the communication, as well as control of the network by intelligently causing interference to a set of nodes. This paper presents a distributed mechanism of avoiding jamming attacks by means of 3D spatial filtering where adaptive beam nulling is used to keep the jammer in null region in order to bypass jamming. Kalman filter based tracking mechanism is used to estimate the most likely trajectory of the jammer from noisy observation of the jammer's position. A beam null border is determined by calculating confidence region of jammer's current and next position estimates. An optimization goal is presented to calculate optimal beam null that minimizes the number of deactivated links while maximizing the higher value of confidence for keeping the jammer inside the null. The survivability of a 3D mesh network with a mobile jammer is studied through simulation that validates an 96.65% reduction in the number of jammed nodes.

A botnet in mobile networks is a collection of compromised nodes due to mobile malware, which are able to perform coordinated attacks. Different from Internet botnets, mobile botnets do not need to propagate using centralized infrastructures, but can keep compromising vulnerable nodes in close proximity and evolving organically via data forwarding. Such a distributed mechanism relies heavily on node mobility as well as wireless links, therefore breaks down the underlying premise in existing epidemic modeling for Internet botnets. In this paper, we adopt a stochastic approach to study the evolution and impact of mobile botnets. We find that node mobility can be a trigger to botnet propagation storms: the average size (i.e., number of compromised nodes) of a botnet increases quadratically over time if the mobility range that each node can reach exceeds a threshold; otherwise, the botnet can only contaminate a limited number of nodes with average size always bounded above. This also reveals that mobile botnets can propagate at the fastest rate of quadratic growth in size, which is substantially slower than the exponential growth of Internet botnets. To measure the denial-of-service impact of a mobile botnet, we define a new metric, called last chipper time, which is the last time that service requests, even partially, can still be processed on time as the botnet keeps propagating and launching attacks. The last chipper time is identified to decrease at most on the order of 1/√B, where B is the network bandwidth. This result reveals that although increasing network bandwidth can help with mobile services; at the same time, it can indeed escalate the risk for services being disrupted by mobile botnets.