Using discriminant analysis to detect intrusions in external communication for self-driving vehicles

Security systems are a necessity for the deployment of smart vehicles in our society. Security in vehicular ad hoe networks is crucial to the reliable exchange of information and control data. In this paper, we propose an intelligent Intrusion Detection System （IDS） to protect the external communication of self-driving and semi self-driving vehicles. This technology has the ability to detect Denial of Service （DOS） and black hole attacks on vehicular ad hoe networks （VANETs）. The advantage of the proposed IDS over existing security systems is that it detects attacks before they causes significant damage. The intrusion prediction technique is based on Linear Discriminant Analysis （LDA） and Quadratic Diseriminant Analysis （QDA） which are used to predict attacks based on observed vehicle behavior. We perform simulations using Network Simulator 2 to demonstrate that the IDS achieves a low rate of false alarms and high accuracy in detection.

Design and analysis of a network coding algorithm for ad hoc networks

Network coding is proved to have advantages in both wireline and wireless networks. Especially, appropriate network coding schemes are programmed for underlined networks. Considering the feature of strong node mobility in aviation communication networks, a hop-by-hop network coding algorithm based on ad hoc networks was proposed. Compared with COPE-like network coding algorithms, the proposed algorithm does not require overhearing from other nodes, which meets confidentiality requirements of aviation communication networks. Meanwhile, it does save resource consumption and promise less processing delay. To analyze the performance of the network coding algorithm in scalable networks with different traffic models, a typical network was built in a network simulator, through which receiving accuracy rate and receiving delay were both examined.The simulation results indicate that, by virtue of network coding, the proposed algorithm works well and improves performance significantly. More specifically, it has better performance in enhancing receiving accuracy rate and reducing receiving delay, as compared with any of the traditional networks without coding. It was applied to both symmetric and asymmetric traffic flows and, in particular, it achieves much better performance when the network scale becomes larger. Therefore, this algorithm has great potentials in large-scale multi-hop aviation communication networks.