The security of sensitive information is vital in many aspects of multimedia applications such as Intelligent Transportation Systems (ITSs), where traffic data collection, analysis and manipulations is essential. In ITS, the images captured by roadside units form the basis of many traffic rerouting and management techniques, and hence, we should take all precautions necessary to deter unwanted traffic actions caused by malicious adversaries. Moreover, the collected traffic images might reveal critical private information. Consequently, this paper presents a new image encryption algorithm, denoted as ChaosNet, using chaotic key controlled neural networks for integration with the roadside units of ITSs. The encryption algorithm is based on the Lorenz chaotic system and the novel key controlled finite field neural network. The obtained cryptanalysis show that the proposed encryption scheme has substantial mixing properties, and thus cryptographic strength with up to 5% increase in information entropy compared to other algorithms. Moreover, it offers consistent resistance to common attacks demonstrated by nearly ideal number of changing pixel rate (NPCR), unified averaged changed intensity (UACI), pixel correlation coefficient values, and robustness to cropped attacks. Furthermore, it has less than 0.002% difference in the NPCR and 0.3% in the UACI metrics for different test images.
Wireless sensor networks for irrigation applications normally consist of low-cost and low-power nodes deployed in a harsh environment. It turns out that the radio links between the coordinating node and actuating nodes are more critical and are expected to be more robust to radio interference and node failure than links between the coordinating node and sensing nodes. We present an efficient method to create robust links for irrigation sensor networks built on the ZigBee specification. In particular, multipaths between the coordinating node and actuating nodes are created and used to enhance the critical links. It is shown that, by utilizing the properties of addresses of ZigBee networks, those multipaths can be dynamically created and released adapting to topology changes without any path search activities. Simulation results confirm the robustness of the proposed multipath links.
The paper presents a model for the total Shannon capacity of a network as a function of antenna orientations. The resulting function is neither concave nor convex and is multiextrema with multiple local optima. An optimum solution for the orientations of the directional antennas leads to the global maximization of the total channel capacity. This global optimization problem cannot be solved by classical nonlinear programming technique. The objective function is shown to be Lipschitzian and is optimized by a Lipschitz optimization algorithm. The algorithm is a realization of the generic branch and bound methodology. Simulation results are reported and discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.