期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：5
出版社：S.S. Mishra
摘要：The open nature of the wireless medium leaves it vulnerable to intentional interference attacks, typically referred to as jamming. This intentional interference with wireless transmissions can be used as a launch pad for mounting Denial-of-Service attacks on wireless networks. Typically, jamming has been addressed under an external threat model. However, adversaries with internal knowledge of protocol specifications and network secrets can launch low-effort jamming attacks that are difficult to detect and counter. In this wo rk, we address the problem of selective jamming attacks in wireless networks. In these attacks, the adversary is active only for a short period of time, selectively targeting messages of high importance. We illustrate the advantages of selective jamming in terms of network performance degradation and adversary effort by presenting two case studies; a selective attack on TCP and one on routing. We show those selective jamming attacks can be launched by performing real-time packet classification at the physical layer. We analyze the security of our methods and evaluate their computational and communication overhead. Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths. In this paper, we consider the problem of jamming -aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual netwo rk nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics. We show that in multi source networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization (NUM). We demonstrate the network's ability to estimate the impact of jamming and incorporate these estimates into the traffic allocation problem. Finally, we simulate the achievable throughput using our proposed traffic allocation method in several scenarios. In Future we can gather the Jamming node information on the server where as, Here we have done on the client side. On gathering this jamming node information from the client to server side we can produce an effective path table to the client node to transfer the data..
