Download Pervasive Wireless Environments: Detecting and Localizing by Jie Yang PDF

By Jie Yang

This Springer short presents a brand new method of hinder person spoofing through the use of the actual homes linked to instant transmissions to realize the presence of consumer spoofing. the most typical procedure, employing cryptographic authentication, calls for extra administration and computational energy that can't be deployed continuously. The authors current the recent process via providing a precis of the hot learn and exploring the advantages and power demanding situations of this system. This short discusses the feasibility of launching consumer spoofing assaults and their impression at the instant and sensor networks. Readers are outfitted to appreciate a number of process versions. One assault detection version exploits the spatial correlation of bought sign power (RSS) inherited from instant units as a origin. via experiments in functional environments, the authors assessment the functionality of the spoofing assault detection version. The short additionally introduces the DEMOTE procedure, which exploits the correlation in the RSS hint in keeping with each one device’s id to discover cellular attackers. a last bankruptcy covers destiny instructions of this box. through providing advanced technical details in a concise structure, this short is a necessary source for researchers, execs, and advanced-level scholars thinking about instant community security.

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Extra resources for Pervasive Wireless Environments: Detecting and Localizing User Spoofing

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We note that under the case that the spoofing attack is present in a different network region of the victim node, a high-level domain management server should be able to detect the attack since the same node identity has appeared in more than one networks. 2 DEMOTE System Overview DEMOTE performs spoofing attack detection by analyzing the RSS trace for each mobile node identity. RSS is widely available in wireless communication networks and governed by the distance from a device to an AP. 2 Detection System Approach 45 are highly correlated with the physical location of a wireless device [5], and thus RSS readings represent a means to distinguish between devices as they move around an environment.

Let the 46 5 Detecting Mobile Agents Using Identity Fraud Input RSS samples from one node identity RSS Partitioning Produce two classes Sa and Sb in each time interval for each AP Trace Reconstruction Produce RSS traces Sg and Sp over the entire time window for each AP Correlation Coefficient Calculation Calculate in signal space or in physical space in Signal Space Calculate the correlation coefficient of Sg and Sp for each AP Combine correlation coefficients of APs Y Obtain location estimates from the localization process based on Sg and Sp Calculate the correlation coefficients of X and Y coordinates over time OR Use the correlation coefficient of individual AP in Physical Space Use the correlation coefficient of X or Y coordinate Correlation Coefficient < Threshold?

References 1. C. van Rijsbergen, Information Retrieval, Second Edition. Butterworths, 1979. 2. T. Fawcett, “An introduction to ROC analysis,” Pattern Recognition Letters, Elsevier, vol. 27, pp. 861–874, 2006. 3. P. Rousseeuw, “Silhouettes: a graphical aid to the interpretation and validation of cluster analysis,” Journal of Computational and Applied Mathematics, vol. 20, no. 1, pp. 53–65, November 1987. 4. K. Wang, J. Zheng, J. Zhang, and J. Dong, “Estimating the number of clusters via system evolution for cluster analysis of gene expression data,” IEEE Transactions on Information Technology in Biomedicine, vol.

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