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Malicious Node Detection and Adaptive Data Fusion in Sensor Network - IEEE Project 2014-2015

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  micans infotech   +91 90036 28940 +91 94435 11725    MICANS INFOTECH , NO: 8 , 100 FEET ROAD,PONDICHERRY .   WWW.MICANSINFOTECH.COM ; MICANSINFOTECH@GMAIL.COM   +91 90036 28940; +91 94435 11725   IEEE Projects 100% WORKING CODE + DOCUMENTATION+ EXPLAINATION – BEST PRICE   LOW PRICE GUARANTEED   MALICIOUS NODE DETECTION AND ADAPTIVE DATA FUSION IN SENSOR NETWORK    ABSTRACT:   Wireless sensor networks have received significant attention due to serious threat such as byzantine attack where the adversary has full control over some of the authenticated nodes and can perform arbitrary behavior to disrupt the system. In this paper we consider q - out - of  - m fusion rule which is popular in distributed detection and can achieve a good tradeoff between the miss detection  probability and the false alarm rate. We propose a simplified, linear q - out - of  - m scheme that can be easily applied to large size networks. The basic idea is to find the optimal scheme parameters at relatively small network sizes through exhaustive search, and then obtain the fusion parameters for large network size  by exploiting the approximately linear relationship between the scheme  parameters and the network size. It is observed that the proposed linear approach can achieve satisfying accuracy with low false alarm rate. However, there are chances of violating the problem constraint. To enforce the miss detection constraint and improve the data fusion accuracy, we further propose to use the linear approximation as the initial point for the optimal exhaustive search algorithm.    micans infotech   +91 90036 28940 +91 94435 11725    MICANS INFOTECH , NO: 8 , 100 FEET ROAD,PONDICHERRY .   WWW.MICANSINFOTECH.COM ; MICANSINFOTECH@GMAIL.COM   +91 90036 28940; +91 94435 11725   IEEE Projects 100% WORKING CODE + DOCUMENTATION+ EXPLAINATION – BEST PRICE   LOW PRICE GUARANTEED   EXISTING SYSTEM:   In existing system, we consider reliable data fusion in wireless sensor networks with mobile access points (SENMA) under both static and dynamic Byzantine attacks, in which the malicious nodes report false information with a fixed or time - varying probability, respectively. In SENMA, the mobile access  point traverses the network and collects the sensing information from the individual sensor nodes. The major advantage of the SENMA architecture is that it ensures a line of sight path to the access point within the power range of the sensor nodes, allowing the information to be conveyed without routing. This feature makes it a resilient, scalable and energy efficient architecture for wireless sensor networks .   PROBLEM DEFINITION:   Due to its high computational complexity, the optimal q - out - of  - m scheme is infeasible as the network size increases and/or the attack behavior changes.   PROPOSED SYSTEM:   We proposed simplified q - out - of  - m fusion schemes by exploiting the linear relationship between the scheme parameters and the network size. We also derived a near  - optimal closed - form solution for the fusion threshold based on the central limit theorem. An important observation is that, even if the  percentage of malicious sensors remains fixed, the false alarm rate diminishes exponentially with the network size. This implies that for a fixed percentage of  micans infotech   +91 90036 28940 +91 94435 11725    MICANS INFOTECH , NO: 8 , 100 FEET ROAD,PONDICHERRY .   WWW.MICANSINFOTECH.COM ; MICANSINFOTECH@GMAIL.COM   +91 90036 28940; +91 94435 11725   IEEE Projects 100% WORKING CODE + DOCUMENTATION+ EXPLAINATION – BEST PRICE   LOW PRICE GUARANTEED   malicious nodes, we can improve the network performance significantly by increasing the density of the nodes.   ADVANTAGES OF PROPOSED SYSTEM:      We show that under a fixed percentage of malicious nodes, the false alarm rate for both approaches diminishes exponentially as the network size increases.    The proposed adaptive fusion scheme can improve the system  performance significantly under both static and dynamic attack strategies. HARDWARE REQUIREMENTS      Processor Type : Pentium -IV    Speed : 2.4 GHZ    Ram : 128 MB RAM    Hard disk : 20 GB HD SOFTWARE REQUIREMENTS:      Operating System : Linux  –   red hat 9.0    Programming Package : C++ , TCL    Tool Used : Vm ware Work station    Version : NS2 2.27, 2.29 , 2.34
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