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Hacker Detection in Wireless sensor network
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Abstract Intrusion detection in Wireless Sensor Network (WSN) is of practical interest in many applications such as detecting an intruder in a battlefield. The intrusion detection is defined as a mechanism for a WSN to detect the existence of inappropriate, incorrect, or anomalous moving attackers. In this paper, we consider this issue according to heterogeneous WSN models. Furthermore, we consider two sensing detection models: single-sensing detection and multiple-sensing detection... Our simulation results show the advantage of multiple sensor heterogeneous WSNs.
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Data Flow Diagram Heterogeneous multiple sensor
Detec1 A S1 Detec2 B S2 Detec3 C Data Flow Intruder Sending packet from source S to D
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Heterogeneous single sensor
Rec1 Rec 3 Detector Data Flow Rec 2 Source Filter
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Existing System In single-sensing detection, At a time only one intruder detected by the detector. Our Previous work was according to homogeneous and heterogeneous single sensor in wireless sensor network.
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Proposed System In Heterogeneous wireless sensor intruder detected anywhere in the network. We are detecting the intruder in multiple sensor heterogeneous wireless sensor network.
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Advantages If primary detector fails another detector detect the intruder. By finding the intruders we can send our information in a secured manner.
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Disadvantages Data will not routed if primary detector fails.
So that there is no guarantee for our information has been sent securely.
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Software & Hardware Requirements
Software Requirement Java1.4 or More Swings Windows 98 or more. Hardware requirement Hard disk : 40 GB RAM : 128mb Processor : Pentium
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Bibliography or References
[1] D.P. Agrawal and Q.-A. Zeng, Introduction to Wireless and Mobile Systems. Brooks/Cole Publishing, Aug [2] B. Liu and D. Towsley, “Coverage of Sensor Networks: Fundamental Limits,” Proc. Third IEEE Int’l Conf. Mobile Ad Hoc and Sensor Systems (MASS), Oct [3] S. Ren, Q. Li, H. Wang, X. Chen, and X. Zhang, “Design and Analysis of Sensing Scheduling Algorithms under Partial Coverage for Object Detection in Sensor Networks,” IEEE Trans. Parallel and Distributed Systems, vol. 18, no. 3, pp , Mar [4] S. Banerjee, C. Grosan, A. Abraham, and P. Mahanti, “Intrusion Detection on Sensor Networks Using Emotional Ants,” Int’l J. Applied Science and Computations, vol. 12, no. 3, pp , 2005. [5] S. Capkun, M. Hamdi, and J. Hubaux, “GPS-Free Positioning in Mobile Ad-Hoc Networks,” Proc. 34th Ann. Hawaii Int’l Conf.System Sciences, Jan [6] N. Bulusu, J. Heidemann, and D. Estrin, “Gps-Less Low Cost Outdoor Localization for Very Small Devices,” IEEE Personal Comm. Magazine, special issue on smart spaces and environments,2000.
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