International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume5,May 2018,

Topic : An Integrated Intrusion Detection Model of Cluster- Based Visual Sensor Networks

Authors:J.Beryl Tahpenes || R.Nirmalan

Abstract:Visual sensor networks (VSNs) are highly exposed to attacks since they are arranged openly in possibly solitary environments. Due to the bulky and bursty data traffic in VSN, it thrusts the need to establish mechanisms which provide reliable data communication across the network over the unreliable channels. Optimized Adaptive Boosting (OAB) algorithm is used for detection of anomalies in sensor nodes, cluster head nodes and Sink nodes. In this paper, in order to identify the modified packets or attacked packets at the receiver side, we propose a protocol named Efficient Secure Routing for Attacker Identification (ESRAI). This paper proposes an integrated intrusion detection model of cluster-based visual sensor network by combining anomaly and misuse detection, aiming at enhancing overall detection, security and System Accuracy. The proposed integrated model provides high throughput and more security, and it increases the efficiency of entire network when compared to the existing network..

Keywords: VSN, Optimized Adaptive Boosting (OAB) algorithm, Cluster-based VSN, ESRAI protocol

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DOI: 01.1617/vol5/iss5/pid50284


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Editor-in-Chief

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Dr. Allon Guez
Professor, Drexel University,
USA


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IMPACT FACTOR: 4.890

ISSN(Online):2394-2320

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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ACCEPTANCE RATIO

ACCEPTANCE RATIO: 28.69%
ARTICLES PUBLISHED:0521
PAPER RECEIVED:01730
Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
Frequency : monthly
Contact : info@ijercse.com


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