Open Access Journal

ISSN : 2394-2320 (Online)

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

Monthly Journal for Computer Science and Engineering

Open Access Journal

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

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

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

Author : J.Beryl Tahpenes 1 R.Nirmalan 2

Date of Publication :30th May 2018

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.

Reference :

    1. Kaixing Huang, Qi Zhang, Naixue Xiong, Yuanquing Qin, "An Efficient Intrusion Detection Approach for Visual Sensor Networks based on Traffic Pattern Learning" in IEEE 2017.
    2.  Xiangyang Liu, Yaping Dai,Yan Zhang, Qiao Yuan, Linhui Zhao, "A Preprocessing method of Adaboost for Mislabeled Data Classification" in IEEE 2017.
    3. Rohini Rajpal, Sanmeet Kaur, Ramandeep Kaur, "Improving Detection Rate using Misuse Detection and Machine Learning" in IEEE 2016.
    4. Fei Lei, Lei Yao, Deng Zhao, Yucong Duan, "Energy efficient abnormal nodes detection and handlings in wireless sensor networks" in IEEE 2016.
    5. V.Jaiganesh, S.Mangayarkarasi, Dr.P.Sumathi "Intrusion detection systems: A survey and analysis of classification techniques" in IJARCCE 2013.
    6. Zoltan Csajbok "Simultaneous Anomaly and Misuse Intrusion Detections based on Partial Approximative Set Theory" in IEEE 2011.
    7. K.Q.Yan, S.C.Wang, S.S.Wang, C.W,Liu "Hybrid Intrusion Detection System for Enhancing the security of a cluster-based Wireless Sensor Network" in IEEE 2010.
    8. Bharanidharan, Shanmugam "Improved Intrusion Detection System using Fuzzy Logic for Detecting Anomaly and Misuse type of attacks" in IEEE 2009.
    9. Ashfaq Hussain, Farooqi Farrukh, Aslam Khan "Intrusion Detection Systems for Wireless Sensor Networks: A Survey" in Springer 2009.
    10. Wojciech, Tylman, "Misuse-Based Intrusion Detection Using Bayesian Networks" in IEEE 2008. 
    11. Alexandra Czarlinska, Deepa Kundur "Coordination and Selfishness in Attacks on Visual Sensor Networks" in IEEE 2008.
    12. Ting Yang, Tang Young, "Short Life Artificial Fish Swarm Algorithm for Wireless Sensor Network" in IEEE 2013.
    13. Slobodan Petrovic, Sverre Bakke, "Improving the Efficiency of Misuse Detection by Means of q-gram Distance" in IEEE 2016.
    14. Adrian Perrig, Robert Szewczyk, J.D.Tygar, Victor Wen, David E.Culler "SPINS: Security Protocols for Sensor Networks" in IEEE 2002.
    15. Peter Lichodzijewski, Malcolm, I.Heywood "HostBased Intrusion Detection Using Self-Organizing Maps" in IEEE 2002.

Recent Article