Sensor Systems and Software. 4th International ICST Conference, S-Cube 2013, Lucca, Italy, June 11-12, 2013, Revised Selected Papers

Research Article

REsilient Double WEighted TruST Based (REDWEST) WSN Using SAX

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  • @INPROCEEDINGS{10.1007/978-3-319-04166-7_2,
        author={Aline Siranossian and Hoda Maalouf},
        title={REsilient Double WEighted TruST Based (REDWEST) WSN Using SAX},
        proceedings={Sensor Systems and Software. 4th International ICST Conference, S-Cube 2013, Lucca, Italy, June 11-12, 2013, Revised Selected Papers},
        proceedings_a={S-CUBE},
        year={2014},
        month={6},
        keywords={Wireless sensor networks malicious node detection weighted trust resiliency},
        doi={10.1007/978-3-319-04166-7_2}
    }
    
  • Aline Siranossian
    Hoda Maalouf
    Year: 2014
    REsilient Double WEighted TruST Based (REDWEST) WSN Using SAX
    S-CUBE
    Springer
    DOI: 10.1007/978-3-319-04166-7_2
Aline Siranossian1,*, Hoda Maalouf1,*
  • 1: Notre Dame University Louaize
*Contact email: asiranossian@ndu.edu.lb, hmaalouf@ndu.edu.lb

Abstract

Wireless Sensor Networks (WSNs) are becoming the most widely used applications in monitoring environment and military operations. However, in such applications sensors are deployed in harsh environments and sometimes are inaccessible once deployed making them vulnerable to both physical and software attacks. Malicious nodes can send misleading data to the controller affecting monitoring results. Sophisticated security applications cannot be used to overcome this problem due to the limited power of the sensors. A new mechanism is needed which first identifies malicious nodes in an accurate manner and offers indispensible characteristics namely, resiliency and reliability to the WSN. In this paper, we develop a malicious and malfunctioning node detection scheme using a resilient double weighted trust evaluation technique in a hierarchical sensor network. Our system evaluates all sensor nodes, increases and decreases trust value accordingly and excludes nodes having under threshold trust values. The simulation results show that our approach is very efficient even in harsh environments.