Elimination of Black Hole and False Data Injection Attacks in Wireless Sensor Networks
Wireless Sensor Networks (WSNs) are currently being used in a wide range of applications that demand high security requirements. Since sensor network is highly resource constrained, providing security becomes a challenging issue. Attacks must be detected and eliminated from the network as early as possible to enhance the rate of successful transactions. In this paper, we propose to eliminate Black Hole and False Data Injection attacks initiated by the compromised inside nodes and outside malicious nodes respectively using a new acknowledge scheme with low overhead. Simulation results show that our scheme can successfully identify and eliminate 100 % black hole nodes and ensures more than 99 % packet delivery with increased network traffic.
KeywordsSecurity Sink acknowledgement Negative acknowledgement Black hole attack Packet delivery rate
- 1.Tanveer Z, Albert Z (2006) Security issues in wireless sensor networks. In: Proceedings international conference systems and networks communication (ICSNC 06), Oct 2006Google Scholar
- 3.Misra S, Bhattarai K, Guoliang X (2011) BAMBi: blackhole attacks mitigation with multiple base stations in wireless sensor networks. In: Proceedings international conference communications (ICC 2011), July 2011Google Scholar
- 4.Bysani LK, Turuk AK (2011) A survey on selective forwarding attack in wireless sensor networks. In: Proceedings international conference on devices and communications (ICDeCom), Feb 2011Google Scholar
- 5.Kaplantzis S, Shilton A, Mani N, Sekercioglu YA (2007) Detecting selective forwarding attacks in wireless sensor networks using support vector machines. In: Proceedings third international conference on intelligent sensors, sensor networks and information, pp 335–340, Dec 2007Google Scholar
- 6.Ba M, Niang I, Gueye B, Noel T (2010) A deterministic key management scheme for securing cluster-based sensor networks. In: Proceedings 2010 IEEE/IFIP international conference on embedded and ubiquitous computing, pp 422–427, Dec 2010Google Scholar