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A QOS Parameter based Solution for Black hole Denial of Service Attack in Wireless Sensor Networks

Affiliations

  • Department of MCA, RV College of Engineering, Bangalore – 560059, Karnataka, India
  • VIT University, Vellore – 632014, Tamil Nadu, India

Abstract


Background/Objectives: A typical Wireless Sensor Network (WSN) is a collection of Sensor nodes with limited charge that get deployed in a range enabling different applications. Enormous potential is there for deployment of WSN in consumer centric applications, industry sector and defence. Method: WSNs are vulnerable to various types of attack, upon which black-hole, a type of Denial of Service (DoS) pose enormous challenge in detection and defence. The primary characteristic of the attack is that reprogramming done by attackers in the captured nodes block the packets received than forwarding to the base station. This results in information entering the black hole area not getting routed to the destination and degradation of QoS factors of delay and final throughput. In this study a comparative performance weighing of Star and tree topology setup of WSN nodes is carried out under the black hole scenario. In case, the parameter of delay is vital Mesh setup is chosen and in the requirement of throughput efficiency and fault tolerance Star topology is chosen. A methodology for choosing the topology depending on the required service parameter under black hole scenario is also devised. Findings: The vital parameters considered for the simulation study are delay in transmission of packets and throughput efficiency among the sensor nodes. The results prove a considerable reduction of the parameter of delay in transmission of packets if hybrid topology is followed and a reasonable increase in the QoS parameter of throughput as mesh topology is adopted during transmission in a black hole vulnerable network. Improvements: The vital parameters of negligible delay and throughput efficiency that contribute effective cooperation among the sensor nodes are taken into account while choosing the appropriate topology, and the results show the distribution of the parameter values for the particular topology chosen.

Keywords

Black Hole Attacks, Delay, Denial of Service, Throughput, Topology.

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References


  • Wazid M, Katal A, Sachan RS, Goudar RH, Singh DP. Detection and prevention mechanism for black hole attack in Wireless Sensor Network. International Conference on Communication and Signal Processing; India. 2013 Apr 3-5.
  • Blilat A, Bouayad A, el houda Chaoui N, ElGhazi M. Wireless Sensor Network: Security challenges. IEEE National Days of Network Security and Systems (JNS2; 2012. p. 68–72.
  • Yu YL, Li K, Zhou W, Li P. Trust mechanisms in Wireless Sensor Networks: Attack analysis and q countermeasures. Journal of Network Computer and Applications. Special Issue on Trusted Computing and Communications. Elsevier. 2012 May; 35(3):867–80.
  • Guechari M, Mokdad L, Tan S. Dynamic solution for detecting Denial of Service attacks in Wireless Sensor Networks. IEEE International Conference on Communications (ICC); 2012.
  • Schaffer P, Farkas K, Horvath A, Holczer T, Buttyan L. Survey secure and reliable clustering in Wireless Sensor Networks: A critical survey. Computer Networks: The International Journal of Computer and Telecommunications Networking. ACM; 2012 Jul.
  • Misra S, Bhattarai K, Xue G. BAMBi: Black hole Attacks Mitigation with Multiple Base Stations in Wireless Sensor Networks. IEEE International Conference on Communications (ICC); 2011.
  • Mahmood AR, Aly HH, El-Derini MN. Defending against energy efficient link layer jamming Denial of Service attack in Wireless Sensor Networks. IEEE 9th IEEE/ACS International Conference on Computer Systems and Applications (AICCSA); 2011.
  • Nanda R, Venkata Krishna P. A self enforcing and flexible security protocol for preventing Denial of Service attacks in Wireless Sensor Networks. IEEE Recent Advances in Intelligent Computational Systems (RAICS); 2011.
  • Modares H, Salleh R, Moravejosharieh A. Overview of security issues in Wireless Sensor Networks. 3rd International Conference on Computational Intelligence, Modeling and Simulation (CIMSIM '11), ACM; 2011.
  • Prathapani A, Santhananr L, Agrawal DP. Intelligent honeypot agent for black hole attack detection in Wireless Mesh Networks. IEEE 6th International Conference on Mobile Ad-hoc and Sensor System (MASS); 2009.
  • Tiwari M, Arya KV, Choudhari R, Choudhary. Designing intrusion detection to detect black hole and selective forwarding attack in WSN based on local Information. IEEE 4th International Conference on Computer Sciences and Convergence on Information Technology (ICCIT ); 2009.
  • Gill K, Yang SH. A scheme for preventing denial of service attacks on Wireless Sensor Networks. IEEE 35th Annual Conference of Industrial Electronics, (IECON '09); 2009.
  • Medadian M, Mebadi A, Shahri E. Combat with black hole attack in AODV routing protocol. IEEE 9th Malaysia International Conference on Communications; 2009 Dec 15-17.
  • Raymond DR, Midkiff SF. Denial-of-Service in Wireless Sensor Networks: Attacks and defenses. IEEE Pervasive Computing; 2008. Jan-Mar.
  • Pathan ASK, Lee HW, Hong CS. Security in Wireless Sensor Networks: Issues and challenges. IEEE 8th International Conference on Advanced Communication Technology (ICACT); 2006.
  • Tanveer Z, Zomaya A. Security issues in Wireless Sensor Networks. IEEE International Conference on Systems and Networks Communications (ICSNC); 2006.

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