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A Framework for Detecting Malicious Nodes in Mobile Adhoc Network


  • VIT University, Vellore, India
  • SCSE, VIT University, Vellore


A wireless network consists of nodes which cooperate with each other for transmission. In adhoc network the nodes are mobile forming temporary network dynamically. These networks don't provide special security mechanics where attacks are highly possible through malicious nodes. Malicious nodes don't cooperate with other nodes and acts selfishly by reserving the resources for its own use. This decreases the performance of the routing protocol in the network. In order to increase the performance of the routing the malicious nodes has to be detected and that route has to be prevented from routing. In the previous paper the malicious nodes are just simulated and analyzed. In this paper the malicious nodes are detected in prior to the routing using consensus based algorithm and then that route is prevented for transmitting data between nodes in mobile adhoc networks.


Consensus Based Algorithm, Malicious Nodes, MANET, NS2, Security.

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  • Dawood MZ, Zaman N, Khan AR, Salih M. Designing of energy efficient routing protocol for Wireless Sensor Network (WSN) Using Location Aware (LA) Algorithm. Journal of Information & Communication Technology. 2009; 3(2):56-70.
  • Ivanovitch MD, Silva, Guedes LA, Vasques F. Performance evaluation of a compression algorithm for wireless sensor networks in monitoring applications.
  • Nidharshini T, Janani V. Detection of duplicate nodes in wireless sensor networks using sequential probability ratio testing. International Journal of Advanced Research in Computer and Communication Engineering. 2012 Dec; 1(10):794-8.
  • Hariharan S, Precia J, Suriyakala CD, Shyry P. A Novel approach for detection of routes with misbehaving nodes in MANETs. ACEEE Int J on Network Security. 2011 Jan; 02(01):32-34.
  • Khedo KK, Perseedoss R and Mungur A. A wireless sensor network air pollution monitoring system. IJWMN. 2010 May; 2:31-45.
  • Sen J. A distributed trust management framework for detecting malicious packet dropping nodes in a mobile Ad Hoc network. IJNSA. 2010 Oct; 2(4):92-104.
  • Sen J, Chandra MG, Balamuralidhar P, Harihara SG, Reddy H. A distributed protocol for detection of packet dropping attack in mobile Ad Hoc networks.
  • Rathna R and Subramanian SA. Improving energy efficiency in wireless sensor networks through scheduling and routing. IJASSN. 2012 Jan; 2(1):21-7.
  • Silva IMD, Guedes LA, Vasques F. Performance Evaluation of a Compression Algorithm for Wireless Sensor Networks in Monitoring Applications. p. 672-8.
  • Gopal R, Parthasarathy V, Mani A. Techniques to identify and eliminate malicious nodes in cooperative wireless networks. 2013 International Conference on Computer Communication and Informatics (ICCCI -2013); 2013 Jan 09-11; Coimbatore, India.
  • Perkins CE, Royer EM. Adhoc-On Demand Distance Vector.
  • Khandakar A. Step by Step Procedural Comparison of DSR, AODV and DSDV Routing protocol. 2012 4th International Conference on Computer Engineering and Technology (ICCET 2012); 2012; Singapore. IACSIT Press.
  • Lokanath S, Thayur A. Implementation of AODV Protocol and Detection of Malicious Nodes in MANETs.
  • Cheng P, Chuah C-N, Liu X. Energy-aware node placement in wireless sensor networks.
  • Yu FR, Huang M, Tang H. Biologically Inspired Consensus-Based Spectrum Sensing in Mobile Ad Hoc Networks with Cognitive Radios. p. 26-30.
  • Khandelwal V, Goyal D. Black hole attack and detection method for aodv routing protocol in MANETs. IJARCET. 2013 Apr; 2(4):1555-9.
  • Rajaram A, Palaniswami S. Malicious node detection system for mobile adhoc networks. IJCSIT. 2010; 1(2):77-85.
  • Kaur J, Kumar V. An effectual defense method against gray hole attack in wireless sensor networks. IJCSIT. 2012; 3(3):4523-8.
  • Wadbude D, Richariya V. An efficient secure AODV routing protocol in MANET. IJEIT. 2012 Apr; 1(4):274-9.
  • Rathod P, Mody N, Gada D, Gogri R, Dedhia Z, Sanyal S, Abraham A. Security scheme for malicious node detection in mobile Ad Hoc networks.
  • Mathioudakis I, White NM, Harris NR, Merrett GV. Wireless sensor networks: a case study for energy efficient environmental monitoring.
  • Khetmal C, Kelkar S, Bhosale N. MANET: black hole node detection in AODV. International Journal of Computational Engineering Research. 2013; 03(6):79-85.
  • Manoj V, Raghavendiran N, Aaqib MM, Vijayan R. An approach for detection of malicious node using fuzzy based trust levels in manet. Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief; 2001. p. 447-80.
  • Kumar V, Sharma R, Kush A. Effect of malicious nodes on AODV in mobile Ad Hoc networks. International Journal of Computer Science and Management Research. 2012 Oct: 1(3):395-8.
  • Boukerche A, Araujo RB, Pazzi RWN. A fast and reliable protocol for wireless sensor networks in critical conditions monitoring applications. 157-64.
  • Priyambadasahu, Bisoy SK, Sahoo S. Detecting and isolating malicious node in AODV routing algorithm. International Journal of Computer Applications. 2013; 66(16):8-12.
  • Thakare AN, Joshi MY. Performance analysis of AODV & DSR routing protocol in mobile Ad hoc networks. IJCA Special Issue on Mobile Ad-hoc Networks MANETs. 2010; 4:211-8.
  • Khalil I, Bagchi S, Rotaru CN, Shroff N. UNMASK: Utilizing Neighbor Monitoring for Attack Mitigation in MultihopWireless Sensor Networks.
  • Ramzan Z, Seshadri V and Nachenberg C. Reputation-based security an analysis of real world effectiveness.
  • A survey of Reputation Based Schemes for MANET Abbas S, Merabti M and Llewellyn-Jones D. A survey of Reputation Based Schemes for MANET.
  • Abrams Z, McGrew R and Plotkin S. A non-Manipulable Trust System Based on Eigen Trust. 2005, Jul; 5(4):21-30.
  • Dehnie, Wayne and Tomasin. Detection of selfish nodes in networks using CoopMAC protocol with ARQ. Wireless Communications IEEE Transactions. 2010 Jun; 9:2328-37.
  • Marks M. A Survey of Multi-Objective Deployment in Wireless Sensor Networks.


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