Collaborative trust aware intelligent intrusion detection in VANETs

Trust aware Collaborative Learning Automata based Intrusion Detection System (T-CLAIDS) for VANETs is proposed in this paper. Learning Automata (LA) are assumed to be deployed on vehicles in the network to capture the information about the different states of the vehicles on the road. A Markov Chain Model (MCM) is constructed for representation of states and their transitions in the network. Transitions from one state to other are dependent upon the density of the vehicles in a particular region. A new classifier is designed for detection of any malicious activity in the network and is tuned based upon the new parameter called as Collaborative Trust Index (CTI) so that it covers all possible types of attacks in the network. An algorithm for detection of abnormal events using the defined classifier is also proposed. The results obtained show that T-CLAIDS performs better than the other existing schemes with respect to parameters such as false alarm ratio, detection ratio and overhead generated.

[1]  M. Zolghadri Jahromi,et al.  A cost sensitive learning algorithm for intrusion detection , 2010, 2010 18th Iranian Conference on Electrical Engineering.

[2]  Jongsung Kim,et al.  ELACCA: Efficient Learning Automata Based Cell Clustering Algorithm for Wireless Sensor Networks , 2013, Wirel. Pers. Commun..

[3]  António Fonseca,et al.  Applicability of position-based routing for VANET in highways and urban environment , 2013, J. Netw. Comput. Appl..

[4]  Dharma P. Agrawal,et al.  SVM-based intrusion detection system for wireless ad hoc networks , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[5]  Naveen K. Chilamkurti,et al.  Learning Automata-based Opportunistic Data Aggregation and Forwarding scheme for alert generation in Vehicular Ad Hoc Networks , 2014, Comput. Commun..

[6]  Nai-Wei Lo,et al.  A Reputation System for Traffic Safety Event on Vehicular Ad Hoc Networks , 2009, EURASIP J. Wirel. Commun. Netw..

[7]  K.D. Wong,et al.  Handling the inter-vehicular communications challenge - a survey , 2004, The Ninth International Conference onCommunications Systems, 2004. ICCS 2004..

[8]  Ajith Abraham,et al.  Modeling intrusion detection system using hybrid intelligent systems , 2007, J. Netw. Comput. Appl..

[9]  Muhammad Usman,et al.  Mobile Agent Based Hierarchical Intrusion Detection System in Wireless Sensor Networks , 2012 .

[10]  Salvatore J. Stolfo,et al.  Toward Cost-Sensitive Modeling for Intrusion Detection and Response , 2002, J. Comput. Secur..

[11]  Christos Xenakis,et al.  A comparative evaluation of intrusion detection architectures for mobile ad hoc networks , 2011, Comput. Secur..

[12]  Jong Hyuk Park,et al.  ALCA: agent learning–based clustering algorithm in vehicular ad hoc networks , 2012, Personal and Ubiquitous Computing.

[13]  Pascal Bouvry,et al.  Information dissemination in VANETs based upon a tree topology , 2012, Ad Hoc Networks.

[14]  Christos Dimitrakakis,et al.  Intrusion detection in MANET using classification algorithms: The effects of cost and model selection , 2013, Ad Hoc Networks.

[15]  Sugata Sanyal,et al.  Adaptive neuro-fuzzy intrusion detection systems , 2004, International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004..

[16]  Bu-Sung Lee,et al.  A-STAR: A Mobile Ad Hoc Routing Strategy for Metropolis Vehicular Communications , 2004, NETWORKING.

[17]  Christian Bonnet,et al.  VanetMobiSim: generating realistic mobility patterns for VANETs , 2006, VANET '06.

[18]  Nasser Yazdani,et al.  Mutual information-based feature selection for intrusion detection systems , 2011, J. Netw. Comput. Appl..

[19]  Yang Li,et al.  MAC layer anomaly detection in ad hoc networks , 2005, Proceedings from the Sixth Annual IEEE SMC Information Assurance Workshop.

[20]  Panagiotis Papadimitratos,et al.  On Data-Centric Trust Establishment in Ephemeral Ad Hoc Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[21]  William H. Robinson,et al.  A distributed intrusion detection system for resource-constrained devices in ad-hoc networks , 2010, Ad Hoc Networks.

[22]  Vivek Tiwari,et al.  Lacas: learning automata-based congestion avoidance scheme for healthcare wireless sensor networks , 2009, IEEE Journal on Selected Areas in Communications.

[23]  Wenke Lee,et al.  A cooperative intrusion detection system for ad hoc networks , 2003, SASN '03.

[24]  Farhan Abdel Fattah,et al.  Dynamic Intrusion Detection Method for Mobile Ad Hoc Network Using CPDOD Algorithm , 2010 .

[25]  Steven Furnell,et al.  Friend-assisted intrusion detection and response mechanisms for mobile ad hoc networks , 2008, Ad Hoc Networks.

[26]  Félix Gómez Mármol,et al.  TRIP, a trust and reputation infrastructure-based proposal for vehicular ad hoc networks , 2012, J. Netw. Comput. Appl..