A Misbehavior-Based Reputation Management System for VANETs

Kim, Chil-Hwa; Bae, Ihn-Han

doi:10.1007/978-94-007-5076-0_54

Cited by 19 publications

(14 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…They have considered the possibility of the fake position information of the vehicle in the PCN along with the false crash alert in 10 . Kim et al 6 have proposed a novel Misbehavior Based Reputation Management Scheme (MBRMS) which includes three components a) Misbehavior detection b) Event rebroadcast and c) Global eviction algorithms for the detection and filtration of false information in vehicular ad-hoc networks. Daeinabi et al 3 have proposed a detection algorithm called DMV to discover malicious nodes through observations that duplicates or drops received packets and isolates such vehicles from honest nodes.…”

Section: Node Centric Misbehavior Detection Schemesmentioning

confidence: 99%

Detection of Malicious Nodes (DMN) in Vehicular Ad-Hoc Networks

Khan

Agrawal

Silakari

2015

Procedia Computer Science

108

View full text Add to dashboard Cite

VANETs enable wireless communication among vehicles and vehicle to infrastructure. Its main objective is to render safety, comfort and convenience on the road. VANET is different from ad-hoc networks due to its unique characteristics. However, because of lack of infrastructure and centralized administration, it becomes vulnerable to misbehaviors. This greatly threatens ing such a useful network must provide adequate security measures for secure communication. The proposed algorithm DMN-Detection of Malicious Nodes in VANETs improves DMV Algorithm in terms of effective selection of verifiers for detection of malicious nodes and hence improves the network performance.

show abstract

Section: Node Centric Misbehavior Detection Schemesmentioning

confidence: 99%

Detection of Malicious Nodes (DMN) in Vehicular Ad-Hoc Networks

Khan

Agrawal

Silakari

2015

Procedia Computer Science

108

View full text Add to dashboard Cite

show abstract

“…Kim and bae [7] have advised a unique wrongdoing based mostly name management theme (MBRMS). It contains the 3 elements (a) wrongdoing detection (b) event transmit (c) international eviction algorithms to find and filter the false data within the transport networks.…”

Section: Ghoshm[6]mentioning

confidence: 99%

“…Of attacks like part, timing, illusion, DOS [10], Sybil that not solely influences the vehicles and deriver's privacy however additionally affects the traffic safety [1][13]. In some cases, it's going to ends up in loss of life to confirm the traffic safety the VANET wants some appropriate security techniques that may assure protection across distinct misbehaviours and malicious nodes that influence the protection of the VANET [5] [7].…”

Section: Introductionmentioning

confidence: 99%

A Robust Security Algorithm for VANETs

Kaur¹,

Grover²

2016

IJCA

View full text Add to dashboard Cite

The VANETs carry several security considerations. One in every of the popular and dangerous attacks is launched within the variety of Sybil, connectivity holes or cut-up attack, wherever associated in Nursing assaulter inserts a faux position inside within the cluster. The inserted faux node data is used by the hackers within the case of inconsiderate driver, traffic jams, selective collisions and different similar dangerous things. To avoid such things the VANETs should be protected against such attacks. During this paper, a completely unique answer has been projected to beat the Sybil and cut-up attacks on the VANETs. The new answer is capable of police work the faux data injections by confirmatory the VANET node behavior within the cluster. The behavior of the node includes the direction, speed and pattern. The projected model has been developed mistreatment the random waypoint model. The random waypoint model has been compared against the point of reference cluster model. The experimental results have shown the effectiveness of the projected model and also shows that RWPM is better than RPGM.

show abstract

“…For example, if the rate at which a node sends packets exceeds a normal (predefined-historical) one, it is characterized as a misbehaving vehicle [15]. Other mechanisms in the same category include some form of reputation management, which inspects the past and present behavior of a node to derive the probability of future misbehaviour, as implemented in [19].…”

Section: Related Workmentioning

confidence: 99%

A Robust Eco-Routing Protocol against Malicious Data in Vehicular Networks

Basaras

Μαγλαράς

Katsaros

et al. 2015

2015 8th IFIP Wireless and Mobile Networking Conference (WMNC)

View full text Add to dashboard Cite

Vehicular networks have a diverse range of applications that vary from safety, to traffic management and comfort. Vehicular communications (VC) can assist in the ecorouting of vehicles in order to reduce the overall mileage and CO2 emissions by the exchange of data among vehicle-entities. However, the trustworthiness of these data is crucial as false information can heavily affect the performance of applications. Hence, the devising of mechanisms that reassure the integrity of the exchanged data is of utmost importance. In this article we investigate how tweaked information originating from malicious nodes can affect the performance of a real time eco routing mechanism that uses DSRC communications, namely ErouVe. We also develop and evaluate defense mechanisms that exploit vehicular communications in order to filter out tweaked data. We prove that our proposed mechanisms can restore the performance of the ErouVe to near its optimal operation and can be used as a basis for protecting other similar traffic management systems.

show abstract

A Misbehavior-Based Reputation Management System for VANETs

Cited by 19 publications

References 6 publications

Detection of Malicious Nodes (DMN) in Vehicular Ad-Hoc Networks

Detection of Malicious Nodes (DMN) in Vehicular Ad-Hoc Networks

A Robust Security Algorithm for VANETs

A Robust Eco-Routing Protocol against Malicious Data in Vehicular Networks

Contact Info

Product

Resources

About