Trust Based Security Schemes in Mobile Ad Hoc Networks - A Review

Sivagurunathan, S.; Prathapchandran, K.

doi:10.1109/icica.2014.67

Cited by 11 publications

(6 citation statements)

References 18 publications

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“…Once authentication is achieved, remaining security requirements such as confidentiality, integrity and non-reputation [8] can be achieved easily. To achieve authentication, shared secret, Public Key Infrastructure [PKI], digital signature, digital certificate [10] are used but these techniques are centralized, pre-determined and depend on trusted third party, thereby increasing computation power, memory and consumption of communication bandwidth and battery power but MANET has limited resource constrains. To provide security with limited computational capabilities trust comes into existence because it offers less memory overhead, less transmission overhead and less bandwidth consumption [11].…”

Section: Authentication and Trustsmentioning

confidence: 99%

Trusted DSR Routing Protocol to withstand against Gray Hole attack in MANET using Q-Learning

2017

IJMTER

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-Routing is one of the required tasks in MANET to exchange packets among the mobile nodes that is accomplished by routing protocols. Traditionally routing protocols are designed to cope with routing operation but in practice they may be affected by misbehaving nodes in the form of attacks. Gray hole attack is one of the notable attack since they are launched internally and cannot be identified easily. It aims to disrupt the normal routing operation and try to minimize or collapse the overall network performance. Therefore, detecting Gray node and secure routing in MANET environment is always a challenging problem due to its distinct characteristics. In this paper, we have proposed a trusted DSR Routing protocol to detect the Gray hole attack over DSR routing protocol. Here we avoid the Gray hole nodes by calculating an overall trust of each node based on metrics such as direct and indirect trusts. In addition Q-learning algorithm is used to enrich the proposed work by assigning reward. This model is the extension of our earlier work [1] that overcomes the black hole attack over AODV Routing protocol.

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Section: Authentication and Trustsmentioning

confidence: 99%

Trusted DSR Routing Protocol to withstand against Gray Hole attack in MANET using Q-Learning

2017

IJMTER

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“…This is used to enable each node to adjust its route request forwarding rate according to its evaluated trust score. Sivagurunathan S et.al [21], proposed a light weight trust based security model to ensure authentication and detect the malicious nodes. In this model trust calculation is accomplished by combining the responses from its neighbors and depending upon the capacity of their work done, thereby ensures the authentication among the nodes by the way security can be achieved.…”

Section: Related Workmentioning

confidence: 99%

“…Once authentication is achieved, remaining security requirements such as confidentiality, integrity and non-reputation [3] can be achieved easily. To achieve authentication, shared secret, Public Key Infrastructure [PKI], digital signature, digital certificate [5] are used but these techniques are centralized, pre-determined and depend on trusted third party, thereby increasing computation power, memory and consumption of communication bandwidth and battery power but MANET has limited resource constrains. To provide security with limited computational capabilities trust comes into existence because it offers less memory overhead, less transmission overhead and less bandwidth consumption [6].…”

Section: Introductionmentioning

confidence: 99%

Authentication Using Trust to Detect Misbehaving Nodes in Mobile Ad hoc Networks Using Q-Learning

Sivagurunathan¹,

Prathapchandran²,

Thirumavalavan³

2016

IJNSA

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Providing security in Mobile Ad Hoc Network is crucial problem due to its open shared wireless medium, multi-hop and dynamic nature, constrained resources, lack of administration and cooperation. Traditionally routing protocols are designed to cope with routing operation but in practice they may be affected by misbehaving nodes so that they try to disturb the normal routing operations by launching different attacks with the intention to minimize or collapse the overall network performance. Therefore detecting a trusted node means ensuring authentication and securing routing can be expected. In this article we have proposed a Trust and Q-learning based Security (TQS) model to detect the misbehaving nodes over Ad Hoc On Demand Distance-Vector (AODV) routing protocol. Here we avoid the misbehaving nodes by calculating an aggregated reward, based on the Q-learning mechanism by using their historical forwarding and responding behaviour by the way misbehaving nodes can be isolated.

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“…Sivagurunathan S et.al [24], proposed a light weight trust based security model to ensure authentication and detect the malicious nodes. In this model trust calculation is accomplished by combining the responses from its neighbors and depending upon capacity of their work done, thereby ensures the authentication among the nodes by the way security can be achieved.…”

Section: Review Of Literaturementioning

confidence: 99%

“…Once an authentication is achieved, remaining security requirements can be achieved easily. To achieve authentication, shared secret, Public Key Infrastructure [PKI], digital signature, digital certificate [5] [6] are used but these techniques are centralized, pre-determined depend on trusted third party there by increasing computation power, memory and consumption of communication bandwidth and battery power.…”

Section: Introductionmentioning

confidence: 99%

A Light Weight Trust based Authentication Mechanism to thwart Black hole Attack in MANET

P¹,

Selvaraj²

2016

IJMTER

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Providing secure routing in MANET environment is a difficult task due to its distinct nature. In MANET, routing protocols are designed to cope with the network operations but in nature they are affecting by both internal and external attacks. Black hole attack is one kind of internal attack that affects routing operation by retaining all incoming packets. This type of attack is very hard to predict because it is launched internally by compromised nodes. In addition, ensuring authentication is also a difficult task because each node in the MANET is in situation to communicate with other nodes without previous interactions. This blindness in communication leads networks more vulnerable. To tackle such issues in this paper a light weight authentication mechanism to thwart black hole attack is proposed. In this mechanism each node evaluates the trustworthiness of other nodes based on direct and indirect recommendations. In addition, it is also make use of closeness, energy and honesty as trust evaluation metrics. The simulation results show better performance in terms of detection of black hole attack and QoS metrics.

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Trust Based Security Schemes in Mobile Ad Hoc Networks - A Review

Cited by 11 publications

References 18 publications

Trusted DSR Routing Protocol to withstand against Gray Hole attack in MANET using Q-Learning

Trusted DSR Routing Protocol to withstand against Gray Hole attack in MANET using Q-Learning

Authentication Using Trust to Detect Misbehaving Nodes in Mobile Ad hoc Networks Using Q-Learning

A Light Weight Trust based Authentication Mechanism to thwart Black hole Attack in MANET

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