A Composite Trust Model for Secure Routing in Mobile Ad-Hoc Networks

Jhaveri, Rutvij H.; Patel, Neelam; Jinwala, Devesh C.

doi:10.5772/66519

Cited by 10 publications

(8 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In IDS, several approaches are proposed such as packet payload analysis [23], pattern propagation [24] and bro language [25]. In addition, various schemes for ad-hoc networks are proposed to detect attack patterns and to provide a defense mechanism in the network [26][27][28][29][30]. IDS which are passive by nature have a key issue their inability to mount targeted, reliable and adaptive response [31].…”

Section: Intrusion Detection and Preventionmentioning

confidence: 99%

Applications in Security and Evasions in Machine Learning: A Survey

2020

View full text Add to dashboard Cite

In recent years, machine learning (ML) has become an important part to yield security and privacy in various applications. ML is used to address serious issues such as real-time attack detection, data leakage vulnerability assessments and many more. ML extensively supports the demanding requirements of the current scenario of security and privacy across a range of areas such as real-time decision-making, big data processing, reduced cycle time for learning, cost-efficiency and error-free processing. Therefore, in this paper, we review the state of the art approaches where ML is applicable more effectively to fulfill current real-world requirements in security. We examine different security applications’ perspectives where ML models play an essential role and compare, with different possible dimensions, their accuracy results. By analyzing ML algorithms in security application it provides a blueprint for an interdisciplinary research area. Even with the use of current sophisticated technology and tools, attackers can evade the ML models by committing adversarial attacks. Therefore, requirements rise to assess the vulnerability in the ML models to cope up with the adversarial attacks at the time of development. Accordingly, as a supplement to this point, we also analyze the different types of adversarial attacks on the ML models. To give proper visualization of security properties, we have represented the threat model and defense strategies against adversarial attack methods. Moreover, we illustrate the adversarial attacks based on the attackers’ knowledge about the model and addressed the point of the model at which possible attacks may be committed. Finally, we also investigate different types of properties of the adversarial attacks.

show abstract

Section: Intrusion Detection and Preventionmentioning

confidence: 99%

Applications in Security and Evasions in Machine Learning: A Survey

2020

View full text Add to dashboard Cite

show abstract

“…Jhaveri et al proposed a composite trust model which utilized both social and QoS trust components [11] to estimate the trust degree of nodes in which the ditch ratio was used as a social trust component. This ditch ratio parameter is valuable for knowing the behavior of nodes and to identify malicious nodes.…”

Section: Related Workmentioning

confidence: 99%

“…There have already been some proposals for securing the process of routing in MANETs. Although cryptographic techniques have been widely used in routing to protect routing information from being tinkered by the adversary, such an approach may not be practical for real MANETs due to heavy computational overhead and lack of capability of spotting attacking nodes given the high mobility of MANETs where nodes continuously join and leave the networks [11]. Introducing "trust" into such a hostile environment can help nodes observe and predict the behavior of neighboring nodes in an efficient manner.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Trust-Based Scheme for Secure and Quality of Service Routing in MANETs

Pathan

Zhu

et al. 2018

Future Internet

View full text Add to dashboard Cite

Due to the dynamism of topology, sharing of bandwidth and constraint of resources in wireless nodes, the provision of quality of service (QoS) for routing in mobile ad hoc networks (MANETs) presents a great challenge. Security is another crucial aspect of providing QoS since the existence of malicious nodes present all kinds of threats to MANETs. Although a number of mechanisms have been proposed for protecting MANETs, most of the solutions are only effective for a particular kind of attacks or provide security at the cost of sacrificing QoS. In this paper, we propose a trust-based secure QoS routing scheme by combining social and QoS trust. The primary approach of the proposed scheme relies on mitigating nodes that exhibit various packet forwarding misbehavior and on discovering the path that ensures reliable communication through the trust mechanism. The scheme would select the best forwarding node based on packet forwarding behavior as well as capability in terms of QoS parameters, such as residual energy, channel quality, link quality, etc. We will present an adversary model for packet dropping attack against which we evaluate the proposed scheme. Simulation experiment using Network Simulator-2 (NS2) and under various network conditions show that mixing social and QoS trust parameters can greatly improve security and quality of service routing in terms of overhead, packet delivery ratio and energy consumption.

show abstract

“…Inspired by these works, a lot of researchers have devoted their efforts to exploring the security issues in large-scale wireless networks. For instance, the secure routing protocols were investigated in [14][15][16], the design of effective physical layer authentication schemes was analysed in [17][18][19], the security performances in terms of secrecy throughput capacity and eavesdropper-tolerance capability were explored in [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Secrecy transmission capacity in mobile ad hoc networks with security‐aware Aloha protocol

Li¹,

Zhang

Shen

et al. 2020

IET Communications

View full text Add to dashboard Cite

Mobile ad hoc networks (MANETs) represent a class of important network models for supporting various critical applications, while the security breach due to eavesdropping attacks has been a critical issue. This study investigates the security issue of MANETs from the perspective of physical layer security (PLS). In particular, by combining PLS techniques [e.g. artificial noise (AN) injection and Secrecy Guard zoNe (SGN)] and the conventional Aloha protocol, the authors first propose an AN-based Aloha protocol and a SGN-based Aloha protocol to ensure secure medium access for legitimate transmitters. In the AN-based Aloha protocol, all potential transmitters are allowed to be active and each active transmitter injects AN into its transmitted signals to confuse eavesdroppers. In the SGN-based protocol, each potential transmitter has an SGN, a circle centred at itself, and only the potential transmitters whose SGN contains no eavesdroppers are allowed to be active. To understand the security performances of the proposed security-aware Aloha protocols, the authors then apply tools from Stochastic Geometry to analyse the secrecy transmission capacity (STC) performances of MANETs under both protocols. Finally, the authors provide simulation/numerical results to corroborate the proposed theoretical analysis and also to show the impacts of network parameters on the STC performances.

show abstract

A Composite Trust Model for Secure Routing in Mobile Ad-Hoc Networks

Cited by 10 publications

References 20 publications

Applications in Security and Evasions in Machine Learning: A Survey

Applications in Security and Evasions in Machine Learning: A Survey

An Efficient Trust-Based Scheme for Secure and Quality of Service Routing in MANETs

Secrecy transmission capacity in mobile ad hoc networks with security‐aware Aloha protocol

Contact Info

Product

Resources

About