Detecting sybil attacks in vehicular ad hoc networks using fuzzy logic and arithmetic optimization algorithm

Maleknasab, Mehdi; Tabarzad, Mohammad Ali; Shayegan, Mohammad Amin

doi:10.1007/s11227-022-04526-z

Cited by 18 publications

(5 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Maleknasab et al 15 proposed a solution based on fuzzy logic and a multi‐layer technique that can be used in roadside devices unit (RSUs). When implementing this strategy, two fuzzy logic controllers (FLCs) are used.…”

Section: Related Workmentioning

confidence: 99%

Developing an optimized routing protocol with rumor riding technique for detection of Sybil attack in VANET environment

Navinkumar,

Somasundaram

2024

Int J Communication

View full text Add to dashboard Cite

SummaryAn attack on VANET known as a Sybil attack involves the attacker claiming or stealing multiple identities with the intent of causing havoc on the network's operation by disseminating false information. To protect the VANET network from Sybil attack, a variety of methods have been proposed. In order to compensate for the Sybil attack on VANETs, a rumor riding with salp swarm optimization (SSO) based Routing protocol is developed in this research work. The primary goal of this investigation is to discover how VANETs are vulnerable to the Sybil attack in order to improve their security. Rumor riding will be used to identify the Sybil attack in the suggested strategy. VANETs are protected by the Blowfish Algorithm, which uses SSO to select the best key for each network. The collective intelligence and dynamic adaptation of SALP swarm optimization algorithm enable efficient identification of rumor sources in complex networks. The algorithm is scalable, flexible, and adept at reducing false positives and negatives, making it suitable for large‐scale monitoring. Its parallel processing capabilities and robustness ensure rapid and reliable detection. Using the NS2 platform, the proposed method is compared to existing benchmark in terms of delay, packet delivery ratio (PDR), packet loss, throughput, and attack detection rate. The proposed SSO has reduced the packet loss by nearly 5% and delay by nearly 7%, when compared with existing techniques. The delivery ratio of packet for proposed model is increased up to 8% of PDR, when compared with ACO, PSO, and FA. According to this evidence, it is clear that the proposed SSO outperformed existing approaches in a variety of performance metrics.

show abstract

Section: Related Workmentioning

confidence: 99%

Developing an optimized routing protocol with rumor riding technique for detection of Sybil attack in VANET environment

Navinkumar,

Somasundaram

2024

Int J Communication

View full text Add to dashboard Cite

show abstract

“…) 2) Linear Activation Function: The linear activation function utilizes leaky rectified linear activation as described in (5) for both the final layer as well as other layers.…”

Section: P R(classmentioning

confidence: 99%

A Smart Service Model for Smart City: A Context-Based IoT Enabled Deep Learning Approach for Intelligent Transportation System

Reddy

Goswami

Roy

2023

Preprint

View full text Add to dashboard Cite

Transportation is considered the fundamental pillarof economic growth in any society. Still, inherent issues likeaccidents, higher fuel consumption, and pollution have pavedthe way for the rise of the intelligent transportation system(ITS), which enables safety and improvement in the existingtransportation system. ITS helps the massive collection of datafrom multiple sources, and this big data needs immediate processing for ascertaining the events. However, prediction accuracycontinues to be low because of the trade-off of accuracy with theimmediate detection of an event, and this limits the performanceof ITS. This paper addresses this issue by proposing a novel IoT-enabled distributed context-aware Fog-cloud architecture, whichimproves the prediction accuracy by utilizing a hybrid CNN(Convolutional Neural Network) deep learning (DL) approach.Each vehicle in the system only has a track of the local knowledge.The nearby fog nodes are enabled to know the global eventsthrough incremental federated learning, which gets updatedcontinuously back and forth with fog and cloud. Experimentsdemonstrated in the paper clearly show that the modified versionof VGGNet for the CNN model outperforms RGB images,delivering an accuracy of more than 95%, which is 3% moreaccurate than the LeNet while using RGB images as input

show abstract

“…Compromised Safety Applications: Safety-related applications, such as collision avoidance systems, can be compromised if Sybil attackers inject false data, leading to incorrect decisions by vehicles. Detecting Sybil attacks is challenging due to the dynamic nature of VANETs and the need for real-time decision-making [167], [168]. Traditional security mechanisms, such as cryptographic solutions, may be insufficient, and additional trust models or reputation systems are required for effective [169] detection.…”

Section: Figure 9 Sybil Attackersmentioning

confidence: 99%

Privacy and security issues surrounding vehicular Adhoc networks

Emmanuel Asituha

2023

World J. Adv. Res. Rev.

View full text Add to dashboard Cite

Vehicular Ad-Hoc Networks (VANETs) is a type of mobile ad hoc network (MANET) specifically designed for communication among vehicles on the road. VANETs enable vehicles to communicate with each other and with roadside infrastructure, forming a dynamic and self-organizing network without the need for a fixed communication infrastructure. Security concerns in VANETs encompass a range of threats, including Authentication and Authorization attacks, Sybil attacks, Denial-of-Service incidents, Location spoofing, and Eavesdropping. Privacy, on the other hand, is a paramount concern in VANETs due to the sensitive nature of location-based data, Identity Disclosure, and user consent Control. The paper emphasizes the necessity for robust security mechanisms and outlines specific requirements for safeguarding VANETs. Proposed mitigation measures, including cryptographic techniques and authentication mechanisms, are critically assessed for their effectiveness and feasibility. The findings provide a comprehensive understanding of the complexities surrounding privacy and security in VANETs, contributing valuable insights for the development of resilient and privacy-preserving vehicular communication systems.

show abstract

Detecting sybil attacks in vehicular ad hoc networks using fuzzy logic and arithmetic optimization algorithm

Cited by 18 publications

References 54 publications

Developing an optimized routing protocol with rumor riding technique for detection of Sybil attack in VANET environment

Developing an optimized routing protocol with rumor riding technique for detection of Sybil attack in VANET environment

A Smart Service Model for Smart City: A Context-Based IoT Enabled Deep Learning Approach for Intelligent Transportation System

Privacy and security issues surrounding vehicular Adhoc networks

Contact Info

Product

Resources

About