VANET: Security Attacks, Solution and Simulation

Jain, Monika; Saxena, Rahul

doi:10.1007/978-981-10-8228-3_42

Cited by 14 publications

(11 citation statements)

References 6 publications

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“…X and Y in equation (3) represent the random variables, and the entropy of a random variable X is written as H (X).…”

Section: Data Pre-processingmentioning

confidence: 99%

“…The vehicles’ nodes communicate with each other and with the road side units (RSUs) through a communication unit in each vehicle called the on-board unit (OBU), which in turn is connected to the application unit (AU) to provide an application interface. 3 VANET supports both safety and non-safety applications. The main goal of its safety applications is to minimize accidents and improve driving safety by alerting drivers regarding collision avoidance, road sign notifications, and alarms for incident management.…”

Section: Introductionmentioning

confidence: 99%

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A simulation work for generating a novel dataset to detect distributed denial of service attacks on Vehicular Ad hoc NETwork systems

Alhaidari

Alrehan

2021

International Journal of Distributed Sensor Networks

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Vehicular Ad hoc NETwork is a promising technology providing important facilities for modern transportation systems. It has garnered much interest from researchers studying the mitigation of attacks including distributed denial of service attacks. Machine learning techniques, which mainly rely on the quality of the datasets used, play a role in detecting many attacks with a high level of accuracy. We conducted a comprehensive literature review and found many limitations on the datasets available for distributed denial of service attacks on Vehicular Ad hoc NETwork including the following: unavailability of online versions, an absence of distributed denial of service traffic, unrepresentative of Vehicular Ad hoc NETwork, and no information regarding the network configurations. Therefore, in this article, we proposed a novel simulation technique to generate a valid dataset called Vehicular Ad hoc NETwork distributed denial of service dataset, which is dedicated to Vehicular Ad hoc NETworks. Vehicular Ad hoc NETwork distributed denial of service dataset holds information on distributed denial of service attack traffic considering Vehicular Ad hoc NETwork architecture, traffic density, attack intensity, and nodes mobility. Well-known simulation tools such as SUMO, OMNeT++, Veins, and INET were used to ensure that all the properties of Vehicular Ad hoc NETwork have been captured. We then compared Vehicular Ad hoc NETwork distributed denial of service dataset with several studies to prove its novelty and evaluated the dataset using several machine learning models. We confirmed that studied models using this dataset achieved high accuracy above 99.5% except support-vector machine that achieved 97.3%.

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“…X and Y in equation (3) represent the random variables, and the entropy of a random variable X is written as H (X).…”

Section: Data Pre-processingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A simulation work for generating a novel dataset to detect distributed denial of service attacks on Vehicular Ad hoc NETwork systems

Alhaidari

Alrehan

2021

International Journal of Distributed Sensor Networks

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“…Vehicle Ad-hoc Networks (VANETs) make use of a number of wireless inter-vehicle networking, such as dedicated short range communications (DSRCs), long-term evolutionary vehicle (LTE-V), and Worldwide Interoperability for Microwave Access (WiMAX) [34]. With the increasing movement toward vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-third-party devices (V2X) communication [36,37], security and privacy challenges correspondingly increase [34,38].…”

Section: Automotive Communicationmentioning

confidence: 99%

“…Through a vehicle's telematics system, such as General Motors' OnStar® or Hyundai's Blue Link®, "white hat hackers" 2 have shown the ability to attack using only an Internet connection [41]. With more outward-facing communication (e.g., V2V, V2I, and V2X), there is increasing risk for malicious actors to inject malware through VANETs [37,38,42,43].…”

Section: Degree Of Accessmentioning

confidence: 99%

Security Patterns for Connected and Automated Automotive Systems†

Cheng¹,

Doherty²,

Polanco³

et al. 2020

JASEN

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As automotive systems become increasingly sophisticated with numerous onboard features that support extensive inward and outward-facing communication, cybersecurity vulnerabilities are exposed. The relatively recent acknowledgement of automotive cybersecurity challenges has prompted numerous research efforts into developing techniques to handle individual threat vectors, the pathways and threat surfaces by which an attack can be realized. Security design patterns have been developed for many application domains (e.g., enterprise systems, networking systems, and distributed systems), but not much has been explored for automotive systems. This paper introduces a collection of security design patterns targeted for automotive cybersecurity needs. We leverage and extend the de facto standard template used to describe design patterns to include fields specific to the automotive domain and SAE J3061 cybersecurity development guidelines.

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“…Due to the opening wireless channel, VANETs faces various attacks (eg, the message replay attack, the denial of service attack, the tracing attacks etc [8][9][10] ) which make it urgent to verify the vehicles validity and messages integrity. On account of the messages complexity, it is also vital to increase the processing speed of RSUs.…”

Section: F I G U R Ementioning

confidence: 99%

An efficient blockchain‐based batch verification scheme for vehicular ad hoc networks

Yang

Wang

et al. 2019

Trans Emerging Tel Tech

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As an important branch of the Internet of Things (IoT), Vehicular Ad Hoc Networks (VANETs) have attracted wide attention from industrial and academic. Due to an opening wireless channel, the security and efficiency of VANETs have also become serious. To enhance the security and efficiency, various batch verification schemes have been proposed. However, most of those schemes suffer from the complicated certificate management problem or different kinds of attacks. Also,the bilinear pairing which is intractable for lightweight devices in VANETs usually be used inthose schemes. To solve the above problems, we propose an efficient blockchain‐based batch verification scheme for VANETs using the Elliptic Curve Cryptography (ECC). We also provide security analysis to show its ability to resist current known attacks. Besides, we have implemented corresponding blockchain system and the performance analysis shows that it is suitable for VANETs.

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VANET: Security Attacks, Solution and Simulation

Cited by 14 publications

References 6 publications

A simulation work for generating a novel dataset to detect distributed denial of service attacks on Vehicular Ad hoc NETwork systems

A simulation work for generating a novel dataset to detect distributed denial of service attacks on Vehicular Ad hoc NETwork systems

Security Patterns for Connected and Automated Automotive Systems†

An efficient blockchain‐based batch verification scheme for vehicular ad hoc networks

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