Issues, Challenges, and Research Opportunities in Intelligent Transport System for Security and Privacy

Ali, Qazi Ejaz; Ahmad, Naveed; Malik, Abdul Haseeb; Ali, G. G. Md. Nawaz; Rehman, Waheed Ur

doi:10.3390/app8101964

Cited by 40 publications

(24 citation statements)

References 101 publications

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“…Due to the sensitivity of the information involved in VANET, a safe and reliable environment is essential [12]. However, because of its poor defense capabilities against various attacks (such as man-in-the-middle attacks, Sybil attacks, black hole attacks, or denial of service attacks), ensuring the security of VANET is very challenging [13,14]. In recent years, the trust model has been introduced as an effective security technology into the trusted environment for message propagation between vehicles.…”

Section: Related Work a Trust Modelmentioning

confidence: 99%

Trusted Opportunistic Routing Based on Node Trust Model

Huan

2020

IEEE Access

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In vehicular ad hoc networks, opportunistic routing can effectively improve the reliability and throughput. However, opportunistic routing also has security issues. For example, malicious nodes can easily mix into node candidate sets, which can interfere with network performance. In this paper, a trust model based on node behavior is proposed for solving the problem of malicious nodes in the opportunistic routing and forwarding candidate set. The proposed trust model uses pruning and filtering mechanisms to remove malicious suggestions,and uses dynamic weight calculation methods to combine direct trust and indirect trust when calculating the comprehensive trust value, which can screen and filter low-trust nodes in the network. Then, combining the ETX (Expected Transmission Count) value and the node trust value, an opportunity routing algorithm based on trust model (BTOR) is proposed. Extensive simulation results represent that the algorithm can significantly improve the network performance and reduce the interference of malicious nodes to the network system.

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Section: Related Work a Trust Modelmentioning

confidence: 99%

Trusted Opportunistic Routing Based on Node Trust Model

Huan

2020

IEEE Access

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“…This is done to reduce system downtime. So, the migration decision problem is formulated as maximizing the fitness function F k described in (1). The fitness function is modeled by considering several QoS objectives, where AV j denotes the availability of jth PH, C j denotes the estimated connection time of the jth PM, SL k denotes the service latency between the VM k and PH j, Dmig k s, denotes the migration delay between source PH s and the destination PH j All these QoS-based objectives are mathematically estimated in Section 5.…”

Section: Description Of the Problemmentioning

confidence: 99%

“…The fast convolution of vehicular network with intelligent transport system (ITS) has introduced smart vehicles and roadside units (RSUs), which contains various sensors and actuators. 1 These sensors and actuators help the on-road vehicles, and the RSUs to collect various sensitive data and communicate among themselves, for executing various intelligent transport applications, such as road safety, traffic management, and infotainment applications. Vehicles perform two types of communications, namely, vehicle-to-vehicle (V2V), where vehicles communicate among themselves, and vehicle-to-infrastructure (V2I), where vehicles communicate with the RSUs.…”

Section: Introductionmentioning

confidence: 99%

An adaptive resource placement policy by optimizing live VM migration for ITS applications in vehicular cloud network

Midya

Roy

Majumder

et al. 2019

Trans Emerging Tel Tech

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Vehicular cloud computing (VCC) is a promising approach that uses cloud computing techniques in vehicular environment to execute smart applications. Vehicular environment is characterized by high mobility. This requires the services executed by a vehicular resource in a vehicular cloud to be migrated before it leaves a network. Migration is also required when a service‐requesting vehicle has to leave a network before its request is executed. Moreover, to balance the network load, virtual machine (VM) migration is desired as, at times, a single physical host may become overloaded. In this work, we propose an adaptive resource placement policy by optimizing live VM migration process in vehicular cloud network. The Pareto optimal mapping of migrating VMs to a physical host is carried out using a hybrid optimized algorithm, which is the combination of particle swarm optimization and genetic algorithm. The optimization is done by maximizing a fitness function that is developed by considering significant quality‐of‐service (QoS) parameters, such as network latency, migration delay, power consumption, and vehicular mobility. These QoS parameters are mathematically formulated in view of a vehicular network. The proposed algorithm reduces migration latency, transmission latency, and service delay. It also distributes the load among the available physical hosts within a cloud system, thus reducing the average wait time for each cloud user. Simulation results exhibit significant decrease in waiting time, service delay, and migration delay. It is also shown that the proposed algorithm reduces total power consumption of the system.

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“…Due to the sensitive nature of the information involved in VANET, a secure and trustworthy environment is essential. However, ensuring security in VANET is very challenging due to its perceptivity to the wide range of attacks such as man-in-themiddle, Sybil, black-hole or denial-of-service [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis of Trust Models for Safety Applications in IoT-enabled Vehicular Networks

Ahmad

Adnane

Kurugöllü

et al. 2019

2019 Wireless Days (WD)

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Vehicular Ad-hoc NETwork (VANET) is a vital transportation technology that facilitates the vehicles to share sensitive information (such as steep-curve warnings and black ice on the road) with each other and with the surrounding infrastructure in real-time to avoid accidents and enable comfortable driving experience.To achieve these goals, VANET requires a secure environment for authentic, reliable and trusted information dissemination among the network entities. However, VANET is prone to different attacks resulting in the dissemination of compromised/false information among network nodes. One way to manage a secure and trusted network is to introduce trust among the vehicular nodes. To this end, various Trust Models (TMs) are developed for VANET and can be broadly categorized into three classes, Entity-oriented Trust Models (ETM), Data oriented Trust Models (DTM) and Hybrid Trust Models (HTM). These TMs evaluate trust based on the received information (data), the vehicle (entity) or both through different mechanisms. In this paper, we present a comparative study of the three TMs. Furthermore, we evaluate these TMs against the different trust, security and quality-ofservice related benchmarks. Simulation results revealed that all these TMs have deficiencies in terms of end-to-end delays, event detection probabilities and false positive rates. This study can be used as a guideline for researchers to design new efficient and effective TMs for VANET.

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Issues, Challenges, and Research Opportunities in Intelligent Transport System for Security and Privacy

Cited by 40 publications

References 101 publications

Trusted Opportunistic Routing Based on Node Trust Model

Trusted Opportunistic Routing Based on Node Trust Model

An adaptive resource placement policy by optimizing live VM migration for ITS applications in vehicular cloud network

A Comparative Analysis of Trust Models for Safety Applications in IoT-enabled Vehicular Networks

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