A survey on internet of vehicles: Applications, security issues & solutions

The widespread adoption of the Internet of Things (IoT) technologies has drastically increased the breadth and depth of attack surfaces in networked systems, providing new mechanisms for the intrusion. In the context of smart-world critical infrastructures and cyber-physical systems, the rapid adoption of the IoT systems and infrastructures without thorough consideration for the risks and vulnerabilities has the potential for catastrophic damage to the privacy, safety, and security of individuals and corporations. While the IoT systems have the potential to increase productivity, accountability, traceability, and efficiency, their potential weaknesses are also more abundant. In this paper, we provide critical consideration of the security of the IoT systems as applied to smart-world critical infrastructures. Particularly, we carry out a detailed assessment of vulnerabilities in IoT-based critical infrastructures from the perspectives of applications, networking, operating systems, software, firmware, and hardware. In addition, we highlight the three key critical infrastructure IoT-based cyber-physical systems, namely the smart transportation, smart manufacturing, and smart grid. Moreover, we provide a broad collection of attack examples upon each of the key applications. Furthermore, we introduce a case study, in which we assess the impacts of potential attacks on critical IoT-based systems, using the smart transportation system as an example. Finally, we provide a set of best practices and address the necessary steps to enact countermeasures for any generic IoT-based critical infrastructure system.

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Secure Internet of Things (IoT)-Based Smart-World Critical Infrastructures: Survey, Case Study and Research Opportunities

Intelligent Traffic Systems (ITS) are currently evolving in the form of a cooperative ITS or connected vehicles. Both forms use the data communications between Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I/I2V) and other on-road entities, and are accelerating the adoption of self-driving cars. The development of cyber-physical systems containing advanced sensors, sub-systems, and smart driving assistance applications over the past decade is equipping unmanned aerial and road vehicles with autonomous decision-making capabilities. The level of autonomy depends upon the make-up and degree of sensor sophistication and the vehicle’s operational applications. As a result, self-driving cars are being compromised perceived as a serious threat. Therefore, analyzing the threats and attacks on self-driving cars and ITSs, and their corresponding countermeasures to reduce those threats and attacks are needed. For this reason, some survey papers compiling potential attacks on VANETs, ITSs and self-driving cars, and their detection mechanisms are available in the current literature. However, up to our knowledge, they have not covered the real attacks already happened in self-driving cars. To bridge this research gap, in this paper, we analyze the attacks that already targeted self-driving cars and extensively present potential cyber-attacks and their impacts on those cars along with their vulnerabilities. For recently reported attacks, we describe the possible mitigation strategies taken by the manufacturers and governments. This survey includes recent works on how a self-driving car can ensure resilient operation even under ongoing cyber-attack. We also provide further research directions to improve the security issues associated with self-driving cars.

Attacks on Self-Driving Cars and Their Countermeasures: A Survey

Vehicular ad hoc networks (VANETs) are emerged technology where vehicles and roadside units (RSUs) communicate with each other. VANETs can be categorized as a subbranch of mobile ad hoc networks (MANETs). VANETs help to improve traffic efficiency and safety and provide infotainment facility as well. The dissemination of messages must be relayed through nodes in VANETs. However, it is possible that a node may propagate false information in a network due to its malicious behaviour or selfishness. False information in VANETs can change drivers’ behaviour and create disastrous consequences in the network. Therefore, sometimes false safety messages may endanger human life. To avoid any lass, it is more important to detect and avoid false messages. This paper has explained some important algorithms that can detect false messages in VANETs. The categorization of false message detection schemes based on local and cooperative behaviour has been presented in this article. The limitations and consequences of existing schemes as well as future work has been discussed.

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A survey of local/cooperative-based malicious information detection techniques in VANETs

To enhance industrial production and automation, rapid and faster transportation of raw materials and finished products to and from distributed factories, warehouses and outlets are essential. To reduce cost with increased efficiency, this will increasingly see the use of connected and self-driving commercial vehicles fitted with industrial grade sensors on roads, shared with normal and self-driving passenger vehicles. For its wide adoption, the trustworthiness of self-driving vehicles in the intelligent transportation system (ITS) is pivotal. In this article, we introduce a novel model to measure the overall trustworthiness of a self-driving vehicle considering on-Board unit (OBU) components, GPS data and safety messages. In calculating the trustworthiness of individual OBU components, CertainLogic and beta distribution function (BDF) are used. Those trust values are fused using both the dempster–Shafer Theory (DST) and a logical operator of CertainLogic. Results of our simulation show that our proposed method can effectively determine the trust of self-driving vehicles.

Trustworthiness of Self-Driving Vehicles for Intelligent Transportation Systems in Industry Applications

Vehicular Ad-hoc Network (VANET) is an emerging technology and is an application of Mobile Ad-hoc Network (MANET). So it has same characteristics like wireless medium, dynamic topology, collision interference. Objective of VANET is to create and provide communications among group of vehicles without any central base station. An attack like Black hole in VANET is a main issue that degrades performance of whole network. Many existing algorithms tried to solve this issue but not completely. In order to solve above problems in VANET from black hole attack, we propose a new routing protocol named Lifetime Improving Ad-hoc On-demand Distance Vector (LI-AODV). To reduce overload in routing process we introduce a scheduling algorithm named Hybrid Round Robin with Highest Response Ratio Next (HRRHRRN). To prevent the network from Black hole attack we propose a new security algorithm called HMAC-SHA3-384 which is a combination of SHA3-384 and HMAC. This LI-AODV achieves better performance in lifetime of the network, reduces black hole attack, End-to-End delay, throughput, packet loss, Packet delivery ratio. Our experimental procedure provides efficient identification and removal of black hole attack in urban VANET.

LI-AODV: lifetime improving AODV routing for detecting and removing black-hole attack from VANET

Vehicular ad hoc network (VANET) technologies are evolving networked communications advances that incorporate mobile-based routing protocol sets for inter-vehicular exchanges of information in support of smart transportation networks. Privacy and security difficulties are primary concerns in VANET research as a result of the repeated vehicular movements, time-critical responses, and hybrid VANET architectures that differentiate these from other ad hoc networking types. Therefore, the design of secure mechanisms for authenticating and validating message transmissions between vehicles and eliminating adversarial elements from networks are of considerable importance in VANET research. This report offers a review of VANET features and security difficulties. The paper also summarizes certain chief threats to the authentication, confidentiality, and availability of secure services.

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Vehicular Ad Hoc Networks and Security Issues: Survey

The Vehicular Ad hoc Networks are a special type of ad hoc network, which along with lacking in infrastructure, contain communicating entities that move with different accelerations. Hence, this obstructs the establishment of more consistent end-to-end communicating pathways and efficiently transferring data. Therefore, the VANETs display many network concerns and show differing security challenges for obtaining a secure communication, ubiquitous connectivity, and reputed management systems that can affect the cooperation and the negotiation between the various mobile networks. This survey report studies some techniques reported by the researchers for the detection of the Sybil attack in the VANET systems.

A Survey on Sybil Attack Detection in Vehicular ad hoc Networks (VANET)

Vehicular ad-hoc network (VANET) is a promising approach that provides safety measures and other application to the drivers on the vehicles The focus of VANETs is to fulfil user's requirements on road side area which increases the safe and comfortable journey for users It provides good communication like mobile ad-hoc network (MANET) when there is no intruders exist in the network In VANET, communication depends on road safety such as emergency situation, vehicles tracking, messages monitoring and tracking of vehicles But many attackers like black hole attack, wormhole attack and Sybil attack are more vulnerable to VANET In order to provide efficient communication, we provide a malicious node identification routing mechanism which gives the valid route between two vehicles To avoid several attacks, we introduce a protection mechanism that includes key management for preventing our network Our proposed system provides efficient communication on VANET that focus on throughput, end-to-end delay, packet delivery ratio, detection rate and misdetection rate

Zaid A. Abdulkader

Papers

LI-AODV: lifetime improving AODV routing for detecting and removing black-hole attack from VANET

Vehicular Ad Hoc Networks and Security Issues: Survey

A Survey on Sybil Attack Detection in Vehicular ad hoc Networks (VANET)

Malicious node identification routing and protection mechanism for vehicular ad-hoc network against various attacks

Cloud Data Security Mechanism using the Lightweight Cryptography