List of Titles

Trusted autonomous vehicle : measuring trust using on-board unit data

- Chowdhury, Abdullahi, Karmakar, Gour, Kamruzzaman, Joarder

Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder
Date: 2019
Type: Text , Conference proceedings , Conference paper
Relation: 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering, TrustCom/BigDataSE 2019 p. 787-792
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Description: Vehicular Ad-hoc Networks (VANETs) play an essential role in ensuring safe, reliable and faster transportation with the help of an Intelligent Transportation system. The trustworthiness of vehicles in VANETs is extremely important to ensure the authenticity of messages and traffic information transmitted in extremely dynamic topographical conditions where vehicles move at high speed. False or misleading information may cause substantial traffic congestions, road accidents and may even cost lives. Many approaches exist in literature to measure the trustworthiness of GPS data and messages of an Autonomous Vehicle (AV). To the best of our knowledge, they have not considered the trustworthiness of other On-Board Unit (OBU) components of an AV, along with GPS data and transmitted messages, though they have a substantial relevance in overall vehicle trust measurement. In this paper, we introduce a novel model to measure the overall trustworthiness of an AV considering four different OBU components additionally. The performance of the proposed method is evaluated with a traffic simulation model developed by Simulation of Urban Mobility (SUMO) using realistic traffic data and considering different levels of uncertainty. © 2019 IEEE.
Description: E1

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Emergency message dissemination schemes based on congestion avoidance in VANET and vehicular FoG computing

- Ullah, Ata, Yaqoob, Shumayla, Imran, Muhammad, Ning, Huansheng

Authors: Ullah, Ata , Yaqoob, Shumayla , Imran, Muhammad , Ning, Huansheng
Date: 2019
Type: Text , Journal article
Relation: IEEE Access Vol. 7, no. (2019), p. 1570-1585
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Description: With the rapid growth in connected vehicles, FoG-assisted vehicular ad hoc network (VANET) is an emerging and novel field of research. For information sharing, a number of messages are exchanged in various applications, including traffic monitoring and area-specific live weather and social aspects monitoring. It is quite challenging where vehicles' speed, direction, and density of neighbors on the move are not consistent. In this scenario, congestion avoidance is also quite challenging to avoid communication loss during busy hours or in emergency cases. This paper presents emergency message dissemination schemes that are based on congestion avoidance scenario in VANET and vehicular FoG computing. In the similar vein, FoG-assisted VANET architecture is explored that can efficiently manage the message congestion scenarios. We present a taxonomy of schemes that address message congestion avoidance. Next, we have included a discussion about comparison of congestion avoidance schemes to highlight the strengths and weaknesses. We have also identified that FoG servers help to reduce the accessibility delays and congestion as compared to directly approaching cloud for all requests in linkage with big data repositories. For the dependable applicability of FoG in VANET, we have identified a number of open research challenges. © 2013 IEEE.

RTRD: Real-time route discovery for urban scenarios using internet of things

- Din, Sadia, Ahmad, Awais, Paul, Anand, Anisetti, Marco, Imran, Muhammad

Authors: Din, Sadia , Ahmad, Awais , Paul, Anand , Anisetti, Marco , Imran, Muhammad
Date: 2019
Type: Text , Conference paper
Relation: 2019 IEEE Global Communications Conference, GLOBECOM 2019, Waikola, 9-13 December 2019
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Description: A rapid development has been seen in the Vehicular ad hoc networks (VANETs) because of their applicability and significance in the fields of traffic management, road monitoring and safety, infotainment, and on-demand services. Route planning in vehicular networks based on efficient collection of real-time data can effectively mitigate traffic congestion problems in urban areas. Furthermore, real-time data is shared by using an effective sharing mechanism to avoid redundancy of the collected information. However, dynamic route replanning and effective sharing mechanisms based on real-time data are still challenging problems. Therefore, based on the aforementioned constraints, this paper describes a route discovery technique that uses real time data collected from various vehcicles using the Internet of Things. The proposed scheme is based on the novel data dissemination technique for information sharing among the roadside units. RTRD is comprised of VANETs, vehicular traffic servers, and a 5G-based cellular system of public transportation. By considering the traffic congestion in urban areas, the optimal path is calculated to re-plan routes based on the k shortest path algorithm, and a load balancing technique is adopted to avoid further congestion. © 2019 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**

A cooperative heterogeneous vehicular clustering mechanism for road traffic management

- Ahmad, Iftikhara, Noor, Rafidah, Zaba, Muhammad, Qureshi, Muhammad, Imran, Muhammad, Shoaib, Muhammad

Authors: Ahmad, Iftikhara , Noor, Rafidah , Zaba, Muhammad , Qureshi, Muhammad , Imran, Muhammad , Shoaib, Muhammad
Date: 2020
Type: Text , Journal article
Relation: International Journal of Parallel Programming Vol. 48, no. 5 (2020), p. 870-889
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Description: The vehicular ad-hoc networks integrates with long-term evolution (LTE) forming a heterogeneous network, capable of providing seamless connectivity, which meets the communication requirements of intelligent transportation systems. However, heterogeneous network-based applications involve LTE resource (data and spectrum) usage cost and must be taken care while developing such a solution. One of the scenarios is the access of the information to/from remote server over the internet via LTE for road traffic management applications. Although clustering of the vehicle is significant to minimize the data and LTE network usage, however, the problem of non-cooperation of the vehicles in clustering process and within a cluster are major issues in sharing costly data acquired from the internet. Because, who and why one (vehicle) should pay the cost is the big question, proliferating the non-cooperative behavior among the cluster members. To solve these issues, strategic game-theoretic based clustering mechanism named as cooperative interest-aware clustering (CIAC) is developed. The proposed CIAC not only balance the cost of usage by controlling non-cooperative behavior among the vehicles within the cluster but at the same time motivate vehicles to participate in the clustering process to share the data and cost as well. It consists of a cluster head selection process based on the strategic game-theoretic approach and a fair-use policy. The implementation results show superiority in performance of our protocol over the existing approaches. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

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Attacks on self-driving cars and their countermeasures : a survey

- Chowdhury, Abdullahi, Karmakar, Gour, Kamruzzaman, Joarder, Jolfaei, Alireza, Das, Rajkumar

Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Jolfaei, Alireza , Das, Rajkumar
Date: 2020
Type: Text , Journal article , Review
Relation: IEEE Access Vol. 8, no. (2020), p. 207308-207342
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Description: 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. © 2013 IEEE.

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