The Experts below are selected from a list of 4182 Experts worldwide ranked by ideXlab platform
Khattab Ali M. Alheeti - One of the best experts on this subject based on the ideXlab platform.
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a hierarchical detection method in External Communication for self driving vehicles based on tdma
PLOS ONE, 2018Co-Authors: Khattab Ali M. Alheeti, Muzhir Shaban Alani, Klaus D McdonaldmaierAbstract:Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on Communications to predict and sense their External environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the Communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms.
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Using discriminant analysis to detect intrusions in External Communication for self-driving vehicles ☆
Digital Communications and Networks, 2017Co-Authors: Khattab Ali M. Alheeti, Anna Gruebler, Klaus D. Mcdonald-maierAbstract:Abstract Security systems are a necessity for the deployment of smart vehicles in our society. Security in vehicular ad hoc networks is crucial to the reliable exchange of information and control data. In this paper, we propose an intelligent Intrusion Detection System (IDS) to protect the External Communication of self-driving and semi self-driving vehicles. This technology has the ability to detect Denial of Service (DoS) and black hole attacks on vehicular ad hoc networks (VANETs). The advantage of the proposed IDS over existing security systems is that it detects attacks before they causes significant damage. The intrusion prediction technique is based on Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) which are used to predict attacks based on observed vehicle behavior. We perform simulations using Network Simulator 2 to demonstrate that the IDS achieves a low rate of false alarms and high accuracy in detection.
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An enhanced AODV protocol for External Communication in self-driving vehicles
2017 Seventh International Conference on Emerging Security Technologies (EST), 2017Co-Authors: Khattab Ali M. Alheeti, Klaus Mcdonald-maierAbstract:The increasing number of autonomous and semi-autonomous vehicles on the road leads to an increasing need for External vehicle Communication, in particular through emerging vehicular ad hoc networks also known as VANETs. This technology has the ability to facilitate intelligent transportation applications, comfort and other required services for self-driving vehicles. However, suitable routing protocols need to be utilised in order to provide stable routing and enable high performance for this External Communication in autonomous vehicles. Ad hoc on Demand Distance Vector routing (AODV) is to date rarely used in mobile ad hoc network but offers great potential as a reactive routing protocol. However, the AODV protocol is affected by poor performance, when directly employed in VANETs. In this paper, two improvements are presented to the route selection and route discovery of AODV to improve its performance in forms of packet delivery rate and Communication link stability for VANETs. Thus, we obtain new vehicle V-AODV that suits the specific requirements of autonomous vehicles Communications. Simulation results demonstrate that V-AODV can enhance the route stability, reduce overhead and improve Communication performance between vehicles.
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ICCE - Prediction of DoS attacks in External Communication for self-driving vehicles using a fuzzy petri net model
2016 IEEE International Conference on Consumer Electronics (ICCE), 2016Co-Authors: Khattab Ali M. Alheeti, Anna Gruebler, Klaus D. Mcdonald-maier, Anil FernandoAbstract:In this paper we propose a security system to protect External Communications for self-driving and semi self-driving cars. The proposed system can detect malicious vehicles in an urban mobility scenario. The anomaly detection system is based on fuzzy petri nets (FPN) to detect packet dropping attacks in vehicular ad hoc networks. The experimental results show the proposed FPN-IDS can successfully detect DoS attacks in External Communication of self-driving vehicles.
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Prediction of DoS attacks in External Communication for self-driving vehicles using a fuzzy petri net model
2016 IEEE International Conference on Consumer Electronics (ICCE), 2016Co-Authors: Khattab Ali M. Alheeti, Anna Gruebler, Klaus D. Mcdonald-maier, Anil FernandoAbstract:In this paper we propose a security system to protect External Communications for self-driving and semi self-driving cars. The proposed system can detect malicious vehicles in an urban mobility scenario. The anomaly detection system is based on fuzzy petri nets (FPN) to detect packet dropping attacks in vehicular ad hoc networks. The experimental results show the proposed FPN-IDS can successfully detect DoS attacks in External Communication of self-driving vehicles.
Klaus D. Mcdonald-maier - One of the best experts on this subject based on the ideXlab platform.
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Intelligent intrusion detection in External Communication systems for autonomous vehicles
Systems Science & Control Engineering, 2018Co-Authors: Khattab M. Ali Alheeti, Klaus D. Mcdonald-maierAbstract:ABSTRACTSelf-driving vehicles are known to be vulnerable to different types of attacks due to the type of Communication systems which are utilized in these vehicles. These vehicles are becoming mor...
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EST - An enhanced AODV protocol for External Communication in self-driving vehicles
2017 Seventh International Conference on Emerging Security Technologies (EST), 2017Co-Authors: Khattab M. Ali Alheeti, Klaus D. Mcdonald-maierAbstract:The increasing number of autonomous and semi-autonomous vehicles on the road leads to an increasing need for External vehicle Communication, in particular through emerging vehicular ad hoc networks also known as VANETs. This technology has the ability to facilitate intelligent transportation applications, comfort and other required services for self-driving vehicles. However, suitable routing protocols need to be utilised in order to provide stable routing and enable high performance for this External Communication in autonomous vehicles. Ad hoc on Demand Distance Vector routing (AODV) is to date rarely used in mobile ad hoc network but offers great potential as a reactive routing protocol. However, the AODV protocol is affected by poor performance, when directly employed in VANETs. In this paper, two improvements are presented to the route selection and route discovery of AODV to improve its performance in forms of packet delivery rate and Communication link stability for VANETs. Thus, we obtain new vehicle V-AODV that suits the specific requirements of autonomous vehicles Communications. Simulation results demonstrate that V-AODV can enhance the route stability, reduce overhead and improve Communication performance between vehicles.
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Using discriminant analysis to detect intrusions in External Communication for self-driving vehicles ☆
Digital Communications and Networks, 2017Co-Authors: Khattab Ali M. Alheeti, Anna Gruebler, Klaus D. Mcdonald-maierAbstract:Abstract Security systems are a necessity for the deployment of smart vehicles in our society. Security in vehicular ad hoc networks is crucial to the reliable exchange of information and control data. In this paper, we propose an intelligent Intrusion Detection System (IDS) to protect the External Communication of self-driving and semi self-driving vehicles. This technology has the ability to detect Denial of Service (DoS) and black hole attacks on vehicular ad hoc networks (VANETs). The advantage of the proposed IDS over existing security systems is that it detects attacks before they causes significant damage. The intrusion prediction technique is based on Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) which are used to predict attacks based on observed vehicle behavior. We perform simulations using Network Simulator 2 to demonstrate that the IDS achieves a low rate of false alarms and high accuracy in detection.
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ICCE - Prediction of DoS attacks in External Communication for self-driving vehicles using a fuzzy petri net model
2016 IEEE International Conference on Consumer Electronics (ICCE), 2016Co-Authors: Khattab Ali M. Alheeti, Anna Gruebler, Klaus D. Mcdonald-maier, Anil FernandoAbstract:In this paper we propose a security system to protect External Communications for self-driving and semi self-driving cars. The proposed system can detect malicious vehicles in an urban mobility scenario. The anomaly detection system is based on fuzzy petri nets (FPN) to detect packet dropping attacks in vehicular ad hoc networks. The experimental results show the proposed FPN-IDS can successfully detect DoS attacks in External Communication of self-driving vehicles.
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Prediction of DoS attacks in External Communication for self-driving vehicles using a fuzzy petri net model
2016 IEEE International Conference on Consumer Electronics (ICCE), 2016Co-Authors: Khattab Ali M. Alheeti, Anna Gruebler, Klaus D. Mcdonald-maier, Anil FernandoAbstract:In this paper we propose a security system to protect External Communications for self-driving and semi self-driving cars. The proposed system can detect malicious vehicles in an urban mobility scenario. The anomaly detection system is based on fuzzy petri nets (FPN) to detect packet dropping attacks in vehicular ad hoc networks. The experimental results show the proposed FPN-IDS can successfully detect DoS attacks in External Communication of self-driving vehicles.
Anil Fernando - One of the best experts on this subject based on the ideXlab platform.
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ICCE - Prediction of DoS attacks in External Communication for self-driving vehicles using a fuzzy petri net model
2016 IEEE International Conference on Consumer Electronics (ICCE), 2016Co-Authors: Khattab Ali M. Alheeti, Anna Gruebler, Klaus D. Mcdonald-maier, Anil FernandoAbstract:In this paper we propose a security system to protect External Communications for self-driving and semi self-driving cars. The proposed system can detect malicious vehicles in an urban mobility scenario. The anomaly detection system is based on fuzzy petri nets (FPN) to detect packet dropping attacks in vehicular ad hoc networks. The experimental results show the proposed FPN-IDS can successfully detect DoS attacks in External Communication of self-driving vehicles.
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Prediction of DoS attacks in External Communication for self-driving vehicles using a fuzzy petri net model
2016 IEEE International Conference on Consumer Electronics (ICCE), 2016Co-Authors: Khattab Ali M. Alheeti, Anna Gruebler, Klaus D. Mcdonald-maier, Anil FernandoAbstract:In this paper we propose a security system to protect External Communications for self-driving and semi self-driving cars. The proposed system can detect malicious vehicles in an urban mobility scenario. The anomaly detection system is based on fuzzy petri nets (FPN) to detect packet dropping attacks in vehicular ad hoc networks. The experimental results show the proposed FPN-IDS can successfully detect DoS attacks in External Communication of self-driving vehicles.
Klaus D Mcdonaldmaier - One of the best experts on this subject based on the ideXlab platform.
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a hierarchical detection method in External Communication for self driving vehicles based on tdma
PLOS ONE, 2018Co-Authors: Khattab Ali M. Alheeti, Muzhir Shaban Alani, Klaus D McdonaldmaierAbstract:Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on Communications to predict and sense their External environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the Communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms.
Sheldon M. Russell - One of the best experts on this subject based on the ideXlab platform.
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The Role of Human Factors in the Design of Automated Vehicle External Communication
Road Vehicle Automation 6, 2019Co-Authors: W. Andy Schaudt, Sheldon M. Russell, Justin M. OwensAbstract:This chapter presents a summary of the 2018 AVS Breakout Session 25, The Role of Human Factors in the Design of Automated Vehicle External Communications. The session was scheduled for four hours with the majority of the time dedicated to presentations from three speakers and the remaining for an interactive exercise. The three speakers presented on a variety of topics, which included automated vehicle research projects involving External Communication, studies investigating vulnerable road user behavior, as well as activities underway exploring the potential value of international standardization. Key points included the importance of exploring new metrics for measuring the performance of automated vehicle External Communication, the need to study these systems longitudinally, and the importance of investigating the relationship between safety and road user trust and acceptance of these systems.
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judging a car by its cover human factors implications for automated vehicle External Communication
2019Co-Authors: Andy W Schaudt, Sheldon M. RussellAbstract:This chapter presents a summary of the 2017 AVS Breakout Session 2.1, Judging a Car by its Cover: Human Factors Implications for Automated Vehicle External Communication. The session was scheduled for four hours with half the time dedicated to presentations from three speakers and half the time for interactive exercises. The three speakers presented on a range of topics which included related research projects across multiple different countries, as well as activities underway exploring the potential value of international standardization. Key points included the importance of communicating vehicle intent, the need for investigating the unintended consequences of deploying new forms of Communication, and the need for automated vehicles to be consistent in the design of these new interfaces.
