A conceptual system dynamics model for cybersecurity assessment of connected and autonomous vehicles

Khan, Shah Khalid; Shiwakoti, Nirajan; Stasinopoulos, Peter

doi:10.1016/j.aap.2021.106515

Cited by 42 publications

(18 citation statements)

References 76 publications

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“…Data sets, mathematical forms, and distinctive calculations are examples of exceptional elements that must be included in the development of privacy-preserving techniques. 94 These additions improve the technique's effectiveness and add another level of protection. Moreover, privacy-preserving techniques should be enthusiastic to achieve meaningful and successful outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…Similarly, assessment tests to determine the number of alternatives that the technique can supply should be conducted. Data sets, mathematical forms, and distinctive calculations are examples of exceptional elements that must be included in the development of privacy‐preserving techniques 94 . These additions improve the technique's effectiveness and add another level of protection.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Mishra,

Jabar,

Alzoubi

et al. 2023

Concurrency and Computation

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SummaryData privacy is critical for users who want to use Cloud storage services. There is a significant focus on Cloud service providers to address this need. However, in the evolving dynamic cyber‐space, privacy infractions are rising and pose threats to Cloud storage infrastructures. Several studies developed various models and techniques to ensure the privacy of Cloud storage contents. However, these models came with several shortages in the privacy‐preserving attributes they cover. Thus, this article identified a comprehensive set of Cloud data storage privacy‐preserving attributes to propose a flexible and efficient framework to handle the privacy problem. This framework uses a multi‐layer encryption storage structure and a one‐time password authentication technique. The findings of this article intend to help future communities to enhance existing techniques or develop new research‐based practical alternatives. Since Cloud computing is a rapidly growing technology, new privacy vulnerabilities emerge daily. Future research might confirm the findings of this article and test the suggested framework in different contexts.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Mishra,

Jabar,

Alzoubi

et al. 2023

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…Although the acceleration and deceleration profiles in the Gipps model are unrealistic, the model is widely used to simulate car-following behaviour due to its simplex nature. As shown in Equation (10), in Gipps model, a vehicle needs to maintain a 'safe speed' to ensure that the gap is not smaller than the minimum gap even if its leader comes to a sudden stop. The updated speed at time t + 𝜏 will take the smallest of the 'safe speed', a desired speed, and the speed assumes that the vehicle accelerates with a constant acceleration a, which takes the form of Equation (11).…”

Section: Gipps Modelmentioning

confidence: 99%

“…In recent years, researchers have demonstrated that CAVs are prone to cyberattacks in real world [7][8][9]. Therefore, it has become an imperative task to understand the cyberattacks that can be made to CAVs and VANETs and the impacts of such attacks [10].…”

Section: Introductionmentioning

confidence: 99%

Cyberattacks on connected automated vehicles: A traffic impact analysis

Sun

Liu

et al. 2022

IET Intelligent Trans Sys

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Cybersecurity has become one of the major challenges for Connected Automated Vehicles. Previous work in this field mostly focused on the detection of and defence against Connected Automated Vehicle‐related cyberattacks. Using performance measures collected from traffic micro‐simulations, the study analysed the traffic impacts of cyberattacks on Connected Automated Vehicles. Two types of adversary models, namely, time‐delay attacks and disturbance attacks, were applied to the simulated traffic on freeway segments and un‐signalised intersections, respectively. The effects of various cyberattacks were evaluated based on safety indicators, including Time‐To‐Collision, Deceleration Rate to Avoid Collision, and efficiency indicators, including speed and flow‐density diagrams. The results revealed that both attacks increase the risk and severity of collisions on freeway segments and un‐signalised intersections. Location‐based time‐delay attacks will result in significant deceleration, congestion and reduction in road throughput. Disturbance attacks not only cause congestion but also result in frequent acceleration/deceleration and uneven distribution of traffic density. The impacts of attacks are more severe on heavy traffic. At un‐signalised intersections, location‐based disturbance attacks lead to a significantly increased risk of right‐angled collisions. The results could help better understand the effects of Connected Automated Vehicle‐related cyberattacks and shed light on proactive defence against such attacks.

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“…Ge et al [ 7 ] proposed an algorithm to address the problem of resilient and safe platooning control of CAVs that are under denial-of-service attacks disrupting the V2V communication. Khan et al [ 8 ] developed a conceptual system dynamics model to analyze the cybersecurity of CAVs. The model integrates six critical areas and their corresponding parameters that either enable or mitigate attacks on CAVs operation.…”

Section: Introductionmentioning

confidence: 99%

Physical and Digital Infrastructure Readiness Index for Connected and Automated Vehicles

Cucor

Petrov

Kamencay

et al. 2022

Sensors

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In this paper, we present an assessment framework that can be used to score segments of physical and digital infrastructure based on their features and readiness to expedite the deployment of Connected and Automated Vehicles (CAVs). We discuss the equipment and methodology applied for the collection and analysis of required data to score the infrastructure segments in an automated way. Moreover, we demonstrate how the proposed framework can be applied using data collected on a public transport route in the city of Zilina, Slovakia. We use two types of data to demonstrate the methodology of the assessment-connectivity and positioning data to assess the connectivity and localization performance provided by the infrastructure and image data for road signage detection using a Convolutional Neural Network (CNN). The core of the research is a dataset that can be used for further research work. We collected and analyzed data in two settings—an urban and suburban area. Despite the fact that the connectivity and positioning data were collected in different days and times, we found highly underserved areas along the investigated route. The main problem from the point of view of communication in the investigated area is the latency, which is an issue associated with infrastructure segments mainly located at intersections with heavy traffic or near various points of interest. The low accuracy of localization has been observed mainly in dense areas with large buildings and trees, which decrease the number of visible localization satellites. To address the problem of automated assessment of the traffic sign recognition precision, we proposed a CNN that achieved 99.7% precision.

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A conceptual system dynamics model for cybersecurity assessment of connected and autonomous vehicles

Cited by 42 publications

References 76 publications

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Cyberattacks on connected automated vehicles: A traffic impact analysis

Physical and Digital Infrastructure Readiness Index for Connected and Automated Vehicles

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