Resource-aware trust-based security for vehicular smart-grid networks
Vehicular smart grids (VSGs) are localised electrical grids that form spontaneously when heterogeneous nodes, including electric vehicles (EVs) and charging stations (CSs), are temporarily co-located and can communicate and exchange energy bi-directionally, e.g., vehicle-to-vehicle (V2V). VSGs are h...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2024
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| Online Access: | https://eprints.nottingham.ac.uk/78567/ |
| _version_ | 1848801090800189440 |
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| author | Walker, Adam David |
| author_facet | Walker, Adam David |
| author_sort | Walker, Adam David |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Vehicular smart grids (VSGs) are localised electrical grids that form spontaneously when heterogeneous nodes, including electric vehicles (EVs) and charging stations (CSs), are temporarily co-located and can communicate and exchange energy bi-directionally, e.g., vehicle-to-vehicle (V2V). VSGs are highly dynamic due primarily to EV mobility. Instability and lack of trust amongst nodes make energy management challenging and create opportunities for malicious actors to disrupt supply through energy denial-of-service (EDoS) attacks. We see VSGs as an extension of opportunistic networks (OppNets). This thesis proposes CognitiveCharge, a framework and template protocol for independent, mutually untrusted nodes to coordinate localised, opportunistic energy exchange that builds on data routing strategies in OppNets. Each device in our VSG model operates as an independent CognitiveCharge node using real-time utility-driven decision-making and cross-layer predictive analytics using first and second-hand observations. We implement CognitiveCharge by significantly extending existing agent-based discrete event network simulation software. CognitiveCharge performance is explored across a range of multi-day urban and semi-urban VSG scenarios, which include real-world and pseudo-realistic data and were developed specifically for this work. Our simulation-based experiments show that CognitiveCharge increases the availability of energy for EVs to expend on mobility, even when under an active EDoS attack. CognitiveCharge nodes can identify and exploit energy exchange opportunities to increase local and regional availability of on-demand energy as well as mitigate the impact of EDoS attacks in terms of energy loss by accurately detecting and avoiding exchanges with malicious nodes. |
| first_indexed | 2025-11-14T21:01:56Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-78567 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:01:56Z |
| publishDate | 2024 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-785672024-12-13T04:40:05Z https://eprints.nottingham.ac.uk/78567/ Resource-aware trust-based security for vehicular smart-grid networks Walker, Adam David Vehicular smart grids (VSGs) are localised electrical grids that form spontaneously when heterogeneous nodes, including electric vehicles (EVs) and charging stations (CSs), are temporarily co-located and can communicate and exchange energy bi-directionally, e.g., vehicle-to-vehicle (V2V). VSGs are highly dynamic due primarily to EV mobility. Instability and lack of trust amongst nodes make energy management challenging and create opportunities for malicious actors to disrupt supply through energy denial-of-service (EDoS) attacks. We see VSGs as an extension of opportunistic networks (OppNets). This thesis proposes CognitiveCharge, a framework and template protocol for independent, mutually untrusted nodes to coordinate localised, opportunistic energy exchange that builds on data routing strategies in OppNets. Each device in our VSG model operates as an independent CognitiveCharge node using real-time utility-driven decision-making and cross-layer predictive analytics using first and second-hand observations. We implement CognitiveCharge by significantly extending existing agent-based discrete event network simulation software. CognitiveCharge performance is explored across a range of multi-day urban and semi-urban VSG scenarios, which include real-world and pseudo-realistic data and were developed specifically for this work. Our simulation-based experiments show that CognitiveCharge increases the availability of energy for EVs to expend on mobility, even when under an active EDoS attack. CognitiveCharge nodes can identify and exploit energy exchange opportunities to increase local and regional availability of on-demand energy as well as mitigate the impact of EDoS attacks in terms of energy loss by accurately detecting and avoiding exchanges with malicious nodes. 2024-12-13 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/78567/1/PhD%20Thesis%20-%20Adam%20Walker.pdf Walker, Adam David (2024) Resource-aware trust-based security for vehicular smart-grid networks. PhD thesis, University of Nottingham. Vehicular smart grids; Opportunistic energy exchange; Data routing; Discrete event network simulation software |
| spellingShingle | Vehicular smart grids; Opportunistic energy exchange; Data routing; Discrete event network simulation software Walker, Adam David Resource-aware trust-based security for vehicular smart-grid networks |
| title | Resource-aware trust-based security for vehicular smart-grid networks |
| title_full | Resource-aware trust-based security for vehicular smart-grid networks |
| title_fullStr | Resource-aware trust-based security for vehicular smart-grid networks |
| title_full_unstemmed | Resource-aware trust-based security for vehicular smart-grid networks |
| title_short | Resource-aware trust-based security for vehicular smart-grid networks |
| title_sort | resource-aware trust-based security for vehicular smart-grid networks |
| topic | Vehicular smart grids; Opportunistic energy exchange; Data routing; Discrete event network simulation software |
| url | https://eprints.nottingham.ac.uk/78567/ |