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Early Warning And Prediction Of Internet Attacks And Exploits
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Springer Vieweg
Automotive Security Analyzer for Exploitability Risks : An Automated and Attack Graph-Based Evaluation of On-Board Networks
Product Code:
9783658435059
ISBN13:
9783658435059
Condition:
New
$117.02
Our lives depend on automotive cybersecurity, protecting us inside and near vehicles. If vehicles go rogue, they can operate against the driver?s will and potentially drive off a cliff or into a crowd. The ?Automotive Security Analyzer for Exploitability Risks? (AutoSAlfER) evaluates the exploitability risks of automotive on-board networks by attack graphs. AutoSAlfER?s Multi-Path Attack Graph algorithm is 40 to 200 times smaller in RAM and 200 to 5 000 times faster than a comparable implementation using Bayesian networks, and the Single-Path Attack Graph algorithm constructs the most reasonable attack path per asset with a computational, asymptotic complexity of only O(n * log(n)), instead of O(n2). AutoSAlfER runs on a self-written graph database, heuristics, pruning, and homogenized Gaussian distributions and boosts people?s productivity for a more sustainable and secure automotive on-board network. Ultimately, we enjoy more safety and security in and around autonomous, connected, electrified, and shared vehicles.
| Author: Martin Salfer |
| Publisher: Springer Vieweg |
| Publication Date: Mar 16, 2024 |
| Number of Pages: NA pages |
| Language: English |
| Binding: Paperback |
| ISBN-10: 3658435054 |
| ISBN-13: 9783658435059 |
Automotive Security Analyzer for Exploitability Risks : An Automated and Attack Graph-Based Evaluation of On-Board Networks
$117.02
Our lives depend on automotive cybersecurity, protecting us inside and near vehicles. If vehicles go rogue, they can operate against the driver?s will and potentially drive off a cliff or into a crowd. The ?Automotive Security Analyzer for Exploitability Risks? (AutoSAlfER) evaluates the exploitability risks of automotive on-board networks by attack graphs. AutoSAlfER?s Multi-Path Attack Graph algorithm is 40 to 200 times smaller in RAM and 200 to 5 000 times faster than a comparable implementation using Bayesian networks, and the Single-Path Attack Graph algorithm constructs the most reasonable attack path per asset with a computational, asymptotic complexity of only O(n * log(n)), instead of O(n2). AutoSAlfER runs on a self-written graph database, heuristics, pruning, and homogenized Gaussian distributions and boosts people?s productivity for a more sustainable and secure automotive on-board network. Ultimately, we enjoy more safety and security in and around autonomous, connected, electrified, and shared vehicles.
| Author: Martin Salfer |
| Publisher: Springer Vieweg |
| Publication Date: Mar 16, 2024 |
| Number of Pages: NA pages |
| Language: English |
| Binding: Paperback |
| ISBN-10: 3658435054 |
| ISBN-13: 9783658435059 |
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