Automotive Security Analyzer for Exploitability Risks

Name: Automotive Security Analyzer for Exploitability Risks
Brand: Springer Nature
SKU: 9783658435059
Availability: InStock

Automotive Security Analyzer for Exploitability Risks

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Springer Nature

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9783658435059

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New

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Product Description

Our lives depend on automotive cybersecurity, protecting us inside and near vehicles. If vehicles go rogue, they can operate against the drivers 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. AutoSAlfERs 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(n). AutoSAlfER runs on a self-written graph database, heuristics, pruning, and homogenized Gaussian distributions and boosts peoples 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.

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