Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Automotive Security Analyzer for Exploitability Risks: An Automated and Attack Graph-Based Evaluation of On-Board Networks

Automotive Security Analyzer for Exploitability Risks: An Automated and Attack Graph-Based Evaluation of On-Board Networks

Salfer, Martin

Paperback

Technology & EngineeringGeneral Computers

ISBN10: 3658435054
ISBN13: 9783658435059
Publisher: Springer Vieweg
Published: Mar 16 2024
Pages: 243
Weight: 0.72
Height: 0.57 Width: 5.83 Depth: 8.27
Language: English
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(n ). 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.

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