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

Salfer, Martin

Springer Vieweg（2024/03発売）

• 製本 Paperback:紙装版/ペーパーバック版／ページ数 243 p.
• 商品コード 9783658435059

Full Description

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.

Contents

Introduction.- Basics and Related Work.- Models.- Single-Path Attack Graph Algorithm.- Multi-Path Attack Graph Algorithm.- Conclusion.- References