联网和自动驾驶车辆数据和软件保障的分布式“黑匣子”审计跟踪设计规范

Gregory Falco, J. Siegel
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引用次数: 14

摘要

汽车软件越来越复杂,对车辆的安全运行至关重要,相关的嵌入式系统必须保持最新,以确保系统的长期性能。更新机制和数据修改工具为恶意行为者提供了破坏这些网络物理系统的机会,并为受信任的行为者错误地安装不兼容的软件版本。提出了一种针对汽车软件和数据来源的分布式分层“黑匣子”审计跟踪,以确保用户、服务提供商和原始设备制造商(oem)的汽车软件完整性和可靠性。提出的黑箱架构是分层和分散的,采用分布式哈希表(DHT),奇偶校验系统和公共区块链为汽车和其他高保证系统提供高弹性,保证,可扩展性和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Distributed “Black Box” Audit Trail Design Specification for Connected and Automated Vehicle Data and Software Assurance
Automotive software is increasingly complex and critical to safe vehicle operation, and related embedded systems must remain up-to-date to ensure long-term system performance. Update mechanisms and data modification tools introduce opportunities for malicious actors to compromise these cyber-physical systems, and for trusted actors to mistakenly install incompatible software versions. A distributed and stratified "black box" audit trail for automotive software and data provenance is proposed to assure users, service providers, and original equipment manufacturers (OEMs) of vehicular software integrity and reliability. The proposed black box architecture is both layered and diffuse, employing distributed hash tables (DHT), a parity system and a public blockchain to provide high resilience, assurance, scalability, and efficiency for automotive and other high-assurance systems.
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