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SAFE and Secure: Deeply Integrating Security in a New Hazard Analysis

Published:29 August 2017Publication History

ABSTRACT

Safety-critical system engineering and traditional safety analyses have for decades been focused on problems caused by natural or accidental phenomena. Security analyses, on the other hand, focus on preventing intentional, malicious acts that reduce system availability, degrade user privacy, or enable unauthorized access. In the context of safety-critical systems, safety and security are intertwined, e.g., injecting malicious control commands may lead to system actuation that causes harm. Despite this intertwining, safety and security concerns have traditionally been designed and analyzed independently of one another, and examined in very different ways. In this work we examine a new hazard analysis technique---Systematic Analysis of Faults and Errors (SAFE)---and its deep integration of safety and security concerns. This is achieved by explicitly incorporating a semantic framework of error "effects" that unifies an adversary model long used in security contexts with a fault/error categorization that aligns with previous approaches to hazard analysis. This categorization enables analysts to separate the immediate, component-level effects of errors from their cause or precise deviation from specification.

This paper details SAFE's integrated handling of safety and security through a) a methodology grounded in---and adaptable to---different approaches from the literature, b) explicit documentation of system assumptions which are implicit in other analyses, and c) increasing the tractability of analyzing modern, complex, component-based software-driven systems. We then discuss how SAFE's approach supports the long-term goals of of increased compositionality and formalization of safety/security analysis.

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        • Published in

          cover image ACM Other conferences
          ARES '17: Proceedings of the 12th International Conference on Availability, Reliability and Security
          August 2017
          853 pages
          ISBN:9781450352574
          DOI:10.1145/3098954

          Copyright © 2017 ACM

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          Publication History

          • Published: 29 August 2017

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          Acceptance Rates

          ARES '17 Paper Acceptance Rate100of191submissions,52%Overall Acceptance Rate228of451submissions,51%

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