Towards Rapid Re-Certification Using Formal Analysis

Abstract

Department of Defense (DoD) acquisition requires IT to undergo the DoD information assurance certification and accreditation process (DIACAP), which makes architecture-dependent assumptions. Emerging IT architectures, such as mobile and cloud-based platforms, invalidate these assumptions and prevent DoD from acquiring commercial that are readily available to adversaries. To address this problem, we extended our initial automation framework, wherein an application profile is expressed in a formal language and scaled with evolving architectural assumptions. These profiles will help ensure that information assurance requirements are commensurate with risk and scalable based on an applications changing external dependencies. Information assurance risk levels must account for changing environmental and IA parameters(confidentiality, integrity and availability) that result from dynamic recombination of applications during runtime. Our proposed language aims to address dynamically composable, multi-party systems that preserve security properties. Software developers and certification authorities can use these profiles expressed in first-order logic with an inference engine to advance the DIACAP and re-check compliance as IT systems evolve over time.

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Document Details

Document Type
Technical Report
Publication Date
Jul 22, 2015
Accession Number
AD1014622

Entities

People

  • Daniel Smullen
  • Travis Breaux

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Acquisition
  • Complex Systems
  • Computer Science
  • Computers
  • Cooperative Engagement Capability
  • Department Of Defense
  • Engineering
  • Formal Languages
  • Information Assurance
  • Information Exchange
  • Information Systems
  • Language
  • Ontologies
  • Public Policy
  • Radar
  • Software Development
  • Zumwalt Class

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Distributed Systems and Data Platform Development
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy