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Navigating the True Random Number Generation Dilemma in Cryptography

Explore the challenges and solutions surrounding true random number generation (TRNG) in cryptography, including standards, implementation, validation, key management, and more. Discover the importance of TRNGs in information assurance and the gap in security arguments left by the lack of TRNG standards. Delve into strategies like statistical acceptance tests, standardized designs, and design criteria to address shortcomings in TRNG implementation. Uncover topics worthy of exploration such as entropy source analysis, implementation validation, and levels of assurance. Enhance your understanding of cryptographic standards and TRNG issues for improved cryptographic assurance.

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Navigating the True Random Number Generation Dilemma in Cryptography

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  1. True Random Number Generation: A Standard(s) Dilemma Paul Timmel Cryptology Office Information Assurance Research Group National Security Agency 24 June 2002

  2. Overview and Thesis • Cryptography depends on the randomness of secrets and other values (e.g. keys) for security. • Existing standards either do not address that, or generate them from an initial secret of unspecified provenance. • ISO, NIST, and ANSI X9 (at least) are finding the problem difficult to address. • Rigorous literature on true (non-deterministic) random number generators (TRNGs) is scarce. • TRNGs are an important information assurance frontier that should be rich with opportunities for publication.

  3. Algorithm Design Algorithm Analysis Cryptographic Standards Implementation Design Validation Testing Information Assurance and Standards Cryptomathematics Social/Technical Consensus Engineering

  4. Security, Standards, and Confidence • Security Standards can: • establish grounds for confidence in security products, • establish ways to achieve confidence, and • guide or bound the confidence required. • Security and confidence are not synonymous • Non-standard products can be secure. • Standards-complying products might not be. • Standards express a consensus about “due diligence” and ease risk assessment.

  5. Design Analysis Implementation Validation Key Management Pseudo RNG True RNG Cryptographic Security Dependencies Crypto-Algorithms Random Number Generation (RNG) More Algorithms Other (recurse)

  6. The Dilemma • True random number generation (TRNG) does not admit to complete abstract specification. • Standards are implementation independent. • “The devil is in the [implementation] details.” • The TRNG details ignored by standards leave a gap in security arguments. • Cryptographic standards assume that secret keys and seeds are suitably random. • Without TRNG standards, that assumption cannot be completely validated in products.

  7. Solution Strategies and Shortcomings • Statistical Acceptance Tests • Standardized Designs • Design Criteria

  8. Statistical Acceptance Tests • Examples: Diehard, NIST • Problems • Where/how should the tests be applied? • Can’t define a general answer without considering design details. • Statistics can distinguish between random sequences and predetermined alternatives, but cannot derive those alternatives. • Statistics is a tool, not a panacea.

  9. Standard RNG Designs • Standard designs would make tests meaningful. • However: • Robust TRNG designs are implementation and technology specific. • Technology changes too fast for a standard design to stay relevant. • The critical implementation details are usually proprietary. • There is insufficient literature on TRNGs on which to base standard designs.

  10. Design Criteria • Criteria would be implementation independent • Criteria would establish the grounds for acceptable designs. • Criteria would define the evidence that designs and implementations must create to support independent validation and acceptance. • However: • Design/product validation could cost more (time and expertise) than for other approaches. • Criteria are most effectively derived from published literature, of which there is little.

  11. Topics Worthy of Exploration • Entropy Source Identification and Analysis • Entropy estimation tools suited for cryptography. • Methodology for both low rate and high rate sources. • Degenerate conditions and environmental factors. • Theory versus practice: technology and environment. • Implementation Design and Criteria • Functional requirements for cryptographic TRNGs. • Designing for assurance: a matter of process. • Designing for validation: a matter of evidence.

  12. More Topics • Implementation Validation • What to validate: theory, design, product, or all three? • How to validate: what to do with the evidence. • Levels of assurance: one size won’t fit all. • Keeping validation cost-effective.

  13. Summary • Cryptographic standards rely on but do not yet address TRNGs. • TRNGs have many open issues concerning both principles and practice. • These issues have largely escaped rigorous scrutiny. • Further improvement in cryptographic assurance will likely depend upon pragmatic solutions to these issues.

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