Affordable Access

Access to the full text

Knowledge Extraction for Cryptographic Algorithm Validation Test Vectors by Means of Combinatorial Coverage Measurement

Authors
  • Simos, Dimitris
  • Garn, Bernhard
  • Kampel, Ludwig
  • Kuhn, D.
  • Kacker, Raghu
Publication Date
Aug 26, 2019
Identifiers
DOI: 10.1007/978-3-030-29726-8_13
OAI: oai:HAL:hal-02520031v1
Source
HAL-Descartes
Keywords
Language
English
License
Green
External links

Abstract

We present a combinatorial coverage measurement analysis for test vectors provided by the NIST Cryptographic Algorithm Validation Program (CAVP), and in particular for test vectors targeting the AES block ciphers for different key sizes and cryptographic modes of operation. These test vectors are measured and analyzed using a combinatorial approach, which was made feasible via developing the necessary input models. The extracted model from the test data in combination with combinatorial coverage measurements allows to extract information about the structure of the test vectors. Our analysis shows that some test sets do not achieve full combinatorial coverage. It is further discussed, how this retrieved knowledge could be used as a means of test quality analysis, by incorporating residual risk estimation techniques based on combinatorial methods, in order to assist the overall validation testing procedure.

Report this publication

Statistics

Seen <100 times