Protocol analysis modulo combination of theories: A case study in Maude-NPA

There is a growing interest in formal methods and tools to analyze cryptographic protocols modulo algebraic properties of their underlying cryptographic functions. It is well-known that an intruder who uses algebraic equivalences of such functions can mount attacks that would be impossible if the cryptographic functions did not satisfy such equivalences. In practice, however, protocols use a collection of well-known functions, whose algebraic properties can naturally be grouped together as a union of theories E 1... ¿ n. Reasoning symbolically modulo the algebraic properties E 1... ¿ n requires performing (E 1... ¿ n)-unification. However, even if a unification algorithm for each individual E i is available, this requires combining the existing algorithms by methods that are highly non-deterministic and have high computational cost. In this work we present an alternative method to obtain unification algorithms for combined theories based on variant narrowing. Although variant narrowing is less efficient at the level of a single theory E i, it does not use any costly combination method. Furthermore, it does not require that each E i has a dedicated unification algorithm in a tool implementation. We illustrate the use of this method in the Maude-NPA tool by means of a well-known protocol requiring the combination of three distinct equational theories. © 2011 Springer-Verlag.R. Sasse and J. Meseguer have been partially supported by NSF Grants CNS0716638, CNS-0831064 and CNS-0904749. S. Escobar has been partially supported by the EU (FEDER) and the Spanish MEC/MICINN under grant TIN 2007-68093- C02-02. C. Meadows has been partially supported by NSF Grant CNS-0904749National Science Foundation, EEUUSasse, R.; Escobar Román, S.; Meadows, C.; Meseguer, J. (2011). Protocol analysis modulo combination of theories: A case study in Maude-NPA. En Security and Trust Management. Springer Verlag (Germany). 6710:163-178. doi:10.1007/978-3-642-22444-7_11S163178671