Automatic Unbounded Verification of Alloy Specifications with Prover9

Alloy is an increasingly popular lightweight specification language based on relational logic. Alloy models can be automatically verified within a bounded scope using off-the-shelf SAT solvers. Since false assertions can usually be disproved using small counter-examples, this approach suffices for most applications. Unfortunately, it can sometimes lead to a false sense of security, and in critical applications a more traditional unbounded proof may be required. The automatic theorem prover Prover9 has been shown to be particularly effective for proving theorems of relation algebras [7], a quantifier-free (or point-free) axiomatization of a fragment of relational logic. In this paper we propose a translation from Alloy specifications to fork algebras (an extension of relation algebras with the same expressive power as relational logic) which enables their unbounded verification in Prover9. This translation covers not only logic assertions, but also the structural aspects (namely type declarations), and was successfully implemented and applied to several examples

Watermarking FPGA Bitfile for Intellectual Property Protection

Intellectual property protection (IPP) of hardware designs is the most important requirement for many Field Programmable Gate Array (FPGA) intellectual property (IP) vendors. Digital watermarking has become an innovative technology for IPP in recent years. Existing watermarking techniques have successfully embedded watermark into IP cores. However, many of these techniques share two specific weaknesses: 1) They have extra overhead, and are likely to degrade performance of design; 2) vulnerability to removing attacks. We propose a novel watermarking technique to watermark FPGA bitfile for addressing these weaknesses. Experimental results and analysis show that the proposed technique incurs zero overhead and it is robust against removing attacks

Formal Analysis of CRT-RSA Vigilant's Countermeasure Against the BellCoRe Attack: A Pledge for Formal Methods in the Field of Implementation Security

In our paper at PROOFS 2013, we formally studied a few known countermeasures to protect CRT-RSA against the BellCoRe fault injection attack. However, we left Vigilant's countermeasure and its alleged repaired version by Coron et al. as future work, because the arithmetical framework of our tool was not sufficiently powerful. In this paper we bridge this gap and then use the same methodology to formally study both versions of the countermeasure. We obtain surprising results, which we believe demonstrate the importance of formal analysis in the field of implementation security. Indeed, the original version of Vigilant's countermeasure is actually broken, but not as much as Coron et al. thought it was. As a consequence, the repaired version they proposed can be simplified. It can actually be simplified even further as two of the nine modular verifications happen to be unnecessary. Fortunately, we could formally prove the simplified repaired version to be resistant to the BellCoRe attack, which was considered a "challenging issue" by the authors of the countermeasure themselves.Comment: arXiv admin note: substantial text overlap with arXiv:1401.817

A Practical Type Analysis for Verification of Modular Prolog Programs

Regular types are a powerful tool for computing very precise descriptive types for logic programs. However, in the context of real life, modular Prolog programs, the accurate results obtained by regular types often come at the price of efficiency. In this paper we propose a combination of techniques aimed at improving analysis efficiency in this context. As a first technique we allow optionally reducing the accuracy of inferred types by using only the types defined by the user or present in the libraries. We claim that, for the purpose of verifying type signatures given in the form of assertions the precision obtained using this approach is sufficient, and show that analysis times can be reduced significantly. Our second technique is aimed at dealing with situations where we would like to limit the amount of reanalysis performed, especially for library modules. Borrowing some ideas from polymorphic type systems, we show how to solve the problem by admitting parameters in type specifications. This allows us to compose new call patterns with some pre computed analysis info without losing any information. We argue that together these two techniques contribute to the practical and scalable analysis and verification of types in Prolog programs

Lightweight specification and analysis of dynamic systems with rich configurations

Model-checking is increasingly popular in the early phases of the software development process. To establish the correctness of a software design one must usually verify both structural and behavioral(or temporal) properties. Unfortunately, most specification languages, and accompanying model-checkers, excel only in analyzing either one or the other kind. This limits their ability to verify dynamic systems with rich configurations: systems whose state space is characterized by rich structural properties, but whose evolution is also expected to satisfy certain temporal properties.To address this problem, we first propose Electrum, an extension of the Alloy specification language with temporal logic operators, where both rich configurations and expressive temporal properties can easily be de fined. Two alternative model-checking techniques are then proposed, one bounded and the other unbounded, to verify systems expressed in this language, namely to verify that every desirable temporal property holds for every possible configuration.ERDF - European Regional Development Fund()info:eu-repo/semantics/publishedVersio

The use of data-mining for the automatic formation of tactics

This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques