Team Cascade

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Section: Scientific Foundations

Provable Security

Since the beginning of public-key cryptography, with the seminal Diffie-Hellman paper  [70] , many suitable algorithmic problems for cryptography have been proposed and many cryptographic schemes have been designed, together with more or less heuristic proofs of their security relative to the intractability of the underlying problems. However, many of those schemes have thereafter been broken. The simple fact that a cryptographic algorithm withstood cryptanalytic attacks for several years has often been considered as a kind of validation procedure, but schemes may take a long time before being broken. An example is the Chor-Rivest cryptosystem  [68] , based on the knapsack problem, which took more than 10 years to be totally broken  [86] , whereas before this attack it was believed to be strongly secure. As a consequence, the lack of attacks at some time should never be considered as a full security validation of the proposal.

A completely different paradigm is provided by the concept of “provable” security. A significant line of research has tried to provide proofs in the framework of complexity theory (a.k.a. “reductionist” security proofs): the proofs provide reductions from a well-studied problem (factoring, RSA or the discrete logarithm) to an attack against a cryptographic protocol. At the beginning, researchers just tried to define the security notions required by actual cryptographic schemes, and then to design protocols which could achieve these notions. The techniques were directly derived from complexity theory, providing polynomial reductions. However, their aim was essentially theoretical. They were indeed trying to minimize the required assumptions on the primitives (one-way functions or permutations, possibly trapdoor, etc)  [74] , without considering practicality. Therefore, they just needed to design a scheme with polynomial-time algorithms, and to exhibit polynomial reductions from the basic mathematical assumption on the hardness of the underlying problem into an attack of the security notion, in an asymptotic way. However, such a result has no practical impact on actual security. Indeed, even with a polynomial reduction, one may be able to break the cryptographic protocol within a few hours, whereas the reduction just leads to an algorithm against the underlying problem which requires many years. Therefore, those reductions only prove the security when very huge (and thus maybe unpractical) parameters are in use, under the assumption that no polynomial time algorithm exists to solve the underlying problem.

For a few years, more efficient reductions have been expected, under the denomination of either “exact security”  [65] or “concrete security”  [79] , which provide more practical security results. The perfect situation is reached when one is able to prove that, from an attack, one can describe an algorithm against the underlying problem, with almost the same success probability within almost the same amount of time: “tight reductions”. We have then achieved “practical security”  [61] . Unfortunately, in many cases, even just provable security is at the cost of an important loss in terms of efficiency for the cryptographic protocol. Thus, some models have been proposed, trying to deal with the security of efficient schemes: some concrete objects are identified with ideal (or black-box) ones. For example, it is by now usual to identify hash functions with ideal random functions, in the so-called “random-oracle model”, informally introduced by Fiat and Shamir  [71] , and later formalized by Bellare and Rogaway  [64] . Similarly, block ciphers are identified with families of truly random permutations in the “ideal cipher model”  [62] . A few years ago, another kind of idealization was introduced in cryptography, the black-box group, where the group operation, in any algebraic group, is defined by a black-box: a new element necessarily comes from the addition (or the subtraction) of two already known elements. It is by now called the “generic model”  [75] , [85] . Some works even require several ideal models together to provide some new validations  [67] .

More recently, the new trend is to get provable security, without such ideal assumptions (there are currently a long list of publications showing “without random oracles” in their title), but under new and possibly stronger computational assumptions. As a consequence, a cryptographer has to deal with the three following important steps:

computational assumptions,

which are the foundations of the security. We thus need to have a strong evidence that the computational problems are reasonably hard to solve. We study several assumptions, by improving algorithms (attacks), and notably using lattice reductions. We furthermore contribute to the list of “potential” hard problems.

security model,

which makes precise the security notions one wants to achieve, as well as the means the adversary may be given. We contribute to this point, in several ways:

  • by providing a security model for many primitives and protocols, and namely group-oriented protocols, which involve many parties, but also many communications (group key exchange, group signatures, etc);

  • by enhancing some classical security models;

  • by considering new means for the adversary, such as side-channel information.


of new schemes/protocols, or more efficient, with additional features, etc.

security proof,

which consists in exhibiting a reduction.

For a long time, the security proofs by reduction used classical techniques from complexity theory, with a direct description of the reduction, and then a long and quite technical analysis for providing the probabilistic estimates. Such analysis is unfortunately error-prone. Victor Shoup proposed a nice way to organize the proofs, and eventually obtain the probabilities, using a sequence of games  [84] , [63] , [80] which highlights the computational assumptions, and splits the analysis in small independent problems. We early adopted and developed this technique, and namely in  [72] .

We applied this methodology to various kinds of systems, in order to achieve the highest security properties: authenticity, integrity, confidentiality, privacy, anonymity. Nevertheless, efficiency was also a basic requirement.


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