PKI Safety Net (PKISN): Addressing the Too-Big-to-Be-Revoked Problem of the TLS Ecosystem

In a public-key infrastructure (PKI), clients must have an efficient and secure way to determine whether a certificate was revoked (by an entity considered as legitimate to do so), while preserving user privacy. A few certification authorities (CAs) are currently responsible for the issuance of the large majority of TLS certificates. These certificates are considered valid only if the certificate of the issuing CA is also valid. The certificates of these important CAs are effectively too big to be revoked, as revoking them would result in massive collateral damage. To solve this problem, we redesign the current revocation system with a novel approach that we call PKI Safety Net (PKISN), which uses publicly accessible logs to store certificates (in the spirit of Certificate Transparency) and revocations. The proposed system extends existing mechanisms, which enables simple deployment. Moreover, we present a complete implementation and evaluation of our scheme.Comment: IEEE EuroS&P 201

Performances of Cryptographic Accumulators

International audienceCryptographic accumulators are space/time efficient data structures used to verify if a value belongs to a set. They have found many applications in networking and distributed systems since their in- troduction by Benaloh and de Mare in 1993. Despite this popularity, there is currently no performance evaluation of the different existing de- signs. Symmetric and asymmetric accumulators are used likewise without any particular argument to support either of the design. We aim to es- tablish the speed of each design and their application's domains in terms of their size and the size of the values

New models for efficient authenticated dictionaries

International audienceWe propose models for data authentication which take into account the behavior of the clients who perform queries. Our models reduce the size of the authenticated proof when the frequency of the query corresponding to a given data is higher. Existing models implicitly assume the frequency distribution of queries to be uniform, but in reality, this distribution generally follows Zipf's law. Our models better reflect reality and the communication cost between clients and the server provider is reduced allowing the server to save bandwidth. The obtained gain on the average proof size compared to existing schemes depends on the parameter of Zipf law. The greater the parameter, the greater the gain. When the frequency distribution follows a perfect Zipf's law, we obtain a gain that can reach 26%. Experiments show the existence of applications for which Zipf parameter is greater than 1, leading to even higher gains