Can NSEC5 be practical for DNSSEC deployments?

NSEC5 is proposed modification to DNSSEC that simultaneously guarantees two security properties: (1) privacy against offline zone enumeration, and (2) integrity of zone contents, even if an adversary compromises the authoritative nameserver responsible for responding to DNS queries for the zone. This paper redesigns NSEC5 to make it both practical and performant. Our NSEC5 redesign features a new fast verifiable random function (VRF) based on elliptic curve cryptography (ECC), along with a cryptographic proof of its security. This VRF is also of independent interest, as it is being standardized by the IETF and being used by several other projects. We show how to integrate NSEC5 using our ECC-based VRF into the DNSSEC protocol, leveraging precomputation to improve performance and DNS protocol-level optimizations to shorten responses. Next, we present the first full-fledged implementation of NSEC5—extending widely-used DNS software to present a nameserver and recursive resolver that support NSEC5—and evaluate their performance under aggressive DNS query loads. Our performance results indicate that our redesigned NSEC5 can be viable even for high-throughput scenarioshttps://eprint.iacr.org/2017/099.pdfFirst author draf

PALPAS - PAsswordLess PAssword Synchronization

Tools that synchronize passwords over several user devices typically store the encrypted passwords in a central online database. For encryption, a low-entropy, password-based key is used. Such a database may be subject to unauthorized access which can lead to the disclosure of all passwords by an offline brute-force attack. In this paper, we present PALPAS, a secure and user-friendly tool that synchronizes passwords between user devices without storing information about them centrally. The idea of PALPAS is to generate a password from a high entropy secret shared by all devices and a random salt value for each service. Only the salt values are stored on a server but not the secret. The salt enables the user devices to generate the same password but is statistically independent of the password. In order for PALPAS to generate passwords according to different password policies, we also present a mechanism that automatically retrieves and processes the password requirements of services. PALPAS users need to only memorize a single password and the setup of PALPAS on a further device demands only a one-time transfer of few static data.Comment: An extended abstract of this work appears in the proceedings of ARES 201

Forecasting the cost of processing multi-join queries via hashing for main-memory databases (Extended version)

Database management systems (DBMSs) carefully optimize complex multi-join queries to avoid expensive disk I/O. As servers today feature tens or hundreds of gigabytes of RAM, a significant fraction of many analytic databases becomes memory-resident. Even after careful tuning for an in-memory environment, a linear disk I/O model such as the one implemented in PostgreSQL may make query response time predictions that are up to 2X slower than the optimal multi-join query plan over memory-resident data. This paper introduces a memory I/O cost model to identify good evaluation strategies for complex query plans with multiple hash-based equi-joins over memory-resident data. The proposed cost model is carefully validated for accuracy using three different systems, including an Amazon EC2 instance, to control for hardware-specific differences. Prior work in parallel query evaluation has advocated right-deep and bushy trees for multi-join queries due to their greater parallelization and pipelining potential. A surprising finding is that the conventional wisdom from shared-nothing disk-based systems does not directly apply to the modern shared-everything memory hierarchy. As corroborated by our model, the performance gap between the optimal left-deep and right-deep query plan can grow to about 10X as the number of joins in the query increases.Comment: 15 pages, 8 figures, extended version of the paper to appear in SoCC'1