Private-keyless access, serving as an implementation mechanism within policy-based data custody, enables control and authorization based on predefined policies without requiring users to possess a private key. The unforgeability of both user identity and authorization decisions is ensured by the cryptosystem in private-keyless data custody. Hereby, we introduce a novel Cryptographic Resource Enabled Framework (CREF) to simplify key management, enhance security, and increase flexibility of access authorization. Firstly, in the data custody phase, data resource and its session key are uploaded in ciphertext form to CREF, and the access authorization complies with multiple policies designated by the provider. Secondly, in the dynamic authorization phase, traditional keys or keycards are replaced with adequate one-time attribute credentials issued by multiple authorities. CREF makes dynamically cryptographic policy decision according to the credentials and the cryptographic policy (cryptopolicy). Technically, we design the Credentials-Driven Cryptosystem (CDC) over ideal lattice to build anti-quantum confidence for CREF. In CDC, preimage Gaussian sampler is adopted to sample short vector as real-time attribute credential instead of user's private key. Small policy matrix is implemented to convert monotone policies into optimized cryptopolicies in order to reduce accumulated error. The security analysis confirms that both credentials and cryptopolicies are existentially unforgeable, ensuring the semantic security of the whole CREF. Experimental results indicate CREF has lower storage and computational costs than existing schemes. Meanwhile, with policies' continuous improvements as system evolves, CREF only need to select a suitable policy among multiple candidates to make authorization decisions without having to reencrypt data.

In this paper, we propose a genetic algorithm for solving the shortest vector problem (SVP) based on sparse representation of short lattice vectors, which, we prove, can guarantee finding the shortest lattice vector under a Markov analysis. With some heuristic improvements (local search and heuristic pruning), the SVP genetic algorithm, by experimental results, outperforms other SVP algorithms, like the famous Kannan-Helfrich algorithm under SVP challenge benchmarks. In summary, we, for the first time, adopt the genetic algorithm in solving the shortest vector problem, based on which lattice-based cryptosystem is as a promising candidate for post-quantum cryptography.

The NTRU cryptosystem is the most practical scheme known to date and has drawn considerable interest, which depends on three integer parameters (N, p, q) and four sets Lf, Lg, Lr, Lm of polynomials of degree N − 1 with small integer coefficients. We choose p, q such that gcd(p, q) = 1 and p is much smaller than q, denote the ring Z[x]/(xN -- 1) by R and the multiplication in R by *.