A Secure and Fast Dispersal Storage Scheme Based on the Learning with Errors Problem

Data confidentiality and availability are of primary concern in data storage. Dispersal storage schemes achieve these two security properties by transforming the data into multiple codewords and dispersing them across multiple storage servers. Existing schemes achieve confidentiality and availability by various cryptographic and coding algorithms, but only under the assumption that an adversary cannot obtain more than a certain number of codewords. Meanwhile existing schemes are designed for storing archives. In this paper, we propose a novel dispersal storage scheme based on the learning with errors problem, known as storage with errors (SWE). SWE can resist even more powerful adversaries. Besides, SWE favorably supports dynamic data operations that are both efficient and secure, which is more practical for cloud storage. Furthermore, SWE achieves security at relatively low computational overhead, but the same storage cost compared with the state of the art. We also develop a prototype to validate and evaluate SWE. Analysis and experiments show that with proper configurations, SWE outperforms existing schemes in encoding/decoding speed

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead