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Ciphertext-policy attribute-based encryption, denoted by CP-ABE, extends identity based encryption by taking a set of attributes as users’ public key which enables scalable access control over outsourced data in cloud storage services. However, a decryption key corresponding to an attribute set may be owned by multiple users. Then, malicious users are subjectively willing to share their decryption keys for profits. In addition, the authority who issues decryption keys in CP-ABE system is able to generate arbitrary decryption key for any (including unauthorized) user. Key abuses of both malicious users and the authority have been regarded as one of the major obstacles to deploy CP-ABE system in real-world commercial applications. In this paper, we try to solve these two kinds of key abuses in CP-ABE system, and propose two accountable CP-ABE schemes supporting any LSSS realizable access structures. Two proposed accountable CP-ABE schemes allow any third party (with the help of authorities if necessary) to publicly verify the identity of an exposed decryption key, allow an auditor to publicly audit whether a malicious user or authorities should be responsible for an exposed decryption key, and the key abuser can’t deny it. At last, we prove the two schemes can achieve publicly verifiable traceability and accountability.

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In recent years, there have been many studies utilizing DNA methylome data to answer fundamental biological questions. Bisulfite sequencing (BS-seq) has enabled measurement of a genome-wide absolute level of DNA methylation at single-nucleotide resolution. However, due to the ambiguity introduced by bisulfite-treatment, the aligning process especially in large-scale epigenetic research is still considered a huge burden. We present Cloud-BS, an efficient BS-seq aligner designed for parallel execution on a distributed environment. Utilizing Apache Hadoop framework, Cloud-BS splits sequencing reads into multiple blocks and transfers them to distributed nodes. By designing each aligning procedure into separate map and reducing tasks while an internal key-value structure is optimized based on the MapReduce programming model, the algorithm significantly improves alignment performance without sacrificing mapping accuracy. In addition, Cloud-BS minimizes the innate burden of configuring a distributed environment by providing a pre-configured cloud image. Cloud-BS shows significantly improved bisulfite alignment performance compared to other existing BS-seq aligners. We believe our algorithm facilitates large-scale methylome data analysis. The algorithm is freely available at https://paryoja.github.io/Cloud-BS/.