Achieving Secure and Efficient Cloud Search Services: Cross-Lingual Multi-Keyword Rank Search over Encrypted Cloud Data

Multi-user multi-keyword ranked search scheme in arbitrary language is a novel multi-keyword rank searchable encryption (MRSE) framework based on Paillier Cryptosystem with Threshold Decryption (PCTD). Compared to previous MRSE schemes constructed based on the k-nearest neighbor searcha-ble encryption (KNN-SE) algorithm, it can mitigate some draw-backs and achieve better performance in terms of functionality and efficiency. Additionally, it does not require a predefined keyword set and support keywords in arbitrary languages. However, due to the pattern of exact matching of keywords in the new MRSE scheme, multilingual search is limited to each language and cannot be searched across languages. In this pa-per, we propose a cross-lingual multi-keyword rank search (CLRSE) scheme which eliminates the barrier of languages and achieves semantic extension with using the Open Multilingual Wordnet. Our CLRSE scheme also realizes intelligent and per-sonalized search through flexible keyword and language prefer-ence settings. We evaluate the performance of our scheme in terms of security, functionality, precision and efficiency, via extensive experiments

Secure buyer - seller watermarking protocol

In the existing watermarking protocols, a trusted third party (TTP) is introduced to guarantee that a protocol is fair to both the seller and buyer in a digital content transaction. However, the TTP decreases the security and affects the protocol implementation. To address this issue, in this article a secure buyer&ndash;seller watermarking protocol without the assistance of a TTP is proposed in which there are only two participants, a seller and a buyer. Based on the idea of sharing a secret, a watermark embedded in digital content to trace piracy is composed of two pieces of secret information, one produced by the seller and one by the buyer. Since neither knows the exact watermark, the buyer cannot remove the watermark from watermarked digital content, and at the same time the seller cannot fabricate piracy to frame an innocent buyer. In other words, the proposed protocol can trace piracy and protect the customer&rsquo;s rights. In addition, because no third party is introduced into the proposed protocol, the problem of a seller (or a buyer) colluding with a third party to cheat the buyer (or the seller), namely, the conspiracy problem, can be avoided.<br /

Fast and Private Genomic Testing for Disease Susceptibility

Advances in DNA sequencing are bringing mass computational genomic testing increasingly closer to reality. The sensitivity of genetic data, however, prompts the need for carefully protecting patients' privacy. Also, it is crucial to conceal the test's specifics, which often constitute a pharmaceutical company's trade secret. This paper presents two cryptographic protocols for privately assessing a patient's genetic susceptibility to a disease, computing a weighted average of patient's genetic markers (the ``SNPs'') and their importance factor. We build on the architecture introduced by Ayday et al. but point out an important limitation of their model, namely, that the protocol leaks which and how many SNPs are tested. Then, we demonstrate that an alternative SNP encoding can simplify (private) computations, and make patient-side computation on a smartcard device extremely efficient. A second protocol variant, based on secret sharing, further reduces online computation

Privacy-preserving genomic testing in the clinic: A model using HIV treatment

Purpose:The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics.Methods:We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers.Results:A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%.Conclusions:The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine. © 2015 American College of Medical Genetics and Genomics

Privacy-Aware Processing of Biometric Templates by Means of Secure Two-Party Computation

The use of biometric data for person identification and access control is gaining more and more popularity. Handling biometric data, however, requires particular care, since biometric data is indissolubly tied to the identity of the owner hence raising important security and privacy issues. This chapter focuses on the latter, presenting an innovative approach that, by relying on tools borrowed from Secure Two Party Computation (STPC) theory, permits to process the biometric data in encrypted form, thus eliminating any risk that private biometric information is leaked during an identification process. The basic concepts behind STPC are reviewed together with the basic cryptographic primitives needed to achieve privacy-aware processing of biometric data in a STPC context. The two main approaches proposed so far, namely homomorphic encryption and garbled circuits, are discussed and the way such techniques can be used to develop a full biometric matching protocol described. Some general guidelines to be used in the design of a privacy-aware biometric system are given, so as to allow the reader to choose the most appropriate tools depending on the application at hand