H. Perl, Yassene Mohammed, Michael Brenner, Matthew Smith
{"title":"Fast confidential search for bio-medical data using Bloom filters and Homomorphic Cryptography","authors":"H. Perl, Yassene Mohammed, Michael Brenner, Matthew Smith","doi":"10.1109/eScience.2012.6404484","DOIUrl":null,"url":null,"abstract":"Data protection is a challenge when outsourcing medical analysis, especially if one is dealing with patient related data. While securing transfer channels is possible using encryption mechanisms, protecting the data during analyses is difficult as it usually involves processing steps on the plain data. A common use case in bioinformatics is when a scientist searches for a biological sequence of amino acids or DNA nucleotides in a library or database of sequences to identify similarities. Most such search algorithms are optimized for speed with less or no consideration for data protection. Fast algorithms are especially necessary because of the immense search space represented for instance by the genome or proteome of complex organisms. We propose a new secure exact term search algorithm based on Bloom filters. Our algorithm retains data privacy by using Obfuscated Bloom filters while maintaining the performance needed for real-life applications. The results can then be further aggregated using Homomorphic Cryptography to allow exact-match searching. The proposed system facilitates outsourcing exact term search of sensitive data to on-demand resources in a way which conforms to best practice of data protection.","PeriodicalId":6364,"journal":{"name":"2012 IEEE 8th International Conference on E-Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 8th International Conference on E-Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/eScience.2012.6404484","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
Data protection is a challenge when outsourcing medical analysis, especially if one is dealing with patient related data. While securing transfer channels is possible using encryption mechanisms, protecting the data during analyses is difficult as it usually involves processing steps on the plain data. A common use case in bioinformatics is when a scientist searches for a biological sequence of amino acids or DNA nucleotides in a library or database of sequences to identify similarities. Most such search algorithms are optimized for speed with less or no consideration for data protection. Fast algorithms are especially necessary because of the immense search space represented for instance by the genome or proteome of complex organisms. We propose a new secure exact term search algorithm based on Bloom filters. Our algorithm retains data privacy by using Obfuscated Bloom filters while maintaining the performance needed for real-life applications. The results can then be further aggregated using Homomorphic Cryptography to allow exact-match searching. The proposed system facilitates outsourcing exact term search of sensitive data to on-demand resources in a way which conforms to best practice of data protection.