{"title":"压缩感知测量的保密性","authors":"Y. Rachlin, D. Baron","doi":"10.1109/ALLERTON.2008.4797641","DOIUrl":null,"url":null,"abstract":"Results in compressed sensing describe the feasibility of reconstructing sparse signals using a small number of linear measurements. In addition to compressing the signal, do these measurements provide secrecy? This paper considers secrecy in the context of an adversary that does not know the measurement matrix used to encrypt the signal. We demonstrate that compressed sensing-based encryption does not achieve Shannon's definition of perfect secrecy, but can provide a computational guarantee of secrecy.","PeriodicalId":120561,"journal":{"name":"2008 46th Annual Allerton Conference on Communication, Control, and Computing","volume":"214 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"335","resultStr":"{\"title\":\"The secrecy of compressed sensing measurements\",\"authors\":\"Y. Rachlin, D. Baron\",\"doi\":\"10.1109/ALLERTON.2008.4797641\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Results in compressed sensing describe the feasibility of reconstructing sparse signals using a small number of linear measurements. In addition to compressing the signal, do these measurements provide secrecy? This paper considers secrecy in the context of an adversary that does not know the measurement matrix used to encrypt the signal. We demonstrate that compressed sensing-based encryption does not achieve Shannon's definition of perfect secrecy, but can provide a computational guarantee of secrecy.\",\"PeriodicalId\":120561,\"journal\":{\"name\":\"2008 46th Annual Allerton Conference on Communication, Control, and Computing\",\"volume\":\"214 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"335\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 46th Annual Allerton Conference on Communication, Control, and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ALLERTON.2008.4797641\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 46th Annual Allerton Conference on Communication, Control, and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ALLERTON.2008.4797641","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Results in compressed sensing describe the feasibility of reconstructing sparse signals using a small number of linear measurements. In addition to compressing the signal, do these measurements provide secrecy? This paper considers secrecy in the context of an adversary that does not know the measurement matrix used to encrypt the signal. We demonstrate that compressed sensing-based encryption does not achieve Shannon's definition of perfect secrecy, but can provide a computational guarantee of secrecy.