{"title":"Energy obfuscation for compressive encryption and processing","authors":"Matteo Testa, T. Bianchi, E. Magli","doi":"10.1109/WIFS.2017.8267649","DOIUrl":null,"url":null,"abstract":"Compressed Sensing enables both computationally secure encryption and signal processing in the compressed domain. Even though these characteristics have always been considered in separate fashion, in this paper we propose a novel method that takes into account these features jointly. As a result we obtain provable secrecy guarantees and enable fast signal processing. In more detail, we show that it is possible to perform anomaly detection relying on the measurements information leakage. At the same time, we can prevent attackers trying to obtain confidential data by obfuscating the information leakage. We show the effectiveness of such method through theoretical bounds and numerical experiments.","PeriodicalId":305837,"journal":{"name":"2017 IEEE Workshop on Information Forensics and Security (WIFS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Workshop on Information Forensics and Security (WIFS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WIFS.2017.8267649","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Compressed Sensing enables both computationally secure encryption and signal processing in the compressed domain. Even though these characteristics have always been considered in separate fashion, in this paper we propose a novel method that takes into account these features jointly. As a result we obtain provable secrecy guarantees and enable fast signal processing. In more detail, we show that it is possible to perform anomaly detection relying on the measurements information leakage. At the same time, we can prevent attackers trying to obtain confidential data by obfuscating the information leakage. We show the effectiveness of such method through theoretical bounds and numerical experiments.