Proceedings of the 19th Workshop on Privacy in the Electronic Society最新文献_第2页

Proximity Tracing in an Ecosystem of Surveillance Capitalism 监视资本主义生态系统中的接近追踪

Proceedings of the 19th Workshop on Privacy in the Electronic Society Pub Date : 2020-09-13 DOI: 10.1145/3411497.3420219

Paul-Olivier Dehaye, Joel Reardon

{"title":"Proximity Tracing in an Ecosystem of Surveillance Capitalism","authors":"Paul-Olivier Dehaye, Joel Reardon","doi":"10.1145/3411497.3420219","DOIUrl":"https://doi.org/10.1145/3411497.3420219","url":null,"abstract":"Proximity tracing apps have been proposed as an aide in dealing with the COVID-19 crisis. Some of those apps leverage attenuation of Bluetooth beacons from mobile devices to build a record of proximate encounters between a pair of device owners. The underlying protocols are known to suffer from false positive and re-identification attacks. We present evidence that the attacker's difficulty in mounting such attacks has been overestimated. Indeed, an attacker leveraging a moderately successful app or SDK with Bluetooth and location access can eavesdrop and interfere with these proximity tracing systems at no hardware cost and perform these attacks against users who do not have this app or SDK installed. We describe concrete examples of actors who would be in a good position to execute such attacks. We further present a novel attack, which we call a biosurveillance attack, which allows the attacker to monitor the exposure risk of a smartphone user who installs their app or SDK but who does not use any contact tracing system and may falsely believe they have opted out of the system. Through traffic auditing with an instrumented testbed, we characterize precisely the behaviour of one such SDK that we found in a handful of apps---but installed on more than one hundred million mobile devices. Its behaviour is functionally indistinguishable from a re-identification or biosurveillance attack and capable of executing a false positive attack with minimal effort. We also discuss how easily an attacker could acquire a position conducive to such attacks, by leveraging the lax logic for granting permissions to apps in the Android framework: any app with some geolocation permission could acquire the necessary Bluetooth permission through an upgrade, without any additional user prompt. Finally we discuss motives for conducting such attacks.","PeriodicalId":329371,"journal":{"name":"Proceedings of the 19th Workshop on Privacy in the Electronic Society","volume":"373 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133947917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Randomness Concerns when Deploying Differential Privacy 部署差异隐私时的随机性问题

Proceedings of the 19th Workshop on Privacy in the Electronic Society Pub Date : 2020-09-06 DOI: 10.1145/3411497.3420211

S. Garfinkel, Philip Leclerc

{"title":"Randomness Concerns when Deploying Differential Privacy","authors":"S. Garfinkel, Philip Leclerc","doi":"10.1145/3411497.3420211","DOIUrl":"https://doi.org/10.1145/3411497.3420211","url":null,"abstract":"The U.S. Census Bureau is using differential privacy (DP) to protect confidential respondent data collected for the 2020 Decennial Census of Population & Housing. The Census Bureau's DP system is implemented in the Disclosure Avoidance System (DAS) and requires a source of random numbers. We estimate that the 2020 Census will require roughly 90TB of random bytes to protect the person and household tables. Although there are critical differences between cryptography and DP, they have similar requirements for randomness. We review the history of random number generation on deterministic computersømitt, including von Neumann's \"middle-square'' method, Mersenne Twister (MT19937) (the default NumPy random number generator, which we conclude is unacceptable for use in production privacy-preserving systems), and the Linux /dev/urandom device. We also review hardware random number generator schemes, including the use of so-called \"Lava Lamps'' and the Intel Secure Key RDRAND instruction. We finally present our plan for generating random bits in the Amazon Web Services (AWS) environment using AES-CTR-DRBG seeded by mixing bits from/dev/urandom and the Intel Secure Key RDSEED instruction, a compromise of our desire to rely on a trusted hardware implementation, the unease of our external reviewers in trusting a hardware-only implementation, and the need to generate so many random bits.","PeriodicalId":329371,"journal":{"name":"Proceedings of the 19th Workshop on Privacy in the Electronic Society","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130996214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Improving Frequency Estimation under Local Differential Privacy 局部差分隐私下改进的频率估计

Proceedings of the 19th Workshop on Privacy in the Electronic Society Pub Date : 2019-11-24 DOI: 10.1145/3411497.3420215

Milan Lopuhaä-Zwakenberg, Zitao Li, B. Škorić, Ninghui Li

引用次数: 5

SoK: Three Facets of Privacy Policies 隐私政策的三个方面

Proceedings of the 19th Workshop on Privacy in the Electronic Society Pub Date : 2019-08-19 DOI: 10.1145/3411497.3420216

Victor Morel, Raúl Pardo

引用次数: 9