Proceedings of the 13th Workshop on Privacy in the Electronic Society最新文献_第3页

Reconciling Utility with Privacy in Genomics 调和基因组学中的效用与隐私

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665945

Mathias Humbert, Erman Ayday, J. Hubaux, A. Telenti

{"title":"Reconciling Utility with Privacy in Genomics","authors":"Mathias Humbert, Erman Ayday, J. Hubaux, A. Telenti","doi":"10.1145/2665943.2665945","DOIUrl":"https://doi.org/10.1145/2665943.2665945","url":null,"abstract":"Direct-to-consumer genetic testing makes it possible for everyone to learn their genome sequences. In order to contribute to medical research, a growing number of people publish their genomic data on the Web, sometimes under their real identities. However, this is at odds not only with their own privacy but also with the privacy of their relatives. The genomes of relatives being highly correlated, some family members might be opposed to revealing any of the family's genomic data. In this paper, we study the trade-off between utility and privacy in genomics. We focus on the most relevant kind of variants, namely single nucleotide polymorphisms (SNPs). We take into account the fact that the SNPs of an individual contain information about the SNPs of his family members and that SNPs are correlated with each other. Furthermore, we assume that SNPs can have different utilities in medical research and different levels of sensitivity for individuals. We propose an obfuscation mechanism that enables the genomic data to be publicly available for research, while protecting the genomic privacy of the individuals in a family. Our genomic-privacy preserving mechanism relies upon combinatorial optimization and graphical models to optimize utility and meet privacy requirements. We also present an extension of the optimization algorithm to cope with the non-linear constraints induced by the correlations between SNPs. Our results on real data show that our proposed technique maximizes the utility for genomic research and satisfies family members' privacy constraints.","PeriodicalId":408627,"journal":{"name":"Proceedings of the 13th Workshop on Privacy in the Electronic Society","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122056741","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: 38

Identifying Webbrowsers in Encrypted Communications 在加密通信中识别web浏览器

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665968

Jiangmin Yu, Eric Chan-Tin

引用次数: 8

Exploiting Users' Inconsistent Preferences in Online Social Networks to Discover Private Friendship Links 利用在线社交网络中用户不一致的偏好来发现私人友谊链接

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665956

Lei Jin, Hassan Takabi, Xuelian Long, J. Joshi

{"title":"Exploiting Users' Inconsistent Preferences in Online Social Networks to Discover Private Friendship Links","authors":"Lei Jin, Hassan Takabi, Xuelian Long, J. Joshi","doi":"10.1145/2665943.2665956","DOIUrl":"https://doi.org/10.1145/2665943.2665956","url":null,"abstract":"In a social network system, a friendship relation between two users is usually represented by an undirected link and it is visible in both users' friend lists. Such a dual visibility of a friendship link may raise privacy threats. This is because both the users of a friendship link can separately control its visibility to other users and their preferences of sharing such a friendship link may not be consistent. Even if one of them conceals the friendship link from a third user, that third user may find the link through the other user's friend list. In addition, as most social network users allow their friends to see their friend lists, an adversary can exploit these inconsistent policies caused by users' conflicting preferences to identify and infer many of a targeted user's friends and even reconstruct the topology of an entire social network. In this paper, we propose, characterize and evaluate such an attack referred as the Friendship Identification and Inference (FII) attack. In an FII attack scenario, an adversary first accumulates the initial attack relevant information based on the friend lists visible to him in a social network. Then, he utilizes this information to identify and infer a target's friends using a random walk based approach. We formally define the attack and present the attack steps, the attack algorithm and various attack schemes. Our experimental results using three real social network datasets show that FII attacks are effective in inferring private friendship links of a target and predicting the topology of the social network. Currently, most popular social network systems, such as Facebook, LinkedIn and Foursquare, are susceptible to FII attacks.","PeriodicalId":408627,"journal":{"name":"Proceedings of the 13th Workshop on Privacy in the Electronic Society","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123554607","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: 0

FARB: Fast Anonymous Reputation-Based Blacklisting without TTPs FARB:快速匿名基于信誉的黑名单，没有https

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665947

Li Xi, D. Feng

引用次数: 10

Prolonging the Hide-and-Seek Game: Optimal Trajectory Privacy for Location-Based Services 延长捉迷藏游戏:基于位置的服务的最优轨迹隐私

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-09-05 DOI: 10.1145/2665943.2665946

George Theodorakopoulos, R. Shokri, C. Troncoso, J. Hubaux, J. Boudec

{"title":"Prolonging the Hide-and-Seek Game: Optimal Trajectory Privacy for Location-Based Services","authors":"George Theodorakopoulos, R. Shokri, C. Troncoso, J. Hubaux, J. Boudec","doi":"10.1145/2665943.2665946","DOIUrl":"https://doi.org/10.1145/2665943.2665946","url":null,"abstract":"Human mobility is highly predictable. Individuals tend to only visit a few locations with high frequency, and to move among them in a certain sequence reflecting their habits and daily routine. This predictability has to be taken into account in the design of location privacy preserving mechanisms (LPPMs) in order to effectively protect users when they expose their whereabouts to location-based services (LBSs) continuously. In this paper, we describe a method for creating LPPMs tailored to a user's mobility profile taking into her account privacy and quality of service requirements. By construction, our LPPMs take into account the sequential correlation across the user's exposed locations, providing the maximum possible trajectory privacy, i.e., privacy for the user's past, present location, and expected future locations. Moreover, our LPPMs are optimal against a strategic adversary, i.e., an attacker that implements the strongest inference attack knowing both the LPPM operation and the user's mobility profile. The optimality of the LPPMs in the context of trajectory privacy is a novel contribution, and it is achieved by formulating the LPPM design problem as a Bayesian Stackelberg game between the user and the adversary. An additional benefit of our formal approach is that the design parameters of the LPPM are chosen by the optimization algorithm.","PeriodicalId":408627,"journal":{"name":"Proceedings of the 13th Workshop on Privacy in the Electronic Society","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130411575","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: 60

An Automated Social Graph De-anonymization Technique 自动社交图去匿名化技术

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-08-06 DOI: 10.1145/2665943.2665960

K. Sharad, G. Danezis

引用次数: 57

Proceedings of the 13th Workshop on Privacy in the Electronic Society 第十三届电子社会私隐研讨会论文集

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 1900-01-01 DOI: 10.1145/2665943

Gail-Joon Ahn, Anupam Datta

引用次数: 3