Proceedings of the 13th Workshop on Privacy in the Electronic Society最新文献_第2页

Privacy Detective: Detecting Private Information and Collective Privacy Behavior in a Large Social Network 隐私侦探:大型社交网络中隐私信息和集体隐私行为的检测

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665958

Aylin Caliskan, J. Walsh, R. Greenstadt

{"title":"Privacy Detective: Detecting Private Information and Collective Privacy Behavior in a Large Social Network","authors":"Aylin Caliskan, J. Walsh, R. Greenstadt","doi":"10.1145/2665943.2665958","DOIUrl":"https://doi.org/10.1145/2665943.2665958","url":null,"abstract":"Detecting the presence and amount of private information being shared in online media is the first step towards analyzing information revealing habits of users in social networks and a useful method for researchers to study aggregate privacy behavior. In this work, we aim to find out if text contains private content by using our novel learning based approach `privacy detective' that combines topic modeling, named entity recognition, privacy ontology, sentiment analysis, and text normalization to represent privacy features. Privacy detective investigates a broader range of privacy concerns compared to previous approaches that focus on keyword searching or profile related properties. We collected 500,000 tweets from 100,000 Twitter users along with other information such as tweet linkages and follower relationships. We reach 95.45% accuracy in a two-class task classifying Twitter users who do not reveal much private information and Twitter users who share sensitive information. We score timelines according to three privacy levels after having Amazon Mechanical Turk (AMT) workers annotate collected tweets according to privacy categories. Supervised machine learning classification results on these annotations reach 69.63% accuracy on a three-class task. Inter-annotator agreement on timeline privacy scores between various AMT workers and our classifiers fall under the same positive agreement level. Additionally, we show that a user's privacy level is correlated with her friends' privacy scores and also with the privacy scores of people mentioned in her text but not with the number of her followers. As such, privacy in social networks appear to be socially constructed, which can have great implications for privacy enhancing technologies and educational interventions.","PeriodicalId":408627,"journal":{"name":"Proceedings of the 13th Workshop on Privacy in the Electronic Society","volume":"17 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":"124783611","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: 81

Adaptive Conflict Resolution Mechanism for Multi-party Privacy Management in Social Media 社交媒体中多方隐私管理的自适应冲突解决机制

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665964

J. Such, N. Criado

引用次数: 22

What Deters Jane from Preventing Identification and Tracking on the Web? 是什么阻止了简在网络上阻止身份识别和跟踪?

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665963

Fatemeh Shirazi, M. Volkamer

{"title":"What Deters Jane from Preventing Identification and Tracking on the Web?","authors":"Fatemeh Shirazi, M. Volkamer","doi":"10.1145/2665943.2665963","DOIUrl":"https://doi.org/10.1145/2665943.2665963","url":null,"abstract":"Recent revelations about surveillance by several institutions and de-identification can be expected to have increased public awareness of identification- and tracking-related privacy threats. It is reasonable to expect that the general public has started using corresponding privacy protection mechanisms. Our goal with this research was to determine whether they actually do this. If not, we wanted to explore possible explanations for not uptaken such privacy-protecting countermeasures. We interviewed 20 (mainly lay) people and found that our interviewees did not proactively try to prevent being identified and tracked. We identified seven different types of explanations. Including a number of misconceptions which might explain this puzzling level of apathy. The participants demonstrated confusion between different kinds of sensitive data; and displayed a confusion between the semantics of `privacy' and `security'. The findings also indicate that security being compromised, resulting in losing money for example, is more concrete and more easily brought to mind than privacy-related problems. In terms of the consequences of surveillance, the most commonly cited outcome is the receipt of personalized advertisements, which many consider beneficial. Potentially negative impacts of identification and tracking is often assumed to not occur to them. Our interviews also pointed out a gap between passive and active knowledge about identification and tracking techniques, their impact on privacy and countermeasures against them.","PeriodicalId":408627,"journal":{"name":"Proceedings of the 13th Workshop on Privacy in the Electronic Society","volume":"49 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":"126169393","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: 31

Privacy-Preserving Whole Genome Sequence Processing through Proxy-Aided ORAM 基于代理辅助ORAM的隐私保护全基因组序列处理

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665962

Nikolaos P. Karvelas, Andreas Peter, S. Katzenbeisser, Erik Tews, K. Hamacher

引用次数: 35

Pretty Bad Privacy: Pitfalls of DNS Encryption 相当糟糕的隐私:DNS加密的陷阱

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665959

Haya Schulmann

{"title":"Pretty Bad Privacy: Pitfalls of DNS Encryption","authors":"Haya Schulmann","doi":"10.1145/2665943.2665959","DOIUrl":"https://doi.org/10.1145/2665943.2665959","url":null,"abstract":"As awareness for privacy of Domain Name System (DNS) is increasing, a number of mechanisms for encryption of DNS packets were proposed. We study the prominent defences, focusing on the privacy guarantees, interoperability with the DNS infrastructure, and the efficiency overhead. In particular: •We explore dependencies in DNS and show techniques that utilise side channel leaks, due to transitive trust, allowing to infer information about the target domain in an encrypted DNS packet. •We examine common DNS servers configurations and show that the proposals are expected to encounter deployment obstacles with (at least) 38% of 50K-top Alexa domains and (at least) 12% of the top-level domains (TLDs), and will disrupt the DNS functionality and availability for clients. •We show that due to the non-interoperability with the caches, the proposals for end-to-end encryption may have a prohibitive traffic overhead on the name servers. Our work indicates that further study may be required to adjust the proposals to stand up to their security guarantees, and to make them suitable for the common servers' configurations in the DNS infrastructure. Our study is based on collection and analysis of the DNS traffic of 50K-top Alexa domains and 568 TLDs.","PeriodicalId":408627,"journal":{"name":"Proceedings of the 13th Workshop on Privacy in the Electronic Society","volume":"205 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":"132976782","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: 43

Privacy-PAC: Privacy-Enhanced Physical Access Control Privacy-PAC:隐私增强物理访问控制

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665969

J. Hajny, Petr Dzurenda, L. Malina

引用次数: 12

Glove: A Bespoke Website Fingerprinting Defense 手套:一个定制的网站指纹防御

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665950

Rishab Nithyanand, Xiang Cai, Rob Johnson

引用次数: 80

CS-BuFLO: A Congestion Sensitive Website Fingerprinting Defense CS-BuFLO:一个对拥塞敏感的网站指纹防御

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665949

Xiang Cai, Rishab Nithyanand, Rob Johnson

引用次数: 149

Secure Evaluation Protocol for Personalized Medicine 个性化医疗安全评估协议

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665967

Mentari Djatmiko, Arik Friedman, R. Boreli, Felix Lawrence, Brian Thorne, Stephen Hardy

引用次数: 20

ProfileGuard: Privacy Preserving Obfuscation for Mobile User Profiles ProfileGuard:隐私保护混淆的移动用户配置文件

Proceedings of the 13th Workshop on Privacy in the Electronic Society Pub Date : 2014-11-03 DOI: 10.1145/2665943.2665961

Imdad Ullah, R. Boreli, S. Kanhere, Sanjay Chawla

{"title":"ProfileGuard: Privacy Preserving Obfuscation for Mobile User Profiles","authors":"Imdad Ullah, R. Boreli, S. Kanhere, Sanjay Chawla","doi":"10.1145/2665943.2665961","DOIUrl":"https://doi.org/10.1145/2665943.2665961","url":null,"abstract":"Analytics companies have become an integral part of the mobile advertising industry, enabling successful user targeting via user profiles, derived from the mobile apps installed by specific users. This poses a threat to privacy of such users, when apps indicating sensitive information, e.g., a gaming app showing a gambling problem, are the basis for profiling. In this paper, we propose a ProfileGuard, novel app-based obfuscation mechanism to remove the dominance (prevalence amongst the interest categories present in a user profile) of selected private user profile interest categories. We show, based on extensive experimental evaluation using 2700 Android apps during a 9 month test campaign, that the best trade-off between the level of effort required by the obfuscating system and the resulting privacy protection can be achieved by choosing the obfuscating apps based on similarity with user's existing apps (while ensuring that the selected apps belong to a non-private category). We implement a POC ProfileGuard app to demonstrate the feasibility of an automated obfuscation mechanism. We also provide insights into the broad Google AdMob profiling rules, showing that there is a deterministic mapping of individual apps to profile interests, that profiles based on multiple apps represent a union of individual app profiles and that there is a minimum level of activity necessary for AdMob to build a stable user profile. Finally, we show the resulting effect of obfuscation on the received ads, demonstrating that modifying user profiles to include a richer set of interests results in correspondingly more diverse received ads.","PeriodicalId":408627,"journal":{"name":"Proceedings of the 13th Workshop on Privacy in the Electronic Society","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133593559","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