Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium最新文献

Compact and Divisible E-Cash with Threshold Issuance 具有阈值发行的紧凑可分割电子现金

Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium Pub Date : 2023-10-01 DOI: 10.56553/popets-2023-0116

Alfredo Rial, Ania M. Piotrowska

引用次数: 0

On the Robustness of Topics API to a Re-Identification Attack 主题API对重新识别攻击的鲁棒性研究

Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium Pub Date : 2023-10-01 DOI: 10.56553/popets-2023-0098

Nikhil Jha, Martino Trevisan, Emilio Leonardi, Marco Mellia

{"title":"On the Robustness of Topics API to a Re-Identification Attack","authors":"Nikhil Jha, Martino Trevisan, Emilio Leonardi, Marco Mellia","doi":"10.56553/popets-2023-0098","DOIUrl":"https://doi.org/10.56553/popets-2023-0098","url":null,"abstract":"Web tracking through third-party cookies is considered a threat to users' privacy and is supposed to be abandoned in the near future. Recently, Google proposed the Topics API framework as a privacy-friendly alternative for behavioural advertising. Using this approach, the browser builds a user profile based on navigation history, which advertisers can access. The Topics API has the possibility of becoming the new standard for behavioural advertising, thus it is necessary to fully understand its operation and find possible limitations. This paper evaluates the robustness of the Topics API to a re-identification attack where an attacker reconstructs the user profile by accumulating user's exposed topics over time to later re-identify the same user on a different website. Using real traffic traces and realistic population models, we find that the Topics API mitigates but cannot prevent re-identification to take place, as there is a sizeable chance that a user's profile is unique within a website's audience. Consequently, the probability of correct re-identification can reach 15-17%, considering a pool of 1,000 users. We offer the code and data we use in this work to stimulate further studies and the tuning of the Topic API parameters.","PeriodicalId":74556,"journal":{"name":"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135010612","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

DP-SIPS: A simpler, more scalable mechanism for differentially private partition selection DP-SIPS:用于区分私有分区选择的更简单、更可扩展的机制

Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium Pub Date : 2023-10-01 DOI: 10.56553/popets-2023-0109

Marika Swanberg, Damien Desfontaines, Samuel Haney

引用次数: 0

Editors' Introduction 编辑的介绍

Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium Pub Date : 2023-10-01 DOI: 10.56553/popets-2023-0094

Michelle Mazurek, Micah Sherr

引用次数: 0

Privacy-Preserving Federated Recurrent Neural Networks 隐私保护联邦递归神经网络

Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium Pub Date : 2023-10-01 DOI: 10.56553/popets-2023-0122

Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat, Jean-Pierre Hubaux

{"title":"Privacy-Preserving Federated Recurrent Neural Networks","authors":"Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat, Jean-Pierre Hubaux","doi":"10.56553/popets-2023-0122","DOIUrl":"https://doi.org/10.56553/popets-2023-0122","url":null,"abstract":"We present RHODE, a novel system that enables privacy-preserving training of and prediction on Recurrent Neural Networks (RNNs) in a cross-silo federated learning setting by relying on multiparty homomorphic encryption. RHODE preserves the confidentiality of the training data, the model, and the prediction data; and it mitigates federated learning attacks that target the gradients under a passive-adversary threat model. We propose a packing scheme, multi-dimensional packing, for a better utilization of Single Instruction, Multiple Data (SIMD) operations under encryption. With multi-dimensional packing, RHODE enables the efficient processing, in parallel, of a batch of samples. To avoid the exploding gradients problem, RHODE provides several clipping approximations for performing gradient clipping under encryption. We experimentally show that the model performance with RHODE remains similar to non-secure solutions both for homogeneous and heterogeneous data distributions among the data holders. Our experimental evaluation shows that RHODE scales linearly with the number of data holders and the number of timesteps, sub-linearly and sub-quadratically with the number of features and the number of hidden units of RNNs, respectively. To the best of our knowledge, RHODE is the first system that provides the building blocks for the training of RNNs and its variants, under encryption in a federated learning setting.","PeriodicalId":74556,"journal":{"name":"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135010614","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

Lessons in VCR Repair: Compliance of Android App Developers with the California Consumer Privacy Act (CCPA) VCR修复课程:Android应用程序开发人员与加州消费者隐私法案(CCPA)的合规性

Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium Pub Date : 2023-07-01 DOI: 10.56553/popets-2023-0072

Nikita Samarin, Shayna Kothari, Zaina Siyed, Oscar Bjorkman, Reena Yuan, Primal Wijesekera, Noura Alomar, Jordan Fischer, Chris Hoofnagle, Serge Egelman

{"title":"Lessons in VCR Repair: Compliance of Android App Developers with the California Consumer Privacy Act (CCPA)","authors":"Nikita Samarin, Shayna Kothari, Zaina Siyed, Oscar Bjorkman, Reena Yuan, Primal Wijesekera, Noura Alomar, Jordan Fischer, Chris Hoofnagle, Serge Egelman","doi":"10.56553/popets-2023-0072","DOIUrl":"https://doi.org/10.56553/popets-2023-0072","url":null,"abstract":"The California Consumer Privacy Act (CCPA) provides California residents with a range of enhanced privacy protections and rights. Our research investigated the extent to which Android app developers comply with the provisions of the CCPA that require them to provide consumers with accurate privacy notices and respond to \"verifiable consumer requests\" (VCRs) by disclosing personal information that they have collected, used, or shared about consumers for a business or commercial purpose. We compared the actual network traffic of 109 apps that we believe must comply with the CCPA to the data that apps state they collect in their privacy policies and the data contained in responses to \"right to know\" requests that we submitted to the app's developers. Of the 69 app developers who substantively replied to our requests, all but one provided specific pieces of personal data (as opposed to only categorical information). However, a significant percentage of apps collected information that was not disclosed, including identifiers (55 apps, 80%), geolocation data (21 apps, 30%), and sensory data (18 apps, 26%) among other categories. We discuss improvements to the CCPA that could help app developers comply with \"right to know\" requests and other related regulations.","PeriodicalId":74556,"journal":{"name":"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135111117","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

Editors' Introduction 编辑的介绍

Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium Pub Date : 2023-07-01 DOI: 10.56553/popets-2023-0066

Michelle Mazurek, Micah Sherr

引用次数: 0

Story Beyond the Eye: Glyph Positions Break PDF Text Redaction 超越眼睛的故事:字形位置打破PDF文本编校

Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium Pub Date : 2023-07-01 DOI: 10.56553/popets-2023-0069

Maxwell Bland, Anushya Iyer, Kirill Levchenko

{"title":"Story Beyond the Eye: Glyph Positions Break PDF Text Redaction","authors":"Maxwell Bland, Anushya Iyer, Kirill Levchenko","doi":"10.56553/popets-2023-0069","DOIUrl":"https://doi.org/10.56553/popets-2023-0069","url":null,"abstract":"In this work we find that many current redactions of PDF text are insecure due to non-redacted character positioning information. In particular, subpixel-sized horizontal shifts in redacted and non-redacted characters can be recovered and used to effectively deredact first and last names. Unfortunately these findings affect redactions where the text underneath the black box is removed from the PDF. We demonstrate these findings by performing a comprehensive vulnerability assessment of common PDF redaction types. We examine 11 popular PDF redaction tools, including Adobe Acrobat, and find that they leak information about redacted text. We also effectively deredact hundreds of real-world PDF redactions, including those found in OIG investigation reports and FOIA responses. To correct the problem, we have released open source algorithms to fix vulnerable redactions and reduce the amount of information leaked by nonexcising redactions (where the text underneath the redaction is copy-pastable). We have also notified the developers of the studied redaction tools. We have notified the Office of Inspector General, the Free Law Project, PACER, Adobe, Microsoft, and the US Department of Justice. We are working with several of these groups to prevent our discoveries from being used for malicious purposes.","PeriodicalId":74556,"journal":{"name":"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135960827","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: 2

Blocking JavaScript Without Breaking the Web: An Empirical Investigation 在不破坏网络的情况下阻止JavaScript:一项实证调查

Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium Pub Date : 2023-07-01 DOI: 10.56553/popets-2023-0087

Abdul Haddi Amjad, Zubair Shafiq, Muhammad Ali Gulzar

{"title":"Blocking JavaScript Without Breaking the Web: An Empirical Investigation","authors":"Abdul Haddi Amjad, Zubair Shafiq, Muhammad Ali Gulzar","doi":"10.56553/popets-2023-0087","DOIUrl":"https://doi.org/10.56553/popets-2023-0087","url":null,"abstract":"Modern websites heavily rely on JavaScript (JS) to implement legitimate functionality as well as privacy-invasive advertising and tracking. Browser extensions such as NoScript block any script not loaded by a trusted list of endpoints, thus hoping to block privacy-invasive scripts while avoiding breaking legitimate website functionality. In this paper, we investigate whether blocking JS on the web is feasible without breaking legitimate functionality. To this end, we conduct a large-scale measurement study of JS blocking on 100K websites. We evaluate the effectiveness of different JS blocking strategies in tracking prevention and functionality breakage. Our evaluation relies on quantitative analysis of network requests and resource loads as well as manual qualitative analysis of visual breakage. First, we show that while blocking all scripts is quite effective at reducing tracking, it significantly degrades functionality on approximately two-thirds of the tested websites. Second, we show that selective blocking of a subset of scripts based on a curated list achieves a better trade-off. However, there remain approximately 15% “mixed” scripts, which essentially merge tracking and legitimate functionality and thus cannot be blocked without causing website breakage. Finally, we show that fine-grained blocking of a subset of JS methods, instead of scripts, reduces major breakage by 3.8× while providing the same level of tracking prevention. Our work highlights the promise and open challenges in fine-grained JS blocking for tracking prevention without breaking the web.","PeriodicalId":74556,"journal":{"name":"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135111118","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

Robust Fingerprint of Location Trajectories Under Differential Privacy. 差异隐私下的位置轨迹鲁棒指纹。

Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium Pub Date : 2023-07-01 DOI: 10.56553/popets-2023-0095

Yuzhou Jiang, Emre Yilmaz, Erman Ayday

{"title":"Robust Fingerprint of Location Trajectories Under Differential Privacy.","authors":"Yuzhou Jiang, Emre Yilmaz, Erman Ayday","doi":"10.56553/popets-2023-0095","DOIUrl":"10.56553/popets-2023-0095","url":null,"abstract":"<p><p>Location-based services have brought significant convenience to people in their daily lives, and the collected location data are also in high demand. However, directly releasing those data raises privacy and liability (e.g., due to unauthorized distribution of such datasets) concerns since location data contain users' sensitive information, e.g., regular moving patterns and favorite spots. To address this, we propose a novel fingerprinting scheme that simultaneously identifies unauthorized redistribution of location datasets and provides differential privacy guarantees for the shared data. Observing data utility degradation due to differentially-private mechanisms, we introduce a utility-focused post-processing scheme to regain spatiotemporal correlations between points in a location trajectory. We further integrate this post-processing scheme into our fingerprinting scheme as a sampling method. The proposed fingerprinting scheme alleviates the degradation in the utility of the shared dataset due to the noise introduced by differentially-private mechanisms (i.e., adds the fingerprint by preserving the publicly known statistics of the data). Meanwhile, it does not violate differential privacy throughout the entire process due to immunity to post-processing, a fundamental property of differential privacy. Our proposed fingerprinting scheme is robust against known and well-studied attacks against a fingerprinting scheme including random flipping attacks, correlation-based flipping attacks, and collusions among multiple parties, which makes it hard for the attackers to infer the fingerprint codes and avoid accusation. Via experiments on two real-life location datasets and two synthetic ones, we show that our scheme achieves high fingerprinting robustness and outperforms existing approaches. Besides, the proposed fingerprinting scheme increases data utility for differentially-private datasets, which is beneficial for data analyzers.</p>","PeriodicalId":74556,"journal":{"name":"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10449389/pdf/nihms-1902824.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10477543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0