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Measuring Privacy Risk in Online Social Networks
"... Measuring privacy risk in online social networks is a challenging task. One of the fundamental difficulties is quantifying the amount of information revealed unintentionally. We present PrivAware, a tool to detect and report unintended information loss in online social networks. Our goal is to provi ..."
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Measuring privacy risk in online social networks is a challenging task. One of the fundamental difficulties is quantifying the amount of information revealed unintentionally. We present PrivAware, a tool to detect and report unintended information loss in online social networks. Our goal is to provide a rudimentary framework to identify privacy risk and provide solutions to reduce information loss. The first instance of the software is focused on information loss attributed to social circles. In subsequent releases we intend to incorporate additional capabilities to capture ancillary threat models. From our initial results, we quantify the privacy risk attributed to friend relationships in Facebook. We show that for each user in our study a majority of their personal attributes can be derived from social contacts. Moreover, we present results denoting the number of friends contributing to a correctly inferred attribute. We also provide similar results for different demographics of users. The intent of PrivAware is to not only report information loss but to recommend user actions to mitigate privacy risk. The actions provide users with the steps necessary to improve their overall privacy measurement. One obvious, but not ideal, solution is to remove risky friends. Another approach is to group risky friends and apply access controls to the group to limit visibility. In summary, our goal is to provide a unique tool to quantify information loss and provide features to reduce privacy risk. 1.
Love and Authentication
- In CHI ’08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems
, 2008
"... Passwords are ubiquitous, and users and service providers alike rely on them for their security. However, good passwords may sometimes be hard to remember. For years, security practitioners have battled with the dilemma of how to authenticate people who have forgotten their passwords. Existing appro ..."
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Passwords are ubiquitous, and users and service providers alike rely on them for their security. However, good passwords may sometimes be hard to remember. For years, security practitioners have battled with the dilemma of how to authenticate people who have forgotten their passwords. Existing approaches suffer from high false positive and false negative rates, where the former is often due to low entropy or public availability of information, whereas the latter often is due to unclear or changing answers, or ambiguous or fault prone entry of the same. Good security questions should be based on long-lived personal preferences and knowledge, and avoid publicly available information. We show that many of the questions used by online matchmaking services are suitable as security questions. We first describe a new user interface approach suitable to such security questions that is offering a reduced risks of incorrect entry. We then detail the findings of experiments aimed at quantifying the security of our proposed method.
(Under)mining Privacy in Social Networks
"... Social networking sites like Facebook or MySpace allow users to keep in touch with their friends, communicate and share content with them, as well as engage in other multiuser applications. What distinguishes such sites from ..."
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Cited by 14 (1 self)
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Social networking sites like Facebook or MySpace allow users to keep in touch with their friends, communicate and share content with them, as well as engage in other multiuser applications. What distinguishes such sites from
ABSTRACT Detecting Privacy Leaks Using Corpus-based Association Rules
"... Detecting inferences in documents is critical for ensuring privacy when sharing information. In this paper, we propose a refined and practical model of inference detection using a reference corpus. Our model is inspired by association rule mining: inferences are based on word co-occurrences. Using t ..."
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Detecting inferences in documents is critical for ensuring privacy when sharing information. In this paper, we propose a refined and practical model of inference detection using a reference corpus. Our model is inspired by association rule mining: inferences are based on word co-occurrences. Using the model and taking the Web as the reference corpus, we can find inferences and measure their strength through web-mining algorithms that leverage search engines such as Google or Yahoo!. Our model also includes the important case of private corpora, to model inference detection in enterprise settings in which there is a large private document repository. We find inferences in private corpora by using analogues of our Web-mining algorithms, relying on an index for the corpus rather than a Web search engine. We present results from two experiments. The first experiment demonstrates the performance of our techniques in identifying all the keywords that allow for inference of a particular topic (e.g. “HIV") with confidence above a certain threshold. The second experiment uses the public Enron e-mail dataset. We postulate a sensitive topic and use the Enron corpus and the Web together to find inferences for the topic. These experiments demonstrate that our techniques are practical, and that our model of inference based on word co-occurrence is well-suited to efficient inference detection.
IRILD: an Information Retrieval based method for Information Leak Detection
"... Abstract—The traditional approach for detecting information leaks is to generate fingerprints of sensitive data, by partitioning and hashing it, and then comparing these fingerprints against outgoing documents. Unfortunately, this approach incurs a high computation cost as every part of document nee ..."
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Abstract—The traditional approach for detecting information leaks is to generate fingerprints of sensitive data, by partitioning and hashing it, and then comparing these fingerprints against outgoing documents. Unfortunately, this approach incurs a high computation cost as every part of document needs to be checked. As a result, it is not applicable to systems with a large number of documents that need to be protected. Additionally, the approach is prone to false positives if the fingerprints are common phrases. In this paper, we propose an improvement for this approach to offer a much faster processing time with less false positives. The core idea of our solution is to eliminate common phrases and non-sensitive phrases from the fingerprinting process. Non-sensitive phrases are identified by looking at available public documents of the organization that we want to protect from information leaks and common phrases are identified with the help of a search engine. In this way, our solution both accelerates leak detection and increases the accuracy of the result. Experiments were conducted on real-world data to prove the efficiency and effectiveness of the proposed solution. Keywords-privacy, information leaks, fingerprinting I.
Abstract Lightweight, Content-based Taint Propagation for Tracking Sensitive Information
"... A user’s workstation eventually accumulates a great deal of personally identifiable or otherwise sensitive information. While the location of some of this information will be obvious (e.g., explicitly saved documents), much will also propagate throughout the system to any number of unknown locations ..."
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A user’s workstation eventually accumulates a great deal of personally identifiable or otherwise sensitive information. While the location of some of this information will be obvious (e.g., explicitly saved documents), much will also propagate throughout the system to any number of unknown locations. Without knowing the location of sensitive data within a system, it can be difficult to set permissions for access control for other users or untrusted code. In this paper, we suggest an architecture for tracking the sensitive information stored within the persistent state of a user’s workstation. In order to achieve minimal computational overhead, we base our proposal on a lightweight, content-based technique for taint propagation. Through a prototype implementation, we demonstrate that this approach incurs very minimal overhead and will not likely cause any user perceptible delays. Furthermore, our architecture is minimally invasive and can implemented completely in userspace, easing system integration. While the content-based technique cannot track sensitive information through arbitrary programs, we show in an initial evaluation using our prototype that common programs can be handled correctly. 1
Security
"... Protecting identity in the Internet age requires the ability to go beyond the identification of explicitly identifying information like social security numbers, to also find the broadlyheld attributes that, when taken together, are identifying. We present a system that can work in conjunction with n ..."
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Protecting identity in the Internet age requires the ability to go beyond the identification of explicitly identifying information like social security numbers, to also find the broadlyheld attributes that, when taken together, are identifying. We present a system that can work in conjunction with natural language processing algorithms or user-generated tags, to protect identifying attributes in text. The system uses a new attribute-based encryption protocol to control access to such identifying attributes and thus protects identity. The system supports the definition of user access rights based on role or identity. We extend the existing model of attributebased encryption to support threshold access rights and provide a heuristic instantiation of revocation.
Decentralized
"... Abstract—Many access control systems, particularly those utilized in hospital environments, exercise optimistic security, because preventing access to information may have undesirable consequences. However, in the wrong hands, these over-broad permissions may result in privacy violations. To circumv ..."
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Abstract—Many access control systems, particularly those utilized in hospital environments, exercise optimistic security, because preventing access to information may have undesirable consequences. However, in the wrong hands, these over-broad permissions may result in privacy violations. To circumvent this issue, we have developed Privacy Enabling Transparent Systems (PETS) that makes transparency a key component in systems architectures. PETS is built on open web standards and introduces the Provenance Tracking Network (PTN), an open global trusted network of peer servers, to the traditional web stack. Websites that conform to the architecture communicate information about transactions for any sensitive data items with the PTN. These usage logs are stored in a decentralized manner and can later be queried to check compliance with individual usage restrictions that assert no unauthorized data transfer or usage has taken place. PETS enables data consumers to be transparent with regard to data usages and determine if there has been privacy violations after the fact. We conducted a user study on a healthcare information application built using PETS to see if transparency on access and usage data satisfies expectations of user privacy. Keywords—Privacy, Transparency, User Choice. I.
Constraint for Safely Outsourcing Multimedia Documents
, 2014
"... HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. de-Linkability: a Privacy-Preserving
Sherlock Holmes’s Evil Twin: On The Impact of Global Inference for Online Privacy
"... User-supplied content—in the form of photos, videos, and text—is a crucial ingredient to many web sites and services today. However, many users who provide content do not realize that their uploads may be leaking personal information in forms hard to intuitively grasp. Correlation of seemingly innoc ..."
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User-supplied content—in the form of photos, videos, and text—is a crucial ingredient to many web sites and services today. However, many users who provide content do not realize that their uploads may be leaking personal information in forms hard to intuitively grasp. Correlation of seemingly innocuous information can create inference chains that tell much more about individuals than they are aware of revealing. We contend that adversaries can system-atically exploit such relationships by correlating information from different sources in what we term global inference attacks: assem-bling a comprehensive understanding from individual pieces found at a variety of locations, Sherlock-style. Not only are such attacks already technically viable given the capabilities that today’s mul-timedia content analysis and correlation technologies readily pro-vide, but we also find business models that provide adversaries with powerful incentives for pursuing them. 1.
