Privacy-Preserving History Mining for Web Browsers
نویسندگان
چکیده
We introduce a new technique that permits servers to harvest selected Internet browsing history from visiting clients. Privacy-Preserving History Mining (PPHM) requires no installation of special-purpose client-side executables. Paradoxically, it exploits a feature in most browsers (IE, Firefox and Safari) regarded for years as a privacy vulnerability. PPHM enables privacy-preserving data-mining through the addition of a client-side filter that supports OR and AND queries over the URLs cached in a client. We describe a lightweight prototype PPHM system designed for targeted advertising. We also discuss audit and policy enhancements that help our PPHM system comply with regulatory guidelines like the OECD Fair Information Practice Principles.
منابع مشابه
Privacy Preserving Internet Browsers: Forensic Analysis of Browzar
With the advance of technology, Criminal Justice agencies are being confronted with an increased need to investigate crimes perpetuated partially or entirely over the Internet. These types of crime are known as cybercrimes. In order to conceal illegal online activity, criminals often use private browsing features or browsers designed to provide total browsing privacy. The use of private browsin...
متن کاملA Privacy Preserving Data Mining Scheme Based on Network User’s Behavior
The privacy preserving data mining has become a research hot issue in the data mining field. The server log of the Web site has preserved the page information visited by users. If the page information is not protected, the user’s privacy data would be leaked. Aiming at the problem, it discusses the privacy preserving problem based on the user’s behavior in the Web data mining, and then introduc...
متن کاملMulti-objective optimization based privacy preserving distributed data mining in Peer-to-Peer networks
This paper proposes a scalable, local privacy-preserving algorithm for distributed peer-to-peer (P2P) data aggregation useful for many advanced data mining/analysis tasks such as average/sum computation, decision tree induction, feature selection, and more. Unlike most multi-party privacy-preserving data mining algorithms, this approach works in an asynchronous manner through local interactions...
متن کاملSafelog: Supporting Web Search and Mining by Differentially-Private Query Logs
Query logs can be very useful for advancing web search and web mining research. Since these web query logs contain private, possibly sensitive data, they need to be effectively anonymized before they can be released for research use. Anonymization of query logs differs from that of structured data since they are generated based on natural language and the vocabulary (domain) is infinite. This u...
متن کاملForensics Evaluation of Privacy of Portable Web Browsers
Browsers claim private mode browsing saves no data on the host machine. Most popular web browsers also offer portable versions of their browsers which can be launched from a removable device. When the removable device is removed, it is claimed that traces of browsing activities will be deleted and consequently private portable browsers offer better privacy. This makes the task of computer foren...
متن کامل