that our society can gain maximum benefit from this technology. In this paper, we discuss a framework of theoretical foundations, models, mechanisms and architectures that allow applications to benefit from privacy-enhanced and secure use of provenance in a modular fashion. After introducing the main

to support most TCP-based programs without modification. Tor now relies on the filtering features of privacy-enhancing application-level proxies such as Privoxy No mixing, padding, or traffic shaping (yet): Onion Routing originally called for batching and reordering cells as they arrived, assumed padding

technology. This paper focuses on a privacy issue that arises when users send security-sensitive data (e.g., the content contains trade secrets or secret formula) to remote servers for data processing. We examine this issue, explore some partial solutions and present an overview of our current work

privacy, individuals can use pseudonyms and determine the degree of linkability between different occurrences of their data. Through the secure and authenticated use of pseudonyms, accountability of an individual for his or her actions can be achieved without giving away personal data. Thus, privacy-enhancing

of privacy protection. Current EPCglobal standards for RFID also suffer from insufficient attention to this issue. In this paper, we propose a privacy controller module that enhances the Filtering and Collection (F&C) middleware of the EPCglobal network. We provide a privacy policy-driven model, using

to stand-alone machines or local networks, people's profiles are now being collected by dozens if not hundreds of personalized websites. Widely publicized security glitches and privacy breaches as well as aggressive telemarketing have led to a wide-spread (~60-80%) reluctance of Internet users

Abstract. Participatory sensing enables new paradigms and markets for information collection based on the ubiquitous availability of smartphones, but also introduces privacy challenges for participating users and their data. In this work, we review existing security models for privacy

. In this paper, we introduce PEPSI: Privacy-Enhanced Participatory Sensing Infrastructure. We explore realistic architectural assumptions and a minimal set of formal requirements aiming at protecting privacy of both data producers and consumers. We also present an instantiation that attains privacy guarantees

The perpetual debate on RFID as a risk to privacy has lead to a variety of technical proposals for securing RFID data and encompasses, apart from general IT security measures, a number of RFID-specific “Privacy-Enhancing Technologies (PETs)”. Against the background of an imminent obligation

information exchanged via Internet, while at the same time protecting their privacy. There is a scale between security and privacy that currently leans towards security; security adopts strong user authentication mechanisms in order to control access to personal data, while privacy requires loose