Participatory privacy enabling privacy in participatory sensing
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The document discusses privacy issues in participatory sensing and proposes a privacy-enhanced participatory sensing infrastructure called PEPSI. Participatory sensing allows mobile users to share sensor data, but existing systems do not provide adequate privacy protections. PEPSI uses cryptographic tools to allow query/report matching by a service provider while guaranteeing privacy for mobile nodes and query submitters. It aims to provide provable privacy by design and defines clear privacy properties.
Participatory privacy enabling privacy in participatory sensing
- 1. Participatory Privacy: Enabling Privacy in Participatory Sensing ABSTRACT: Participatory sensing is an emerging computing paradigm that enables the distributed collection of data by self-selected participants. It allows the increasing number of mobile phone users to share local knowledge acquired by their sensor- equipped devices (e.g., to monitor temperature, pollution level, or consumer pricing information). While research initiatives and prototypes proliferate, their real-world impact is often bounded to comprehensive user participation. If users have no incentive, or feel that their privacy might be endangered, it is likely that they will not participate. In this article, we focus on privacy protection in participatory sensing and introduce a suitable privacy-enhanced infrastructure. First, we provide a set of definitions of privacy requirements for both data producers (i.e., users providing sensed information) and consumers (i.e., applications accessing the data). Then we propose an efficient solution designed for mobile phone users, which incurs very low overhead. Finally, we discuss a number of open problems and possible research directions.
- 2. EXISTING SYSTEM: In the last few years, PS initiatives have multiplied, ranging from research prototypes to deployed systems. Due to space limitations we briefly review some PS application that apparently expose participant privacy (location, habits, etc.). Each of them can easily be enhanced with our privacy-protecting layer. DISADVANTAGES OF EXISTING SYSTEM: Privacy in participatory sensing relying on weak assumptions: they attempted to protect anonymity of mobile nodes through the use of Mix Networks. (A Mix Network is a statistical-based anonymizing infrastructure that provides k- anonymity; i.e., an adversary cannot tell a user from a set of k.) However, Mix Networks are unsuitable for many PS settings. They do not attain provable privacy guarantees and assume the presence of a ubiquitous WiFi infrastructure used by mobile nodes, whereas PS applications do leverage the increasing use of broadband 3G/4G connectivity. In fact, a ubiquitous presence of open WiFi networks is not realistic today or anticipated in the near future. PROPOSED SYSTEM: We now present our innovative solution for a Privacy-Enhanced Participatory Sensing Infrastructure (PEPSI). PEPSI protects privacy using efficient
- 3. cryptographic tools. Similar to other cryptographic solutions, it introduces an additional (offline) entity, the registration authority. It sets up system parameters and manages mobile nodes or queriers registration. However, the registration authority is not involved in real-time operations (e.g., query/report matching); nor is it trusted to intervene for protecting participants’ privacy. PEPSI allows the service provider to perform report/query matching while guaranteeing the privacy of both mobile nodes and queriers. It aims at providing (provable) privacy by design, and starts off with defining a clear set of privacy properties. ADVANTAGES OF PROPOSED SYSTEM: • Secure encryption of reports and queries • Efficient and oblivious matching by the service provider
- 4. ARCHITECTURE: SYSTEM CONFIGURATION:- HARDWARE CONFIGURATION:- Processor - Pentium –IV Speed - 1.1 Ghz RAM - 256 MB(min) Hard Disk - 20 GB Key Board - Standard Windows Keyboard
- 5. Mouse - Two or Three Button Mouse Monitor - SVGA SOFTWARE CONFIGURATION:- Operating System : Windows XP Programming Language : JAVA Java Version : JDK 1.6 & above. REFERENCE: Emiliano De Cristofaro, Palo Alto Research Center (PARC) Claudio Soriente, ETH Zurich, Switzerland, “Participatory Privacy: Enabling Privacy in Participatory Sensing”, IEEE Network January/February 2013.