Client-side multi-agent system for contextual private data management for e-commerce and m-commerce on the semantic web

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Existing private data management and related privacy enhancing tools (PETs), aimed at increasing the users' control over their private information, are fragmented, limited in capability and usability, and thus are far from suitable for wide scale user adoption. There is also an urgent need for client-side technologies to complement, and thus strengthen the goals, of the enterprise technologies that organizations' employees use to protect and manage customers' private data, in accordance to recent legal guidelines in many countries. Currently, technology-based privacy solutions take a one-size-fits-all approach. This research's goals are to provide a high-level of customization around user decision-making depending on the contexts in which the user is being asked to release private information. Contexts and customization are important and useful mechanisms, as privacy, ethical, social, and economic concerns regarding data handling differ according to user profiles, customer, and other stakeholder groups. Such concerns differ too according to physical (spatial and temporal) situation and types of data. This research proposes a client-side private data management system to support users' contextual and privacy-aware data release to organizations when conducting commerce over the Internet and mobile networks.  Scientific problems that will be investigated include suitable socio-technical privacy architecture, knowledge representations to support privacy-aware user contexts in e-commerce and m-commerce, intelligence-based algorithms and agents for supporting these contexts, intelligent algorithms and personal agents for increasing privacy software usability, and novel agent-based privacy Web services and infrastructure. While the objectives of this research address scientific problems, the user-visible outcomes are technologies that enable users to make informed and highly-nuanced contextual decisions around releasing private data to organizations. The technologies will also alert users as to potential privacy problems, remind them of socio-economic contexts when conducting e- or m-commerce transactions, and allow users to organize and view reports on the private data they have given to organizations under particular circumstances.