Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> Privacy Challenges <s> hat the individual shall have full protection in person and in property is a principle as old as the common law; but it has been found necessary from time to time to define anew the exact nature and extent of such protection. Political, social, and economic changes entail the recognition of new rights, and the common law, in its eternal youth, grows to meet the new demands of society. Thus, in very early times, the law gave a remedy only for physical interference with life and property, for trespasses vi et armis. Then the "right to life" served only to protect the subject from battery in its various forms; liberty meant freedom from actual restraint; and the right to property secured to the individual his lands and his cattle. Later, there came a recognition of man's spiritual nature, of his feelings and his intellect. Gradually the scope of these legal rights broadened; and now the right to life has come to mean the right to enjoy life, -the right to be let alone; the right to liberty secures the exercise of extensive civil privileges; and the term "property" has grown to comprise every form of possession -intangible, as well as tangible. <s> BIB001 </s> Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> Privacy Challenges <s> The MOBIlearn project (EU IST-2001-37187) aims to support a wide range of services and applications for learners using mobile computing devices such as phones, PDAs, and laptops. The display limitations of these devices mean that it is crucial to deliver the right content at the right time. One way of doing this is to use contextual information to derive content that is relevant to what the user is doing, as well as where and how they are doing it. We present an object-oriented, feature-based architecture for a context awareness subsystem to be implemented within the MOBIlearn project, and consider the implications involved in the use of such a system for mobile learning. <s> BIB002 </s> Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> Privacy Challenges <s> Abstract Privacy-Enhancing Technologies (PET) are the technical answer to social and legal privacy requirements. PET become constituents for tools to manage users' personal data. Users can thereby control their individual digital identity, i.e. their individual partial identities in an online world. Existing commercially available identity management systems (IMS) do not yet provide privacy-enhancing functionality. We discuss general concepts and mechanisms for privacy-enhancing IMS (PE-IMS) in detail and highlight where existing IMS need to be improved in order to deliver them. Derived from general concepts and incorporating existing mechanisms, we define a component-based architecture for PE-IMS. This architecture describes the basic building blocks a PE-IMS must include, and so it is meant to be used as a fundamental concept for PE-IMS in practice. Finally, we give an outlook on the future development concerning IMS. Identity, Privacy, Identity Management System, Privacy-Enhancing Technologies, PET, Privacy-Enhancing Identity Management System, Multilateral Security <s> BIB003 </s> Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> Privacy Challenges <s> OBJECTIVE ::: We present an integrated set of technologies, known as the Hippocratic Database, that enable healthcare enterprises to comply with privacy and security laws without impeding the legitimate management, sharing, and analysis of personal health information. ::: ::: ::: APPROACH ::: The Hippocratic Database approach to securing electronic health records involves (1) active enforcement of fine-grained data disclosure policies using query modification techniques, (2) efficient auditing of past database access to verify compliance with policies and track security breaches, (3) data mining algorithms that preserve privacy by randomizing information at the individual level, (4) de-identification of personal health data using an optimal method of k-anonymization, and (5) information sharing across autonomous data sources using cryptographic protocols. ::: ::: ::: CONCLUSIONS ::: Our research confirms that policies concerning the disclosure of electronic health records can be reliably and efficiently enforced and audited at the database level. We further demonstrate that advanced data mining and anonymization techniques can be employed to analyze aggregate health records without revealing individual patient identities. Finally, we show that web services and commutative encryption can be used to share sensitive information selectively among autonomous entities without compromising security or privacy. <s> BIB004
Privacy and legal protection rights are a major challenge that needs to be tackled when capturing and using contextual data for recommendation. So far, researchers have often ignored privacy issues. However, if contextaware recommender technologies want to move beyond the current prototype phase, practical solutions regarding legal and privacy issues are needed. The challenge needs to be tackled from two perspectives: 1) the privacy of the target users needs to be preserved in order to deploy current prototypes in real-life settings and 2) the sharing and exchange of data is a key requirement to enable comparative evaluation studies-as discussed in the previous section. In principle, researchers do not want to harm the privacy rights of the target users and are willing to make scientific data available. However, they are inexperienced how to address both issues in a proper way. They are missing a condensed overview of the legal situation and practical solutions regarding data set sharing. In order to overcome these challenges, guidelines need to be developed that document data protection laws like the European Directive on data protection 95/46/EC  . The main principles of this directive have been discussed in BIB002 and include 1) informed consent: users must be made aware of what data is being gathered and what it is being used for, 2) control: where consent has been given for the gathering and use of contextual data, users should be given information, access, and control over data, and 3) security: data has to be stored securely. Several frameworks to address these requirements are discussed in the literature BIB004 ,  ; . In a privacy as confidentiality paradigm, privacy has been defined as "the right to be let alone" BIB001 . One way of achieving data confidentiality is to enable the use of information-based services, while either minimizing the collection of information, or securing the collected information from unauthorized access. Another way is to guarantee anonymity, e.g., by anonymizing the collected data. . In a privacy as control paradigm, privacy is defined as the ability to control what happens with information. A reason for this notion is that revelation of data is necessary and beneficial under many circumstances and that control may help to prevent abuses of data. Identity Management Systems (IDMSs) BIB003 are an important class of tools that provide the ability to control information that is revealed. . In a privacy as practice paradigm, the objectives are to make it possible to intervene in the flows of existing data by making transparent the way in which information is collected and used for decision making. We discuss in the next section how such an approach can be supported from a user interface point of view. The documentation of these frameworks as well as research on the use of these frameworks in TEL settings is an interesting further line of research. Initial work in this area has been presented by Gü rses and Vuorikari  .