Aimilia Tasidou

Review: Mobile guides: Taxonomy of architectures, context awareness, technologies and applications

Portable devices are increasingly employed in a wide range of mobile guidance applications. Typical examples are guides in urban areas, museum guides, and exhibition space aids. The demand is for the delivery of context-specific services, wherein the context is typically identified by a combination of data related to location, time, user profile, device profile, network conditions and usage scenario. A context-aware mobile guide is intended to provide guidance services adjusted to the context of the received request. The adjustment may refer to tailoring the user interface to the perceived context, as well as delivering the right type of information to the right person at the right time and the right location. It may also refer to intermediary adaptation, as in the case of mobile multimedia transmission. This paper offers a taxonomy of mobile guides considering multiple criteria. The taxonomy considers several aspects of the mobile applications space, including context awareness, client architectures, mobile user interfaces, as well as offered functionalities, highlighting functional, architectural, technological, and implementation issues. Existing implementations are classified accordingly and a discussion of research issues and emerging trends is offered.

Towards privacy in personal data management

We present a personal data management framework called Polis, which abides by the following principle: Every individual has absolute control over her personal data, which reside only at her own side. Preliminary results indicate that beyond the apparent advantages of such an environment for userspsila privacy, everyday transactions remain both feasible and straightforward.

myVisitPlanner GR : Personalized Itinerary Planning System for Tourism.

This application paper presents myVisitPlanner GR, an intelligent web-based system aiming at making recommendations that help visitors and residents of the region of Northern Greece to plan their leisure, cultural and other activities during their stay in this area. The system encompasses a rich ontology of activities, categorized across dimensions such as activity type, historical era, user profile and age group. Each activity is characterized by attributes describing its location, cost, availability and duration range. The system makes activity recommendations based on user-selected criteria, such as visit duration and timing, geographical areas of interest and visit profiling. The user edits the proposed list and the system creates a plan, taking into account temporal and geographical constraints imposed by the selected activities, as well as by other events in the user’s calendar. The user may edit the proposed plan or request alternative plans. A recommendation engine employs non-intrusive machine learning techniques to dynamically infer and update the user’s profile, concerning his preferences for both activities and resulting plans, while taking privacy concerns into account. The system is coupled with a module to semi-automatically feed its database with new activities in the area.

Towards Privacy in Personal Data Management

We present a personal data management framework called Polis, which abides by the following principle: Every individual has absolute control over her personal data, which reside only at her own side. Preliminary results indicate that beyond the apparent advantages of such an environment for userspsila privacy, everyday transactions remain both feasible and straightforward.

Privacy-Preserving Television Audience Measurement Using Smart TVs

Internet-enabled television systems, often referred to as Smart TVs, are a new development in television and home entertainment technologies. In this work, we propose a new, privacy-preserving, approach for Television Audience Measurement (TAM), utilizing the capabilities of the Smart TV technologies. We propose a novel application to calculate aggregate audience measurements using Smart TV computation capabilities and permanent Internet access. Cryptographic techniques, including homomorphic encryption and zero-knowledge proofs, are used to ensure both that the privacy of the participating individuals is preserved and that the computed results are valid. Additionally, participants can be compensated for sharing their information. Preliminary experimental results on an Android-based Smart TV platform show the viability of the approach.

Privacy-preserving, user-centric VoIP CAPTCHA challenges: An integrated solution in the SIP environment

– This work aims to argue that it is possible to address discrimination issues that naturally arise in contemporary audio CAPTCHA challenges and potentially enhance the effectiveness of audio CAPTCHA systems by adapting the challenges to the user characteristics. , – A prototype has been designed, called PrivCAPTCHA, to offer privacy-preserving, user-centric CAPTCHA challenges. Anonymous credential proofs are integrated into the Session Initiation Protocol (SIP) protocol and the approach is evaluated in a real-world Voice over Internet Protocol (VoIP) environment. , – The results of this work indicate that it is possible to create VoIP CAPTCHA services offering privacy-preserving, user-centric challenges while maintaining sufficient efficiency. , – The proposed approach was evaluated through an experimental implementation to demonstrate its feasibility. Additional features, such as appropriate user interfaces and efficiency optimisations, would be useful for a commercial product. Security measures to protect the system from attacks against the SIP protocol would be useful to counteract the effects of the introduced overhead. Future research could investigate the use of this approach on non-audio CAPTCHA services. , – PrivCAPTCHA is expected to achieve fairer, non-discriminating CAPTCHA services while protecting the user’s privacy. Adoption success relies upon the general need for employment of privacy-preserving practices in electronic interactions. , – This approach is expected to enhance the quality of life of users, who will now receive CAPTCHA challenges closer to their characteristics. This applies especially to users with disabilities. Additionally, as a privacy-preserving service, this approach is expected to increase trust during the use of services that use it. , – To the best of authors’ knowledge, this is the first comprehensive proposal for privacy-preserving CAPTCHA challenge adaptation. The proposed system aims at providing an improved CAPTCHA service that is more appropriate for and trusted by human users.

Privacy-Enhanced Television Audience Measurements

Internet-enabled television systems (SmartTVs) are a development that introduces these devices into the interconnected environment of the Internet of Things. We propose a privacy-preserving application for computing Television Audience Measurement (TAM) ratings. SmartTVs communicate over the Internet to calculate aggregate measurements. Contemporary cryptographic building blocks are utilized to ensure the privacy of the participating individuals and the validity of the computed TAM ratings. Additionally, user compensation capabilities are introduced to bring some of the company profits back to the data owners. A prototype implementation is developed on an Android-based SmartTV platform and experimental results illustrate the feasibility of the approach.