Towards Privacy-Preserving Web Metering via User-Centric Hardware

2015 ◽  
pp. 329-340
Author(s):  
Fahad Alarifi ◽  
Maribel Fernández
Keyword(s):  
Privacy Preserving ◽  
User Centric

scholarly journals User-centric privacy-preserving statistical analysis of ubiquitous health monitoring data

2014 ◽  
Vol 11 (2) ◽  
pp. 525-548 ◽  
Author(s):  
George Drosatos ◽  
Pavlos Efraimidis
Keyword(s):  
Statistical Analysis ◽  
Health Monitoring ◽  
Wearable Sensors ◽  
Privacy Preserving ◽  
Monitoring Data ◽  
Biomedical Data ◽  
Enormous Amount ◽  
User Centric ◽  
Personal Agents ◽  
To Receive

In this paper, we propose a user-centric software architecture for managing Ubiquitous Health Monitoring Data (UHMD) generated from wearable sensors in a Ubiquitous Health Monitoring System (UHMS), and examine how these data can be used within privacy-preserving distributed statistical analysis. Two are the main goals of our approach. First, to enhance the privacy of patients. Second, to decongest the Health Monitoring Center (HMC) from the enormous amount of biomedical data generated by the users? wearable sensors. In our solution personal software agents are used to receive and manage the personal medical data of their owners. Moreover, the personal agents can support privacy-preserving distributed statistical analysis of the health data. To this end, we present a cryptographic protocol based on secure multi-party computations that accept as input current or archived values of users? wearable sensors. We describe a prototype implementation that performs a statistical analysis on a community of independent personal agents. Finally, experiments with up to several hundred agents confirm the viability and the effectiveness of our approach.

scholarly journals Towards Privacy-Preserving Web Metering Via User-Centric Hardware

2015 ◽  
Vol 2 (4) ◽  
pp. 150478
Author(s):  
Fahad Alarfi ◽  
Maribel Fernández
Keyword(s):  
Privacy Preserving ◽  
User Centric

scholarly journals A Privacy-Preserving Platform for User-Centric Quantitative Benchmarking

2009 ◽  
pp. 32-41 ◽  
Author(s):  
Dominik Herrmann ◽  
Florian Scheuer ◽  
Philipp Feustel ◽  
Thomas Nowey ◽  
Hannes Federrath
Keyword(s):  
Privacy Preserving ◽  
User Centric

User-centric distributed solutions for privacy-preserving analytics

2017 ◽  
Vol 60 (2) ◽  
pp. 37-39 ◽  
Author(s):  
Azer Bestavros ◽  
Andrei Lapets ◽  
Mayank Varia
Keyword(s):  
Privacy Preserving ◽  
Distributed Solutions ◽  
User Centric

Privacy-preserving, user-centric VoIP CAPTCHA challenges

2016 ◽  
Vol 24 (1) ◽  
pp. 2-19 ◽  
Author(s):  
Aimilia Tasidou ◽  
Pavlos S. Efraimidis ◽  
Yannis Soupionis ◽  
Lilian Mitrou ◽  
Vasilios Katos
Keyword(s):  
User Interfaces ◽  
Privacy Preserving ◽  
Future Research ◽  
Security Measures ◽  
User Characteristics ◽  
Content Type ◽  
Sip Protocol ◽  
Use Of Services ◽  
User Centric ◽  
Anonymous Credential

Purpose – 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. Design/methodology/approach – 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. Findings – 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. Research limitations/implications – 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. Practical implications – 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. Social implications – 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. Originality/value – 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.

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