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Generating User-Understandable Privacy Preferences

Jan Kolter, Günther Pernul
2009 2009 International Conference on Availability, Reliability and Security  
This paper introduces a novel, user-friendly privacy preference generator that allows the definition of privacy preferences for twelve different Internet service types, allowing for more precise and practical  ...  Accordingly, the creation of these disclosure rules requires tools that accurately record individual privacy preferences in an understandable way.  ...  Addressing these usability deficiencies we propose a new user-understandable privacy preference generator in the following sections. III.  ... 
doi:10.1109/ares.2009.89 dblp:conf/IEEEares/KolterP09 fatcat:m5ezjz6f7fa2xlykwgu642sfy4

Learning Privacy Preferences

Inger Anne Tondel, Åsmund Ahlmann Nyre, Karin Bernsmed
2011 2011 Sixth International Conference on Availability, Reliability and Security  
This paper suggests a machine learning approach to preference generation in the context of privacy agents.  ...  Instead, historical privacy decisions are used as a basis for providing privacy recommendations to users in new situations.  ...  Compared to the existing approaches to preference specification (outlined in the Introduction), the machine learning approach reduces the need for users to understand the preferences as these are generated  ... 
doi:10.1109/ares.2011.96 dblp:conf/IEEEares/TondelNB11 fatcat:l5oefxetmbc67jvrcklah5vogu

Collaborative Privacy – A Community-Based Privacy Infrastructure [chapter]

Jan Kolter, Thomas Kernchen, Günther Pernul
2009 IFIP Advances in Information and Communication Technology  
Service providers collecting more and more of these personal user data pose a growing privacy threat for users. Addressing user concerns privacy-enhancing technologies emerged.  ...  We lay out the privacy community's functions and potentials within a user-centric, provider-independent privacy architecture that will help foster the usage and acceptance of privacy-enhancing technologies  ...  Even though the Privacy Preference Generator component should alleviate this challenge by offering a usable and understandable user interface, building accurate privacy preferences is a critical task.  ... 
doi:10.1007/978-3-642-01244-0_20 fatcat:j4qri7wev5grhamvrax3newctu

Towards a Model of User-centered Privacy Preservation

Paul Grace, Mike Surridge
2017 Proceedings of the 12th International Conference on Availability, Reliability and Security - ARES '17  
In this paper, we present a model of user-centered privacy that can be used to analyse a service's behaviour against user preferences, such that a user can be informed of the privacy implications of that  ...  We show through a case-study that the user-based privacy model can: i) provide customizable privacy aligned with user needs; and ii) identify potential privacy breaches.  ...  We also acknowledge the work of Robbie Anderson in developing an early implementation of the privacy questionnaire.  ... 
doi:10.1145/3098954.3104054 dblp:conf/IEEEares/GraceS17 fatcat:rkwtdjje4jhfjcewv7modmmgnu

Multi-View Permission Risk Notification for Smartphone System

Carol J. Fung, Bahman Rashidi, Vivian Genaro Motti
2019 Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications  
The implementation of our model includes a new design of User Interface (UI), interpreting apps' activities risks, and users' preferences adaption.  ...  The current permission requests interface provides little information to help users understand the risk of granting those requests.  ...  Some other views may target inexperienced users with little understanding about IT (users who are not familiar with privacy risks and technical terms).  ... 
doi:10.22667/jowua.2019.03.31.042 dblp:journals/jowua/FungRM19 fatcat:wddduhihkbc2jgrnfq5avrlywu

Privacy Knowledge Modelling for Internet of Things: A Look Back [article]

Charith Perera, Chang Liu, Rajiv Ranjan, Lizhe Wang, Albert Y. Zomaya
2016 arXiv   pre-print
Therefore, understanding the privacy expectations and preferences of stakeholders is an important task in the IoT domain.  ...  of users and lead them to consume resources more efficiently.  ...  Further, it is important to understand what P3P is, how it has been designed to work, and why P3P failed in order to propose the next generation privacy preferences modelling approaches, especially for  ... 
arXiv:1606.08480v1 fatcat:wj4zj2fx3vevvlzyvczogedbje

User Agents for Matching Privacy Policies with User Preferences

Karin Bernsmed, Åsmund Ahlmann Nyre, Martin Gilje Jaatun
2012 Journal of clean energy technologies  
This paper surveys user agents that automatically fetch and compare privacy policies with privacy preferences, in order to help the end-user understand the implications of personal data disclosure.  ...  Privacy policies are commonly used by service providers to state how personal data obtained from users will be handled.  ...  Its appearance is very similar to the general model presented in Figure 1 ; it consists of a privacy preference generator and a privacy agent.  ... 
doi:10.7763/ijcte.2012.v4.506 fatcat:g4qf5qn53zghnke2dkaee23vba

A User Study to Evaluate a Web-based Prototype for Smart Home Internet of Things Device Management [article]

Leena Alghamdi, Ashwaq Alsoubai, Mamtaj Akter, Faisal Alghamdi, Pamela Wisniewski
2022 arXiv   pre-print
This paper provides an empirical examination of the privacy versus convenience trade-offs smart home users make when managing their IoT devices.  ...  Based on their average scores of privacy vs. convenience importance, participants with low privacy and low convenience significantly reported less privacy control and convenience preferences than participants  ...  Therefore, we urge future research to leverage both users' privacy and convenience in order to understand the perceptions of smart IoT devices users toward their privacy concerns and convenience preferences  ... 
arXiv:2204.07751v1 fatcat:t6qpcbpuzzaw5cdfwogwkmpytm

ConTra Preference Language: Privacy Preference Unification via Privacy Interfaces

Stefan Becher, Armin Gerl
2022 Sensors  
These changes mostly affect the Controller to achieve GDPR-compliant privacy policies and management.However, measures to give users a better understanding of privacy, which is essential to generate legitimate  ...  We recommend addressing this issue by the usage of privacy preference languages, whereas users define rules regarding their preferences for privacy handling.  ...  Therefore, very general rules, which are easy to understand by the user, can be defined, e.g., one that only excludes the usage of location data.  ... 
doi:10.3390/s22145428 pmid:35891105 pmcid:PMC9316104 fatcat:wv2g6hfl7vfwrcglzd7p3egqia

Personal privacy through understanding and action: five pitfalls for designers

Scott Lederer, Jason I. Hong, Anind K. Dey, James A. Landay
2004 Personal and Ubiquitous Computing  
These pitfalls are based on the literature, on analyses of existing privacy-affecting systems, and on our own experiences designing a user interface for managing privacy in ubiquitous computing.  ...  People create and maintain personal privacy by understanding the privacy implications relevant to a situation and influencing them through intuitive social action.  ...  Making the scope of a system's privacy implications clear will help users understand its capabilities and limits.  ... 
doi:10.1007/s00779-004-0304-9 fatcat:o3iyjylpvffabgtx7urdsp2vpa

A Server-side Approach to Privacy Policy Matching

Åsmund Ahlmann Nyre, Karin Bernsmed, Solvar Bo, Stian Pedersen
2011 2011 Sixth International Conference on Availability, Reliability and Security  
Commonly, web privacy is handled through matching of privacy policies and user preferences using software agents on the client side.  ...  ' privacy preferences.  ...  To protect their privacy it is of major importance that the users understand the implications of data sharing.  ... 
doi:10.1109/ares.2011.95 dblp:conf/IEEEares/NyreBBP11 fatcat:k64jz76455c7hghdyulqheo5dy

User preferences for privacy features in digital assistants

Frank Ebbers, Jan Zibuschka, Christian Zimmermann, Oliver Hinz
2020 Electronic Markets  
In general, a playful design of privacy features is strongly preferred, as users are willing to pay 23.8% more compared to an option without any gamified elements.  ...  In addition, it estimates users' willingness to pay (WTP) for different versions of privacy features.The results for the full sample show that users prefer to understand the rationale behind the DA's decisions  ...  Users' privacy preferences and their economic value Understanding privacy preferences is important for business (as it can be a competitive advantage), for legal scholars (as privacy is becoming increasingly  ... 
doi:10.1007/s12525-020-00447-y fatcat:bdqpqb4hlffhjcwt6di7oufeuy

Collaborative privacy management

Jan Kolter, Thomas Kernchen, Günther Pernul
2010 Computers & security  
Targeting growing privacy concerns of users, privacy-enhancing technologies emerged.  ...  Unfortunately, the growing amount of personal data collected by service providers poses a significant privacy threat for Internet users.  ...  Even though the Privacy Preference Generator component should alleviate this challenge by offering a usable and understandable user interface, building accurate privacy preferences is a critical task.  ... 
doi:10.1016/j.cose.2009.12.007 fatcat:6o3gnb5ojngcjnbo4s4jitvmze

Privacy policies for shared content in social network sites

Anna C. Squicciarini, Mohamed Shehab, Joshua Wede
2010 The VLDB journal  
We integrate our design with inference techniques that free the users from the burden of manually selecting privacy preferences for each picture.  ...  Users responded favorably to the approach, indicating a general understanding of co-ownership and the auction, and found the approach to be both useful and fair.  ...  The user sets his/her privacy policy according to his/her privacy preference.  ... 
doi:10.1007/s00778-010-0193-7 fatcat:aaaskp6bb5dg5acg7ajtbop76q

Privacy in pervasive environments: next generation labeling protocols

Mark S. Ackerman
2004 Personal and Ubiquitous Computing  
Recent experiences with the Platform for Privacy Preferences Project (P3P), an attempt to provide privacy mechanisms for the Web, suggest important lessons for the design of a next generation labeling  ...  In pervasive environments, privacy is likely to be a major issue for users, and users will want to be notified of potential data capture.  ...  Acknowledgements Many people have helped in my understanding both of privacy and pervasive environments.  ... 
doi:10.1007/s00779-004-0305-8 fatcat:ikrwrofntnahvgjee55ml5pbla
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