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Reciprocities or Incentives?: Understanding Privacy Intrusion Perspectives and Sharing Behaviors
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013).ORCID-id: 0000-0002-6509-3792
Karlstads universitet, Fakulteten för humaniora och samhällsvetenskap (from 2013), Centrum för tjänsteforskning (from 2013). Karlstads universitet, Fakulteten för humaniora och samhällsvetenskap (from 2013), Institutionen för sociala och psykologiska studier (from 2013).ORCID-id: 0000-0001-8102-8168
2019 (engelsk)Inngår i: HCI for Cybersecurity, Privacy and Trust: First International Conference, HCI-CPT 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Orlando, FL, USA, July 26–31, 2019, Proceedings / [ed] Abbas Moallem, Cham, Switzerland: Springer, 2019, s. 355-370Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The importance and perception of privacy varies from one context to the other. However, everyone values his or her privacy to a certain extent. The subjectivity of that value, attitudes, and behaviors would depend on different entangling factors. It is important to understand the motivation that influences human behavior, whether to protect or share their information. In this paper, we aim at understanding the boundaries of privacy, factors influencing information sharing behavior including experiences (reciprocities of privacy), and efforts taken to protect one’s data. We collected data using quantitative (survey/quiz) and qualitative means (focus groups). In the survey/quiz, our results showed that intrusion experience and awareness have a significant correlation between sharing of data. Furthermore, our focus groups results yielded details on influencing factors for privacy reciprocities and tradeoffs. We discuss our results in terms of privacy incentives and factors influencing the sharing behavior of their information. Finally, we highlight the complexity of behavior where intrinsic and extrinsic motivations could clash and result in a dilemma such as the privacy paradox phenomenon. © 2019, Springer Nature Switzerland AG.

sted, utgiver, år, opplag, sider
Cham, Switzerland: Springer, 2019. s. 355-370
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11594
Emneord [en]
Behavior, Incentive, Motivation, Privacy, Privacy paradox, Reciprocity, Behavioral research, Data privacy, Human computer interaction, Information dissemination, Surveys, Extrinsic motivation, Focus groups, Human behaviors, Information sharing, Privacy intrusion, Computer privacy
HSV kategori
Forskningsprogram
Datavetenskap; Psykologi
Identifikatorer
URN: urn:nbn:se:kau:diva-75636DOI: 10.1007/978-3-030-22351-9_24Scopus ID: 2-s2.0-85069853461ISBN: 9783030223502 (tryckt)OAI: oai:DiVA.org:kau-75636DiVA, id: diva2:1369655
Konferanse
21st HCI International Conference, HCII 2019, July 26–31, 2019, Orlando, FL, USA,
Tilgjengelig fra: 2019-11-12 Laget: 2019-11-12 Sist oppdatert: 2019-12-16bibliografisk kontrollert
Inngår i avhandling
1. Tinkering the Wicked Problem of Privacy: Design Challenges and Opportunities for Crypto-based Services
Åpne denne publikasjonen i ny fane eller vindu >>Tinkering the Wicked Problem of Privacy: Design Challenges and Opportunities for Crypto-based Services
2020 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Data privacy has been growing in importance in recent years, especially with the constant increase of online activity. Consequently, researchers study, design, and develop solutions aimed at enhancing users' data privacy. The wicked problem of data privacy is a dynamic challenge that defies straightforward solutions. Since there are many factors involved in data privacy, such as technological, legal, and human aspects, we can only aim at mitigating rather than solving this wicked problem.

Our aim was to explore challenges and opportunities with a focus on human aspects for designing usable crypto-based privacy-enhancing technologies (PETs). Mainly, there were three PETs in the cloud context included in our studies: malleable signatures, secret sharing, and homomorphic encryption. Based on the three PETs, services were developed within European research projects that were the scope of our user studies. We followed a user-centered design approach by using empirical qualitative and quantitative means for collecting study data. Our results and tinkering conveyed (i) analysis of different categories of user's perspectives, mental models, and trade-offs, (ii) user requirements for PET services, and (iii) user interface design guidelines for PET services. In our contributions, we highlight considerations and guidelines for supporting the design of future solutions.

Abstract [en]

Data privacy has been growing in importance in recent years, especially with the constant increase of online activity. Consequently, researchers study, design, and develop solutions aimed at enhancing users' data privacy. The wicked problem of data privacy is a dynamic challenge that defies straightforward solutions. Since there are many factors involved in data privacy, such as technological, legal, and human aspects, we can only aim at mitigating rather than solving this wicked problem.

Our aim was to explore challenges and opportunities with a focus on human aspects for designing usable crypto-based privacy-enhancing technologies (PETs). Our results and tinkering conveyed (i) analysis of different categories of user's perspectives, mental models, and trade-offs, (ii) user requirements for PET services, and (iii) user interface design guidelines for PET services. In our contributions, we highlight considerations and guidelines for supporting the design of future solutions.

sted, utgiver, år, opplag, sider
Karlstads universitet, 2020. s. 22
Serie
Karlstad University Studies, ISSN 1403-8099 ; 2020:5
Emneord
Data privacy, wicked problems, user-centered design, privacy enhancing technologies, human factors, malleable signatures, secret sharing, homomorphic encryption
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
urn:nbn:se:kau:diva-75992 (URN)978-91-7867-077-2 (ISBN)978-91-7867-087-1 (ISBN)
Disputas
2020-01-30, 21A342, Eva Eriksson, 10:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2020-01-09 Laget: 2019-12-16 Sist oppdatert: 2020-01-27bibliografisk kontrollert

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