私隐分类系统检讨

IF 13.3 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Paola Inverardi , Patrizio Migliarini , Massimiliano Palmiero
{"title":"私隐分类系统检讨","authors":"Paola Inverardi ,&nbsp;Patrizio Migliarini ,&nbsp;Massimiliano Palmiero","doi":"10.1016/j.cosrev.2023.100574","DOIUrl":null,"url":null,"abstract":"<div><p>In the modern digital world users need to make privacy and security choices that have far-reaching consequences. Researchers are increasingly studying people’s decisions when facing with privacy and security trade-offs, the pressing and time consuming disincentives that influence those decisions, and methods to mitigate them. This work aims to present a systematic review of the literature on privacy categorisation, which has been defined in terms of profile, profiling, segmentation, clustering and personae. Privacy categorisation involves the possibility to classify users according to specific prerequisites, such as their ability to manage privacy issues, or in terms of which type of and how many personal information they decide or do not decide to disclose. Privacy categorisation has been defined and used for different purposes. The systematic review focuses on three main research questions that investigate the study contexts, i.e. the motivations and research questions, that propose privacy categorisations; the methodologies and results of privacy categorisations; the evolution of privacy categorisations over time. Ultimately it tries to provide an answer whether privacy categorisation as a research attempt is still meaningful and may have a future.</p></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"49 ","pages":"Article 100574"},"PeriodicalIF":13.3000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Systematic review on privacy categorisation\",\"authors\":\"Paola Inverardi ,&nbsp;Patrizio Migliarini ,&nbsp;Massimiliano Palmiero\",\"doi\":\"10.1016/j.cosrev.2023.100574\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In the modern digital world users need to make privacy and security choices that have far-reaching consequences. Researchers are increasingly studying people’s decisions when facing with privacy and security trade-offs, the pressing and time consuming disincentives that influence those decisions, and methods to mitigate them. This work aims to present a systematic review of the literature on privacy categorisation, which has been defined in terms of profile, profiling, segmentation, clustering and personae. Privacy categorisation involves the possibility to classify users according to specific prerequisites, such as their ability to manage privacy issues, or in terms of which type of and how many personal information they decide or do not decide to disclose. Privacy categorisation has been defined and used for different purposes. The systematic review focuses on three main research questions that investigate the study contexts, i.e. the motivations and research questions, that propose privacy categorisations; the methodologies and results of privacy categorisations; the evolution of privacy categorisations over time. Ultimately it tries to provide an answer whether privacy categorisation as a research attempt is still meaningful and may have a future.</p></div>\",\"PeriodicalId\":48633,\"journal\":{\"name\":\"Computer Science Review\",\"volume\":\"49 \",\"pages\":\"Article 100574\"},\"PeriodicalIF\":13.3000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Science Review\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1574013723000412\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Science Review","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574013723000412","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

在现代数字世界中,用户需要做出具有深远影响的隐私和安全选择。研究人员越来越多地研究人们在面临隐私和安全权衡时的决策,影响这些决策的紧迫和耗时的抑制因素,以及缓解这些影响的方法。这项工作旨在对隐私分类的文献进行系统综述,隐私分类已从个人资料、特征分析、分割、聚类和人物角色等方面进行了定义。隐私分类包括根据特定的先决条件对用户进行分类的可能性,例如他们管理隐私问题的能力,或者根据他们决定或不决定披露的个人信息的类型和数量。隐私分类已被定义并用于不同的目的。系统综述侧重于调查研究背景的三个主要研究问题,即提出隐私分类的动机和研究问题;隐私分类的方法和结果;隐私分类随时间的演变。最终,它试图提供一个答案,即隐私分类作为一种研究尝试是否仍然有意义,是否有未来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic review on privacy categorisation

In the modern digital world users need to make privacy and security choices that have far-reaching consequences. Researchers are increasingly studying people’s decisions when facing with privacy and security trade-offs, the pressing and time consuming disincentives that influence those decisions, and methods to mitigate them. This work aims to present a systematic review of the literature on privacy categorisation, which has been defined in terms of profile, profiling, segmentation, clustering and personae. Privacy categorisation involves the possibility to classify users according to specific prerequisites, such as their ability to manage privacy issues, or in terms of which type of and how many personal information they decide or do not decide to disclose. Privacy categorisation has been defined and used for different purposes. The systematic review focuses on three main research questions that investigate the study contexts, i.e. the motivations and research questions, that propose privacy categorisations; the methodologies and results of privacy categorisations; the evolution of privacy categorisations over time. Ultimately it tries to provide an answer whether privacy categorisation as a research attempt is still meaningful and may have a future.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Computer Science Review
Computer Science Review Computer Science-General Computer Science
CiteScore
32.70
自引率
0.00%
发文量
26
审稿时长
51 days
期刊介绍: Computer Science Review, a publication dedicated to research surveys and expository overviews of open problems in computer science, targets a broad audience within the field seeking comprehensive insights into the latest developments. The journal welcomes articles from various fields as long as their content impacts the advancement of computer science. In particular, articles that review the application of well-known Computer Science methods to other areas are in scope only if these articles advance the fundamental understanding of those methods.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信