计算机科学 ›› 2021, Vol. 48 ›› Issue (9): 9-20.doi: 10.11896/jsjkx.201000011

所属专题: 智能数据治理技术与系统

• 智能数据治理技术与系统* 上一篇    下一篇

面向跨模态隐私保护的AI治理法律技术化框架

雷羽潇, 段玉聪   

  1. 海南大学计算机科学与技术学院 海口570228
  • 收稿日期:2020-10-03 修回日期:2021-04-04 出版日期:2021-09-15 发布日期:2021-09-10
  • 通讯作者: 段玉聪(duanyucong@hotmail.com)
  • 作者简介:229597800@qq.com
  • 基金资助:
    国家自然科学基金(61662021,72062015);海南省自然科学基金项目(620RC561);海南省教育厅项目(Hnky2019-13);海南大学教育教学改革研究项目(HDJY2102,HDJWJG03)

AI Governance Oriented Legal to Technology Bridging Framework for Cross-modal Privacy Protection

LEI Yu-xiao , DUAN Yu-cong   

  1. School of Computer Science and Technology,Hainan University,Haikou 570228,China
  • Received:2020-10-03 Revised:2021-04-04 Online:2021-09-15 Published:2021-09-10
  • About author:LEI Yu-xiao,born in 1997,postgra-duate.Her main research interests include privacy protection,knowledge graphs and big data.
    DUAN Yu-cong,born in 1977,Ph.D,professor,Ph.D.supervisor,is a senior member of China Computer Federation.His main research interests include service computing,artificial intelligence,knowledge graph and big data.
  • Supported by:
    National Natural Science Foundation of China(61662021,72062015),Natural Science Foundation of Hainan Province,China(620RC561),Program of Education Bureau of Hainan Province,China(Hnky2019-13) and Educational Reform Research Program of Hainan University,China(HDJY2102,HDJWJG03)

摘要: 随着虚拟社区在网络用户中的普及,虚拟社区群已经成为一个小型社会,可通过用户浏览所留下的“虚拟痕迹”和发布的用户生成内容提炼出与用户相关的隐私类型资源。根据隐私类型资源自身的特性,可将其分类为数据资源、信息资源和知识资源,三者构成了用户的数据信息知识与智慧图谱(DIKW图谱)。虚拟社区中的隐私类型资源有4个流通过程,即隐私资源的感知、存储、传输和处理;4个过程分别由3个参与方(用户、AI系统和访问者)单独或合作完成,3个参与方所拥有的隐私权包括知情权、参与权、遗忘权和监督权。通过明确3个参与方在4个流通过程中的隐私权范围,结合隐私价值保护,设计了匿名保护机制/风险评估机制和监督机制,用于构建一个虚拟社区隐私保护的AI治理法律框架。

关键词: 数据、信息、知识与智慧图谱, 虚拟社区, 隐私保护, 隐私的价值, 隐私权

Abstract: With the popularity of virtual communities among network users,virtual community groups have become a small society,which can extract user-related privacy resources through the “virtual traces” left by users' browsing and user-generated content user published.Privacy resources can be classified into data resources,information resources and knowledge resources according to their characteristics,which constitute the data,information,knowledge,and wisdom graph (DIKW graph).There are four circulation processes for privacy resources in virtual communities,namely,the sensing,storage,transfern,and processing of privacy resources.The four processes are respectively completed by the three participants,the user,the AI system,and the visitor individually or in cooperation.The right to privacy includes the right to know,the right to participate,the right to forget,and the right to supervise.By clarifying the scope of privacy rights of the three participants in the four circulation processes,and combining the protection of privacy values,an anonymous protection mechanism,risk assessment mechanism and supervision mechanism are designed to build an AI governance legal framework for privacy protection of virtual communities.

Key words: Data\Information\Knowledge and Wisdom graph, Privacy protection, Right to privacy, Value of privacy, Virtual community

中图分类号: 

  • TP309
[1]O'NEILL E,KOSTAKOS V,KINDBERG T,et al.Instrumenting the City:Developing Methods for Observing and Understanding the Digital Cityscape [C]//Lecture Notes in Computer Science.2006,4206:315-322.
[2]GIRARDIN F,CALABRESE F,FIORE F D,et al.Digital Footprinting:uncovering tourists with user-generated content[J].IEEE Pervasive Computing,2008,7(4):36-43.
[3]HU H,GE Y J,HOU D Y.Using Web Crawler Technology for Geo-Events Analysis:A Case Study of theHuangyan Island Incident[J].Sustainability,2014,6(4):1896-1912.
[4]KRUMM J,DAVIES N,NARAYANASWAMI C.User-generated content[J].IEEE Pervasive Computing,2008,7(4):10-11.
[5]LEI Y,DUAN Y.Personality Classification and ConversionMethod of Virtual Community Personnel Based on DIKW Graph[J].Chinese Journal of Applied Sciences,2020,38(5):803-824.
[6]ULRIKE H.Reviewing person's value of privacy of online social networking[J].Internet Research,2011,21(4):384-407.
[7]BOZDA E.Bias in algorithmic filtering and personalization[J].Ethics & Information Technology,2013,15(3):209-227.
[8]MITTELSTADT B D,ALLO P,TADDEO M,et al.The ethics of algorithms:mapping the debate[J].Big Data and Society,2016,3(2):1-21.
[9]DUAN Y C,ZHAN L G,ZHANG XY,et al.Formalizing DIKW Architecture for Modeling Security and Privacy as Typed Resources[C]//Testbeds and Research Infrastructures for the Development of Networks and Communities.2018:157-168.
[10]DUAN Y C,SHAO L X,HU G Z,et al.Specifying architecture of knowledge graph with data graph,information graph,know-ledge graph and wisdom graph[C]//IEEE International Confe-rence on Software Engineering Research.IEEE,2017.
[11]SONG Z Y,DUAN Y C,WAN S X,et al.Processing Optimization of Typed Resources with Synchronized Storage and Computation Adaptation in Fog Computing[J].Wireless Communications and Mobile Computing,2018,2018:1-13.
[12]GURSES S,ALAMO J M D.Privacy Engineering:Shaping an Emerging Field of Research and Practice[J].IEEE Security & Privacy,2016,14(2):40-46.
[13]DUAN Y C,SUN X B,CHE H Y,et al.Modeling Data,Information and Knowledge for Security Protection of Hybrid IoT and Edge Resources[J].IEEE Access,2019,7:99161-99176.
[14]DUAN Y C.Existence Computation:Revelation on Entity vs.Relationship for Relationship Defined Everything of Semantics[C]//2019 20th IEEE/ACIS International Conference on Software Engineering,Artificial Intelligence,Networking and Parallel/Distributed Computing (SNPD).2019:139-144.
[15]OLSON D L.Data mining in business services[J].Service Business,2007,1(3):181-193.
[16]KURGAN L A,MUSILEK P.A survey of Knowledge Discovery and Data Mining process models[J].The Knowledge Enginee-ring Review,2006,21(1):1-24.
[17]VISSER W,HINDRIKS K V,JONKER C M.Argumentation-Based Qualitative Preference Modelling with Incomplete and Uncertain Information[J].Group Decision & Negotiation,2012,21(1):99-127.
[18]MITTELSTAD B.From Individual to Group Privacy in Big Data Analytics[J].Philosophy & Technology,2017,30(4):475-494.
[19]VASSILIADIS P.A Survey of Extract-Transform-Load Technology[J].International Journal of Data Warehousing & Mi-ning,2009,5(3):1-27.
[20]HARIRI R H,FREDERICKS E M,BOWERS K M.Uncertainty in big data analytics:survey,opportunities,and challenges[J].Journal of Big Data,2019,6(1):44.
[21]HARPER J.Privacy and the Four Categories of InformationTechnology[R].American Enterprise Institute Report,2020.
[22]EKSTRAND M D,JOSHAGHANI R,MEHRPOUYAN H.Privacy for All:Ensuring Fair and Equitable Privacy Protections[C]//Proceedings of the 1st Conference on Fairness,Accountability and Transparency.2018:35-47.
[23]HOFFMAN S,PODGURSKI A.Balancing Privacy,Autonomy,and Scientific Needs In Electronic Health Records Research[J].SMU law review:a publication of Southern Methodist University School of Law,2012,65(1):85-144.
[24]SOLOVE D J.The Future of Reputation:Gossip,Rumor,and Privacy on the Internet[M]//Yale University Press,2007.
[25]GORMAN D.Rights in Collision: The Individual Right of Privacy and the Public Right To Know[J].Asahi Law Review Asahi University School of Law,1978,35(2):249-257.
[26]MANTELERO A.The EU Proposal for a General Data Protection Regulation and the roots of the right to be forgotten[J].Computer Law & Security Review,2013,29(3),229-235.
[27]WALLACE K A.Anonymity[J].Ethics and Information Technology,1999,1(1):21-31.
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