在刑事情报中使用“大”元数据:了解限制和适当的保障措施

A. Maurushat, L. B. Moses, D. Vaile
{"title":"在刑事情报中使用“大”元数据:了解限制和适当的保障措施","authors":"A. Maurushat, L. B. Moses, D. Vaile","doi":"10.1145/2746090.2746110","DOIUrl":null,"url":null,"abstract":"Using Internet Service Provider 'Big' metadata as a case study, we examine legal and ethical issues with machine learning Big Data tools developed and deployed in Australia for law enforcement intelligence purposes. In order to do this, we outline the benefits, limitations and risks of these tools, analyze current methods for de-identification and anonymisation, and discuss necessary safeguards.","PeriodicalId":309125,"journal":{"name":"Proceedings of the 15th International Conference on Artificial Intelligence and Law","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Using 'big' metadata for criminal intelligence: understanding limitations and appropriate safeguards\",\"authors\":\"A. Maurushat, L. B. Moses, D. Vaile\",\"doi\":\"10.1145/2746090.2746110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Using Internet Service Provider 'Big' metadata as a case study, we examine legal and ethical issues with machine learning Big Data tools developed and deployed in Australia for law enforcement intelligence purposes. In order to do this, we outline the benefits, limitations and risks of these tools, analyze current methods for de-identification and anonymisation, and discuss necessary safeguards.\",\"PeriodicalId\":309125,\"journal\":{\"name\":\"Proceedings of the 15th International Conference on Artificial Intelligence and Law\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 15th International Conference on Artificial Intelligence and Law\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2746090.2746110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 15th International Conference on Artificial Intelligence and Law","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2746090.2746110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

以互联网服务提供商“大”元数据为例,我们研究了澳大利亚为执法情报目的开发和部署的机器学习大数据工具的法律和道德问题。为了做到这一点,我们概述了这些工具的好处、局限性和风险,分析了当前的去识别和匿名化方法,并讨论了必要的保障措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using 'big' metadata for criminal intelligence: understanding limitations and appropriate safeguards
Using Internet Service Provider 'Big' metadata as a case study, we examine legal and ethical issues with machine learning Big Data tools developed and deployed in Australia for law enforcement intelligence purposes. In order to do this, we outline the benefits, limitations and risks of these tools, analyze current methods for de-identification and anonymisation, and discuss necessary safeguards.
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
自引率
0.00%
发文量
0
×
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