{"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}
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.