{"title":"大数据和云计算中客户位置的隐私","authors":"Imad Ali Hassoon, N. Tapus, Anwar Chitheer Jasim","doi":"10.1109/SACI.2018.8440940","DOIUrl":null,"url":null,"abstract":"Amid the very hot issues, nowadays, the one related to Locations' privacy (GPS related) finds itself in top position. When it comes to talking about clients' locations in cloud or big data, the probable risk to privacy of clients' location is one of the major challenges should to be faced. In the recent years, a lot of developers and researchers have been paying attention to improve methods to provide privacy for data of clients' locations which it always processed by third-party. Big data could be like a puzzle for many researchers if they didn't understand it in the correct-side. Big data has to be understood as the process of gathering as much data as can be permitted in order to collect knowledge out of them (ideally in ground-breaking ways). so, this concept gives us attention that is privacy of clients' locations in cloud or big data could be under risks if it is used to collect knowledge or sell it to third-party. In our research, we try to show how we have implemented our algorithm (Diff-Anonym) in real data set (available at http://openaddresses.io) as to offer privacy for the clients' Locations in Big Data and cloud computing, as well as to improve our previous work which was simulation in normal data that appeared little differences in the results.","PeriodicalId":126087,"journal":{"name":"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Privacy of Clients' Locations in Big Data and Cloud Computing\",\"authors\":\"Imad Ali Hassoon, N. Tapus, Anwar Chitheer Jasim\",\"doi\":\"10.1109/SACI.2018.8440940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Amid the very hot issues, nowadays, the one related to Locations' privacy (GPS related) finds itself in top position. When it comes to talking about clients' locations in cloud or big data, the probable risk to privacy of clients' location is one of the major challenges should to be faced. In the recent years, a lot of developers and researchers have been paying attention to improve methods to provide privacy for data of clients' locations which it always processed by third-party. Big data could be like a puzzle for many researchers if they didn't understand it in the correct-side. Big data has to be understood as the process of gathering as much data as can be permitted in order to collect knowledge out of them (ideally in ground-breaking ways). so, this concept gives us attention that is privacy of clients' locations in cloud or big data could be under risks if it is used to collect knowledge or sell it to third-party. In our research, we try to show how we have implemented our algorithm (Diff-Anonym) in real data set (available at http://openaddresses.io) as to offer privacy for the clients' Locations in Big Data and cloud computing, as well as to improve our previous work which was simulation in normal data that appeared little differences in the results.\",\"PeriodicalId\":126087,\"journal\":{\"name\":\"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SACI.2018.8440940\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2018.8440940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Privacy of Clients' Locations in Big Data and Cloud Computing
Amid the very hot issues, nowadays, the one related to Locations' privacy (GPS related) finds itself in top position. When it comes to talking about clients' locations in cloud or big data, the probable risk to privacy of clients' location is one of the major challenges should to be faced. In the recent years, a lot of developers and researchers have been paying attention to improve methods to provide privacy for data of clients' locations which it always processed by third-party. Big data could be like a puzzle for many researchers if they didn't understand it in the correct-side. Big data has to be understood as the process of gathering as much data as can be permitted in order to collect knowledge out of them (ideally in ground-breaking ways). so, this concept gives us attention that is privacy of clients' locations in cloud or big data could be under risks if it is used to collect knowledge or sell it to third-party. In our research, we try to show how we have implemented our algorithm (Diff-Anonym) in real data set (available at http://openaddresses.io) as to offer privacy for the clients' Locations in Big Data and cloud computing, as well as to improve our previous work which was simulation in normal data that appeared little differences in the results.