S. Tanimoto, Ken Takahashi, Taro Yabuki, Kazuhiko Kato, M. Iwashita, Hiroyuki Sato, Atsushi Kanai
{"title":"生命日志服务中的风险评估量化","authors":"S. Tanimoto, Ken Takahashi, Taro Yabuki, Kazuhiko Kato, M. Iwashita, Hiroyuki Sato, Atsushi Kanai","doi":"10.1109/SNPD.2014.6888723","DOIUrl":null,"url":null,"abstract":"A Life Log Service that handles action records, such as an individual search logs and data on shoppers' browsing and buying habits, have attracted attention with the spread of the Internet. Life Log Service is thought to present various risks to private information, such as personal information. For this reason, countermeasures to these risks need to be investigated. We have already qualitatively analyzed the risks of life log services. To extract the specific risks of using a life log service comprehensively, we used a Risk Breakdown Structure (RBS), which is the typical risk-analysis method. Furthermore, after risks were analyzed, concrete countermeasures were proposed. However, these results need to be quantitatively evaluated from a more practical viewpoint. In this paper, the validity is visualized by performing quantitive risk assessment on the proposed countermeasures for risks in the life log obtained in our previous research. Specifically, the risk value based on a risk formula is computed to a risk factor and its proposed countermeasures. Thereby, the effects of the proposed countermeasures on risks of the life log service found in previous research are evaluated quantitatively, and this will contribute to spreading and promoting the life log service.","PeriodicalId":272932,"journal":{"name":"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"642 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Risk assessment quantification in life log service\",\"authors\":\"S. Tanimoto, Ken Takahashi, Taro Yabuki, Kazuhiko Kato, M. Iwashita, Hiroyuki Sato, Atsushi Kanai\",\"doi\":\"10.1109/SNPD.2014.6888723\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Life Log Service that handles action records, such as an individual search logs and data on shoppers' browsing and buying habits, have attracted attention with the spread of the Internet. Life Log Service is thought to present various risks to private information, such as personal information. For this reason, countermeasures to these risks need to be investigated. We have already qualitatively analyzed the risks of life log services. To extract the specific risks of using a life log service comprehensively, we used a Risk Breakdown Structure (RBS), which is the typical risk-analysis method. Furthermore, after risks were analyzed, concrete countermeasures were proposed. However, these results need to be quantitatively evaluated from a more practical viewpoint. In this paper, the validity is visualized by performing quantitive risk assessment on the proposed countermeasures for risks in the life log obtained in our previous research. Specifically, the risk value based on a risk formula is computed to a risk factor and its proposed countermeasures. Thereby, the effects of the proposed countermeasures on risks of the life log service found in previous research are evaluated quantitatively, and this will contribute to spreading and promoting the life log service.\",\"PeriodicalId\":272932,\"journal\":{\"name\":\"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)\",\"volume\":\"642 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SNPD.2014.6888723\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2014.6888723","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Risk assessment quantification in life log service
A Life Log Service that handles action records, such as an individual search logs and data on shoppers' browsing and buying habits, have attracted attention with the spread of the Internet. Life Log Service is thought to present various risks to private information, such as personal information. For this reason, countermeasures to these risks need to be investigated. We have already qualitatively analyzed the risks of life log services. To extract the specific risks of using a life log service comprehensively, we used a Risk Breakdown Structure (RBS), which is the typical risk-analysis method. Furthermore, after risks were analyzed, concrete countermeasures were proposed. However, these results need to be quantitatively evaluated from a more practical viewpoint. In this paper, the validity is visualized by performing quantitive risk assessment on the proposed countermeasures for risks in the life log obtained in our previous research. Specifically, the risk value based on a risk formula is computed to a risk factor and its proposed countermeasures. Thereby, the effects of the proposed countermeasures on risks of the life log service found in previous research are evaluated quantitatively, and this will contribute to spreading and promoting the life log service.