{"title":"Design of a cognitive tool to detect malicious images using the smart phone","authors":"Hiroyuki Nishiyama, F. Mizoguchi","doi":"10.1109/ICCI-CC.2013.6622276","DOIUrl":null,"url":null,"abstract":"In this study, we design a cognitive tool to detect malicious images using a smart phone. This tool can learn shot images taken with the camera of a smart phone and automatically classify the new image as an malicious image in the smart phone. To develop the learning and classifier tool, we implement an image analysis function and a learning and classifier function using a support vector machine (SVM) with the smart phone. With this tool, the user can collect image data with the camera of a smart phone, create learning data, and classify the new image data according to the learning data in the smart phone. In this study, we apply this tool to a user interface of a cosmetics recommendation service system and demonstrate its effectiveness by in reducing the load of the diagnosis server in this service and improving the user service.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCI-CC.2013.6622276","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this study, we design a cognitive tool to detect malicious images using a smart phone. This tool can learn shot images taken with the camera of a smart phone and automatically classify the new image as an malicious image in the smart phone. To develop the learning and classifier tool, we implement an image analysis function and a learning and classifier function using a support vector machine (SVM) with the smart phone. With this tool, the user can collect image data with the camera of a smart phone, create learning data, and classify the new image data according to the learning data in the smart phone. In this study, we apply this tool to a user interface of a cosmetics recommendation service system and demonstrate its effectiveness by in reducing the load of the diagnosis server in this service and improving the user service.