{"title":"基于融合方法的在线市场系统反馈欺诈检测","authors":"M. Elfahmi, G. Saptawati","doi":"10.1109/ICODSE.2015.7436981","DOIUrl":null,"url":null,"abstract":"For online marketplace system, feedback is the evaluation given by a buyer to a seller based on a certain transaction aspects. Feedback fraud is a fraud that happens when a seller exploits the feedback system to gain as much good feedback as possible. This paper adapted Fusion Approach, a fraud detection method on credit cards, and used it to detect feedback fraud case. Fusion Approach is a fraud detection method that combines multiple evidences from current action and past actions. To adapt Fusion Approach in feedback fraud case, we modified the underlying rules, parameters, components, and detection target on this method. Evaluation with a real word dataset proved that this method gives good accuracy with low false alarm and takes reasonable amount of detection time.","PeriodicalId":374006,"journal":{"name":"2015 International Conference on Data and Software Engineering (ICoDSE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Feedback fraud detection on online marketplace system based on fusion approach\",\"authors\":\"M. Elfahmi, G. Saptawati\",\"doi\":\"10.1109/ICODSE.2015.7436981\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For online marketplace system, feedback is the evaluation given by a buyer to a seller based on a certain transaction aspects. Feedback fraud is a fraud that happens when a seller exploits the feedback system to gain as much good feedback as possible. This paper adapted Fusion Approach, a fraud detection method on credit cards, and used it to detect feedback fraud case. Fusion Approach is a fraud detection method that combines multiple evidences from current action and past actions. To adapt Fusion Approach in feedback fraud case, we modified the underlying rules, parameters, components, and detection target on this method. Evaluation with a real word dataset proved that this method gives good accuracy with low false alarm and takes reasonable amount of detection time.\",\"PeriodicalId\":374006,\"journal\":{\"name\":\"2015 International Conference on Data and Software Engineering (ICoDSE)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Data and Software Engineering (ICoDSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICODSE.2015.7436981\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Data and Software Engineering (ICoDSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICODSE.2015.7436981","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feedback fraud detection on online marketplace system based on fusion approach
For online marketplace system, feedback is the evaluation given by a buyer to a seller based on a certain transaction aspects. Feedback fraud is a fraud that happens when a seller exploits the feedback system to gain as much good feedback as possible. This paper adapted Fusion Approach, a fraud detection method on credit cards, and used it to detect feedback fraud case. Fusion Approach is a fraud detection method that combines multiple evidences from current action and past actions. To adapt Fusion Approach in feedback fraud case, we modified the underlying rules, parameters, components, and detection target on this method. Evaluation with a real word dataset proved that this method gives good accuracy with low false alarm and takes reasonable amount of detection time.