{"title":"通过鼠标处理方法实现系统用户的真实性","authors":"Kiran Kamble, Nandinee Mudegol, Pooja Mundada, Abhijeet Urunkar","doi":"10.1109/icac353642.2021.9697250","DOIUrl":null,"url":null,"abstract":"The proposed work narrate a behavioural bio-metric approach to confirm authenticated users dynamically based on their mouse motion. A self–generated mouse data [9] was used to extract features to categorize the user’s mouse handling pattern which is different from other users. The model built is trained using the Gaussian Naive Bayes Classifier for quick and accurate classification of data. The proposed model performs better than previously used models in all evaluation metrics including, accuracy, false accept rate, false reject rate.","PeriodicalId":196238,"journal":{"name":"2021 International Conference on Advances in Computing, Communication, and Control (ICAC3)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Authenticity of System Users via Mouse Handling Method\",\"authors\":\"Kiran Kamble, Nandinee Mudegol, Pooja Mundada, Abhijeet Urunkar\",\"doi\":\"10.1109/icac353642.2021.9697250\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The proposed work narrate a behavioural bio-metric approach to confirm authenticated users dynamically based on their mouse motion. A self–generated mouse data [9] was used to extract features to categorize the user’s mouse handling pattern which is different from other users. The model built is trained using the Gaussian Naive Bayes Classifier for quick and accurate classification of data. The proposed model performs better than previously used models in all evaluation metrics including, accuracy, false accept rate, false reject rate.\",\"PeriodicalId\":196238,\"journal\":{\"name\":\"2021 International Conference on Advances in Computing, Communication, and Control (ICAC3)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Advances in Computing, Communication, and Control (ICAC3)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icac353642.2021.9697250\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Advances in Computing, Communication, and Control (ICAC3)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icac353642.2021.9697250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Authenticity of System Users via Mouse Handling Method
The proposed work narrate a behavioural bio-metric approach to confirm authenticated users dynamically based on their mouse motion. A self–generated mouse data [9] was used to extract features to categorize the user’s mouse handling pattern which is different from other users. The model built is trained using the Gaussian Naive Bayes Classifier for quick and accurate classification of data. The proposed model performs better than previously used models in all evaluation metrics including, accuracy, false accept rate, false reject rate.