{"title":"Deep learning for the detection of fraudulent credit card activity","authors":"Rishabh Saxena, Dalwinder Singh, Manik Rakhra, Shivali Dwivedi, Ashutosh Kumar Singh","doi":"10.1109/IC3I56241.2022.10072543","DOIUrl":null,"url":null,"abstract":"As the world is forwarding to new technology’s innovation and research. for one keeping their privacy defended is the most rock-hard task in the current scenario’s privacy breach is common in which offensive and unauthorized access by a third party is committed in order to steal the confidential information which termed in cyber security attack as spyware. such of the massive and worldwide problems can be tackled with the help of deep learning this research paper will demonstrate in modelling of data set using deep learning. This study intends to distinguish between legitimate and fraudulent financial dealings by employing a variety of deep learning techniques, including the convolutional neural network (CNN) and the long short-term memory (LSTM), both of which are utilised to make accurate predictions regarding financial dealings. As far as we will analyze and pre-process the data set and compare both CNN and LSTM with each other in order to find the optimal solution.","PeriodicalId":274660,"journal":{"name":"2022 5th International Conference on Contemporary Computing and Informatics (IC3I)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th International Conference on Contemporary Computing and Informatics (IC3I)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3I56241.2022.10072543","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
As the world is forwarding to new technology’s innovation and research. for one keeping their privacy defended is the most rock-hard task in the current scenario’s privacy breach is common in which offensive and unauthorized access by a third party is committed in order to steal the confidential information which termed in cyber security attack as spyware. such of the massive and worldwide problems can be tackled with the help of deep learning this research paper will demonstrate in modelling of data set using deep learning. This study intends to distinguish between legitimate and fraudulent financial dealings by employing a variety of deep learning techniques, including the convolutional neural network (CNN) and the long short-term memory (LSTM), both of which are utilised to make accurate predictions regarding financial dealings. As far as we will analyze and pre-process the data set and compare both CNN and LSTM with each other in order to find the optimal solution.