{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,10]],"date-time":"2026-05-10T06:44:20Z","timestamp":1778395460646,"version":"3.51.4"},"reference-count":15,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,8,15]],"date-time":"2021-08-15T00:00:00Z","timestamp":1628985600000},"content-version":"vor","delay-in-days":226,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Wireless Communications and Mobile Computing"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>In today\u2019s era of technology, especially in the Internet commerce and banking, the transactions done by the Mastercards have been increasing rapidly. The card becomes the highly useable equipment for Internet shopping. Such demanding and inflation rate causes a considerable damage and enhancement in fraud cases also. It is very much necessary to stop the fraud transactions because it impacts on financial conditions over time the anomaly detection is having some important application to detect the fraud detection. A novel framework which integrates Spark with a deep learning approach is proposed in this work. This work also implements different machine learning techniques for detection of fraudulent like random forest, SVM, logistic regression, decision tree, and KNN. Comparative analysis is done by using various parameters. More than 96% accuracy was obtained for both training and testing datasets. The existing system like Cardwatch, web service\u2010based fraud detection, needs labelled data for both genuine and fraudulent transactions. New frauds cannot be found in these existing techniques. The dataset which is used contains transaction made by credit cards in September 2013 by cardholders of Europe. The dataset contains the transactions occurred in 2 days, in which there are 492 fraud transactions out of 284,807 which is 0.172% of all transaction.<\/jats:p>","DOI":"10.1155\/2021\/6079582","type":"journal-article","created":{"date-parts":[[2021,8,16]],"date-time":"2021-08-16T05:28:20Z","timestamp":1629091700000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":86,"title":["An Enhanced Secure Deep Learning Algorithm for Fraud Detection in Wireless Communication"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2533-478X","authenticated-orcid":false,"given":"Sumaya","family":"Sanober","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2022-8446","authenticated-orcid":false,"given":"Izhar","family":"Alam","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4506-6997","authenticated-orcid":false,"given":"Sagar","family":"Pande","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8008-3808","authenticated-orcid":false,"given":"Farrukh","family":"Arslan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0334-3469","authenticated-orcid":false,"given":"Kantilal Pitambar","family":"Rane","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3262-1894","authenticated-orcid":false,"given":"Bhupesh Kumar","family":"Singh","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9019-8230","authenticated-orcid":false,"given":"Aditya","family":"Khamparia","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5106-7609","authenticated-orcid":false,"given":"Mohammad","family":"Shabaz","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,8,15]]},"reference":[{"key":"e_1_2_8_1_2","doi-asserted-by":"crossref","unstructured":"AltitiO. Credit card fraud detection based on machine and deep learning 2020 11th International Conference on Information and Communication Systems (ICICS) 2020 Irbid Jordan 204\u2013208 https:\/\/doi.org\/10.1109\/ICICS49469.2020.239524.","DOI":"10.1109\/ICICS49469.2020.239524"},{"key":"e_1_2_8_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2927266"},{"key":"e_1_2_8_3_2","doi-asserted-by":"publisher","DOI":"10.21533\/pen.v6i2.533"},{"key":"e_1_2_8_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11914-0_24"},{"key":"e_1_2_8_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2736643"},{"key":"e_1_2_8_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2018.2856910"},{"key":"e_1_2_8_7_2","doi-asserted-by":"publisher","DOI":"10.14419\/ijet.v7i2.9356"},{"key":"e_1_2_8_8_2","doi-asserted-by":"crossref","unstructured":"ThennakoonA. BhagyaniC. PremadasaS. MihirangaS. andKuruwitaarachchiN. Real-time credit card fraud detection using machine learning 7 Proceedings of the 9th International Conference on Cloud Computing Data Science & Engineering 2019 Noida India no. 10 488\u2013493 https:\/\/doi.org\/10.1109\/CONFLUENCE.2019.8776942 2-s2.0-85070592652.","DOI":"10.1109\/CONFLUENCE.2019.8776942"},{"key":"e_1_2_8_9_2","first-page":"257","article-title":"Credit card fraud detection using machine learning methodology","volume":"8","author":"Shukur H. A.","year":"2019","journal-title":"International Journal of Computer Science and Mobile Computing"},{"key":"e_1_2_8_10_2","doi-asserted-by":"publisher","DOI":"10.26438\/ijcse\/v7i4.10601064"},{"key":"e_1_2_8_11_2","doi-asserted-by":"crossref","unstructured":"YuW. F.andWangN. Research on credit card fraud detection model based on distance sum IJCAI international joint conference on artificial intelligence 2009 Hainan China 353\u2013356 https:\/\/doi.org\/10.1109\/JCAI.2009.146 2-s2.0-70350749301.","DOI":"10.1109\/JCAI.2009.146"},{"key":"e_1_2_8_12_2","unstructured":"https:\/\/towardsdatascience.com\/logistic-regression-detailed-overview-46c4da4303bc."},{"key":"e_1_2_8_13_2","unstructured":"Autoencoders tutorial : a beginner\u2019s guide to autoencoders https:\/\/www.edureka.co\/blog\/autoencoders-tutorial\/."},{"key":"e_1_2_8_14_2","doi-asserted-by":"crossref","unstructured":"MengQ. CatchpooleD. SkillicomD. andKennedyP. J. Relational autoencoder for feature extraction 2017 International Joint Conference on Neural Networks (IJCNN) 2017 Anchorage AK 364\u2013371.","DOI":"10.1109\/IJCNN.2017.7965877"},{"key":"e_1_2_8_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.09.005"}],"container-title":["Wireless Communications and Mobile Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/wcmc\/2021\/6079582.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/wcmc\/2021\/6079582.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/6079582","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T13:33:29Z","timestamp":1723037609000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/6079582"}},"subtitle":[],"editor":[{"given":"VIMAL","family":"SHANMUGANATHAN","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":15,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/6079582"],"URL":"https:\/\/doi.org\/10.1155\/2021\/6079582","archive":["Portico"],"relation":{},"ISSN":["1530-8669","1530-8677"],"issn-type":[{"value":"1530-8669","type":"print"},{"value":"1530-8677","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2021-07-09","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-07-26","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-08-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"6079582"}}