{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T13:06:52Z","timestamp":1762348012863,"version":"build-2065373602"},"reference-count":0,"publisher":"SASA Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JISIS"],"published-print":{"date-parts":[[2025,8,30]]},"abstract":"<jats:p>An internet-wide computer network is made up of several machines that are connected, whether the \nnetwork is built using traditional infrastructure or cloud computing technology. All of these goods, \nservices and programs come together in one technical framework, together with a large amount of \ndatabase storage, creating a valuable resource variety. Internet services that enable consumers to \nmake use of the vast possibilities provided by cloud technology facilitate access to these products. \nCloud computing's many benefits include low cost, easy-to-use self-service accessibility, built-in \nflexibility, smooth scalability, and efficient use of virtualised resources, which are driving creativity \nand effectiveness in contemporary technology paradigms. However, there are several security \nvulnerabilities in the cloud computing (CC) setup. Trojan horses (TH) are among the most frequent \nsecurity issues in the context of computing in the cloud. The TH can compromise services offered \nby cloud computing and harm virtual machines, apps and resources in the cloud infrastructure. TH \nassaults could be hazardous, intricate and hard to identify. We begin by assembling an extensive \ndataset with TH Infections for Securing Financial Cloud data. We proposed the Adaptive Butterfly\noptimised Hierarchical Random Forest (ABO-HRF) technique for accurately estimating TH \ndetection. The suggested approach improves the accuracy (89.56%), precision (88.32%), recall \n(82.54%), and F1 score (84.68%) compared with the current methods.<\/jats:p>","DOI":"10.58346\/jisis.2025.i3.013","type":"journal-article","created":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T09:34:33Z","timestamp":1762335273000},"page":"189-199","source":"Crossref","is-referenced-by-count":0,"title":["Study on Identification of Trojan Horse Infections for Securing  Financial Cloud"],"prefix":"10.58346","volume":"15","author":[{"given":"Yoghesh","family":"Dharangutti","sequence":"first","affiliation":[]},{"given":"Dr. Sumitra","family":"Padmanabhan","sequence":"additional","affiliation":[]},{"given":"R. Hannah","family":"Jessie Rani","sequence":"additional","affiliation":[]},{"given":"Manish","family":"Nagpal","sequence":"additional","affiliation":[]},{"given":"Divya","family":"Paikaray","sequence":"additional","affiliation":[]},{"given":"Shreya","family":"Ghosal","sequence":"additional","affiliation":[]}],"member":"37075","published-online":{"date-parts":[[2025,8,30]]},"container-title":["Journal of Internet Services and Information Security"],"original-title":[],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T13:02:54Z","timestamp":1762347774000},"score":1,"resource":{"primary":{"URL":"https:\/\/jisis.org\/wp-content\/uploads\/2025\/10\/2025.I3.013.pdf"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,30]]},"references-count":0,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,8,30]]},"published-print":{"date-parts":[[2025,8,30]]}},"URL":"https:\/\/doi.org\/10.58346\/jisis.2025.i3.013","relation":{},"ISSN":["2182-2069","2182-2077"],"issn-type":[{"type":"print","value":"2182-2069"},{"type":"electronic","value":"2182-2077"}],"subject":[],"published":{"date-parts":[[2025,8,30]]}}}