{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T13:06:51Z","timestamp":1762348011518,"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>The scheduling and distribution of tasks is one of the biggest problems with cloud computing, a \nplatform that is becoming more and more popular for everyday use and financial applications. \nHowever, one of the main problems in the financial segment remains to be cloud security. Several \nstudies have demonstrated that the financial cloud load balancing system manages the arrangement \nof n tasks in the process flow on cloud devices, which is critical to the effectiveness of the system. \nTo research load balancing and dynamic task prioritization in financial cloud systems, a novel \nadaptive weighted round robin based versatile random forest (AWRR-VRF) strategy was suggested \nin this research. The suggested strategy uses the versatile random forest (VRF) method for dynamic \ntask prioritization depending on security requirements and the adaptive weighted round robin \n(AWRR) approach for effective load balancing in the financial cloud. To categorize the task-oriented \npriority of requests and enable efficient task performance, the VRF is implemented based on user \nbehavior patterns. Based on the suggested methodology, this research is carried out using the Python \nprogram and performance is examined in terms of CPU utilization (0.0100), energy consumption \n(62.675), task prioritization (77,600) and optimized memory usage (5102.50) measures. Task \nsecurity is enhanced to minimize security threats and maximize the protection of financial data. By using the experimental assessment, this research determined that the suggested AWRR-VRF \ntechnique maximizes the financial cloud systems security and performance components.<\/jats:p>","DOI":"10.58346\/jisis.2025.i3.010","type":"journal-article","created":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T09:34:33Z","timestamp":1762335273000},"page":"149-159","source":"Crossref","is-referenced-by-count":0,"title":["Load Balancing in Financial Cloud with Dynamic Task  Prioritization: An Efficient Security Model Perspective"],"prefix":"10.58346","volume":"15","author":[{"given":"Dipti N.","family":"Kashyap","sequence":"first","affiliation":[]},{"given":"Dr.T.A.","family":"Madankar","sequence":"additional","affiliation":[]},{"given":"Yoghesh","family":"Dharangutti","sequence":"additional","affiliation":[]},{"given":"Dr. Sumitra","family":"Padmanabhan","sequence":"additional","affiliation":[]},{"given":"R. Hannah","family":"Jessie Rani","sequence":"additional","affiliation":[]},{"given":"Divya","family":"Paikaray","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":"2025-11-05T13:02:53Z","timestamp":1762347773000},"score":1,"resource":{"primary":{"URL":"https:\/\/jisis.org\/wp-content\/uploads\/2025\/10\/2025.I3.010.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.i3.010","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]]}}}