{"id":25753,"date":"2026-09-03T12:22:33","date_gmt":"2026-09-03T12:22:33","guid":{"rendered":"https:\/\/scientificassociation.org\/?post_type=journal-paper&#038;p=25753"},"modified":"2026-09-03T12:22:33","modified_gmt":"2026-09-03T12:22:33","slug":"a-proposed-deep-learning-model-for-ransomware-detection-in-developing-countries-egypt-as-a-case-study","status":"publish","type":"journal-paper","link":"https:\/\/scientificassociation.org\/ar\/journal-paper\/a-proposed-deep-learning-model-for-ransomware-detection-in-developing-countries-egypt-as-a-case-study\/","title":{"rendered":"A proposed deep learning model for ransomware detection in developing countries: Egypt as a case study"},"content":{"rendered":"<div class=\"padding_abstract justify ltr\">Ransomware attacks have emerged as one of the most significant cybersecurity threats facing organizations today, with attacks noted highest in 2023 and continuing to grow (5). This research presents a deep learning framework leveraging Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models to detect and prevent ransomware attacks in developing countries, especially in Egypt. The proposed system combines parallel Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks\u00a0to achieve superior detection accuracy. A hybrid CNN-LSTM model addresses critical gaps in ransomware prevention for resource-constrained environments, providing a scalable solution particularly relevant for developing nations where Africa emerged as the most targeted region, with an alarming average of 2,960 weekly attacks per organization (9). The primary contribution of this paper lies in incorporating aspects of risk management, resource efficiency, and assessment of economic effects designed specifically in Egypt, where the financial sector is the second most targeted after government entities. The study&#8217;s contributions include an incremental learning approach, comprehensive dataset development, and practical deployment strategies for business organizations seeking strong ransomware defense mechanisms.<\/div>\n","protected":false},"featured_media":25700,"template":"","meta":{"_acf_changed":false},"journal-name":[220],"paper-tag":[277,233,276],"class_list":["post-25753","journal-paper","type-journal-paper","status-publish","has-post-thumbnail","hentry","journal-name-jaiep","paper-tag-april-2026","paper-tag-issue-1","paper-tag-volume-3"],"acf":[],"_links":{"self":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-paper\/25753","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-paper"}],"about":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/types\/journal-paper"}],"wp:attachment":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/media?parent=25753"}],"wp:term":[{"taxonomy":"journal-name","embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-name?post=25753"},{"taxonomy":"paper-tag","embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/paper-tag?post=25753"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}