aspg-2-4034-1791417083 20261007235123 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Cybersecurity and Information Management JCIM 2769-7851 2690-6775 2026 17 2 Maha Farouk Sabir Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia 16.00 Normal false false false TR X-NONE AR-SA DefSemiHidden="false" DefQFormat="false" DefPriority="99" LatentStyleCount="371"> UnhideWhenUsed="true" QFormat="true" Name="heading 2"/> UnhideWhenUsed="true" QFormat="true" Name="heading 3"/> UnhideWhenUsed="true" QFormat="true" Name="heading 4"/> UnhideWhenUsed="true" QFormat="true" Name="heading 5"/> UnhideWhenUsed="true" QFormat="true" Name="heading 6"/> UnhideWhenUsed="true" QFormat="true" Name="heading 7"/> UnhideWhenUsed="true" QFormat="true" Name="heading 8"/> UnhideWhenUsed="true" QFormat="true" Name="heading 9"/> Name="index 1"/> Name="index 2"/> Name="index 3"/> Name="index 4"/> Name="index 5"/> Name="index 6"/> Name="index 7"/> Name="index 8"/> Name="index 9"/> UnhideWhenUsed="true" Name="toc 1"/> UnhideWhenUsed="true" Name="toc 2"/> UnhideWhenUsed="true" Name="toc 3"/> UnhideWhenUsed="true" Name="toc 4"/> UnhideWhenUsed="true" Name="toc 5"/> UnhideWhenUsed="true" Name="toc 6"/> UnhideWhenUsed="true" Name="toc 7"/> UnhideWhenUsed="true" Name="toc 8"/> UnhideWhenUsed="true" Name="toc 9"/> Name="Normal Indent"/> Name="footnote text"/> Name="annotation text"/> Name="header"/> Name="footer"/> Name="index heading"/> UnhideWhenUsed="true" QFormat="true" Name="caption"/> Name="table of figures"/> Name="envelope address"/> Name="envelope return"/> Name="footnote reference"/> Name="annotation reference"/> Name="line number"/> Name="page number"/> Name="endnote reference"/> Name="endnote text"/> Name="table of authorities"/> Name="macro"/> Name="toa heading"/> Name="List"/> Name="List Bullet"/> Name="List Number"/> Name="List 2"/> Name="List 3"/> Name="List 4"/> Name="List 5"/> Name="List Bullet 2"/> Name="List Bullet 3"/> Name="List Bullet 4"/> Name="List Bullet 5"/> Name="List Number 2"/> Name="List Number 3"/> Name="List Number 4"/> Name="List Number 5"/> Name="Closing"/> Name="Signature"/> UnhideWhenUsed="true" Name="Default Paragraph Font"/> Name="Body Text"/> Name="Body Text Indent"/> Name="List Continue"/> Name="List Continue 2"/> Name="List Continue 3"/> Name="List Continue 4"/> Name="List Continue 5"/> Name="Message Header"/> Name="Salutation"/> Name="Date"/> Name="Body Text First Indent"/> Name="Body Text First Indent 2"/> Name="Note Heading"/> Name="Body Text 2"/> Name="Body Text 3"/> Name="Body Text Indent 2"/> Name="Body Text Indent 3"/> Name="Block Text"/> Name="Hyperlink"/> Name="FollowedHyperlink"/> Name="Document Map"/> Name="Plain Text"/> Name="E-mail Signature"/> Name="HTML Top of Form"/> Name="HTML Bottom of Form"/> Name="Normal (Web)"/> Name="HTML Acronym"/> Name="HTML Address"/> Name="HTML Cite"/> Name="HTML Code"/> Name="HTML Definition"/> Name="HTML Keyboard"/> Name="HTML Preformatted"/> Name="HTML Sample"/> Name="HTML Typewriter"/> Name="HTML Variable"/> Name="Normal Table"/> Name="annotation subject"/> Name="No List"/> Name="Outline List 1"/> Name="Outline List 2"/> Name="Outline List 3"/> Name="Table Simple 1"/> Name="Table Simple 2"/> Name="Table Simple 3"/> Name="Table Classic 1"/> Name="Table Classic 2"/> Name="Table Classic 3"/> Name="Table Classic 4"/> Name="Table Colorful 1"/> Name="Table Colorful 2"/> Name="Table Colorful 3"/> Name="Table Columns 1"/> Name="Table Columns 2"/> Name="Table Columns 3"/> Name="Table Columns 4"/> Name="Table Columns 5"/> Name="Table Grid 1"/> Name="Table Grid 2"/> Name="Table Grid 3"/> Name="Table Grid 4"/> Name="Table Grid 5"/> Name="Table Grid 6"/> Name="Table Grid 7"/> Name="Table Grid 8"/> Name="Table List 1"/> Name="Table List 2"/> Name="Table List 3"/> Name="Table List 4"/> Name="Table List 5"/> Name="Table List 6"/> Name="Table List 7"/> Name="Table List 8"/> Name="Table 3D effects 1"/> Name="Table 3D effects 2"/> Name="Table 3D effects 3"/> Name="Table Contemporary"/> Name="Table Elegant"/> Name="Table Professional"/> Name="Table Subtle 1"/> Name="Table Subtle 2"/> Name="Table Web 1"/> Name="Table Web 2"/> Name="Table Web 3"/> Name="Balloon Text"/> Name="Table Theme"/> Name="List Paragraph"/> Name="Intense Quote"/> Name="Subtle Emphasis"/> Name="Intense Emphasis"/> Name="Subtle Reference"/> Name="Intense Reference"/> UnhideWhenUsed="true" Name="Bibliography"/> UnhideWhenUsed="true" QFormat="true" Name="TOC Heading"/> Name="Grid Table 1 Light Accent 1"/> Name="Grid Table 6 Colorful Accent 1"/> Name="Grid Table 7 Colorful Accent 1"/> Name="Grid Table 1 Light Accent 2"/> Name="Grid Table 6 Colorful Accent 2"/> Name="Grid Table 7 Colorful Accent 2"/> Name="Grid Table 1 Light Accent 3"/> Name="Grid Table 6 Colorful Accent 3"/> Name="Grid Table 7 Colorful Accent 3"/> Name="Grid Table 1 Light Accent 4"/> Name="Grid Table 6 Colorful Accent 4"/> Name="Grid Table 7 Colorful Accent 4"/> Name="Grid Table 1 Light Accent 5"/> Name="Grid Table 6 Colorful Accent 5"/> Name="Grid Table 7 Colorful Accent 5"/> Name="Grid Table 1 Light Accent 6"/> Name="Grid Table 6 Colorful Accent 6"/> Name="Grid Table 7 Colorful Accent 6"/> Name="List Table 1 Light Accent 1"/> Name="List Table 6 Colorful Accent 1"/> Name="List Table 7 Colorful Accent 1"/> Name="List Table 1 Light Accent 2"/> Name="List Table 6 Colorful Accent 2"/> Name="List Table 7 Colorful Accent 2"/> Name="List Table 1 Light Accent 3"/> Name="List Table 6 Colorful Accent 3"/> Name="List Table 7 Colorful Accent 3"/> Name="List Table 1 Light Accent 4"/> Name="List Table 6 Colorful Accent 4"/> Name="List Table 7 Colorful Accent 4"/> Name="List Table 1 Light Accent 5"/> Name="List Table 6 Colorful Accent 5"/> Name="List Table 7 Colorful Accent 5"/> Name="List Table 1 Light Accent 6"/> Name="List Table 6 Colorful Accent 6"/> Name="List Table 7 Colorful Accent 6"/> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi; mso-ansi-language:TR;} Network security has become vulnerable to hacker threats owing to its advancement and easily accessible to computer and internet technology. Ransomware is the most commonly used malware in cyberattacks to mislead the victim user to expose private and sensitive data to hackers. Ransomware is malicious software that encodes the entire system or consumer’s files, creating it impossible, and later demands a payment fee from the victim’s computer in exchange for the decryption key. Ransomware attacks become highly popular and overwhelming for both individuals and organizations. Recently, deep learning (DL) and machine learning (ML) models are established to identify ransomware attacks in real-time and categorize them into various types. The system will be considered to examine the behaviors of malicious software and detect the particular kind of ransomware being utilized. This data will enhance the system’s accuracy and deliver appropriate data to cybersecurity professionals and victims. Therefore, this study proposes an accurate Ransomware Detection and classification using the Hybrid Metaheuristic Feature Selection with Deep Learning (RDC-HMFSDL) technique. The aim is in effectually detecting and classifying the ransomware attacks. Initially, the RDC-HMFSDL technique utilizes min-max model to transform the input data into a standard setting. Furthermore, the hybrid red deer sparrow search optimization (HRDSO) approach is used for the feature selection (FS). For ransomware attack detection, the long short-term memory autoencoder (LSTM-AE) approach is employed. Finally, the sine cosine algorithm (SCA) is used to optimally choose the parameter values of the LSTM-AE approach. The RDC-HMFSDL approach was tested on a benchmark dataset, achieving a superior accuracy of 99.88% compared to existing methods. 2026 34 47 4034 https://creativecommons.org/licenses/by/4.0/ 10.54216/JCIM.170204 https://www.americaspg.com/journal/2/article/4034 https://www.americaspg.com/storage/31756404158.pdf