aspg-2-3976-1791417038 20261007235038 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Cybersecurity and Information Management JCIM 2769-7851 2690-6775 2026 17 1 Gagan Kumar Koduru Associate Professor, Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad, India P. Chinnasamy Associate Professor, Department of Computer Science and Engineering, School of Computing, Kalasalingam Academy of Research and Education, Srivilliputtur, India S. Kalaimagal Professor, Department of AI & DS, Panimalar Engineering College, Chennai, Tamil Nadu, India Karri Nagaraju Assistant Professor, Computer Science and Engineering, Vishnu Institute of Technology, Andhrapradesh, India V. Bhaskara Murthy Professor and HOD, Department of MCA, B V Raju College Vishnupur, Bhimavaram, Hyderabad, India Shivanadhuni Spandana Assistant Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad-500043, Telangana, India M. Rajesh Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation (DU), Tamilnadu, India Normal false false false EN-US 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"/> 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mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif;} Over uncovered and under-covered areas, satellite communication provides the potential for ubiquity, scalability, and service continuity. However, before these benefits may be fully realized, a number of obstacles need to be overcome. Satellite networks present more difficulties than terrestrial networks in terms of spectrum management, energy consumption, network control, resource management, and network security. The goal of this research is to create a novel way to remote sensing network security modelling by utilizing machine-learning techniques to analyses the security of satellite data. In order to provide an intrusion detection technique for the modern network environment, this study considers data from both terrestrial and satellite networks. Here the remote sensing network security analysis is carried out using quantum federated encryption algorithm and data security has been analysis by quantile regression adversarial convolutional neural networks. Experimental analysis has been carried out in terms of data integrity, latency, random accuracy, QoS, AUC. Proposed technique Data integrity of 93%, LATENCY of 95%, QOS of 96%, random accuracy of 98%, AUC of 92%. 2026 62 70 3976 https://creativecommons.org/licenses/by/4.0/ 10.54216/JCIM.170106 https://www.americaspg.com/journal/2/article/3976 https://www.americaspg.com/storage/21753560058.pdf