Designing Deep Learning based Network Intrusion Detection System for Software Defined Network
| dc.contributor.author | Mohammed Hamid Abdulraheem Abdullah محمد حامد عبد الرحيم عبد الله | |
| dc.contributor.author | Supervised By Assistant Professor Dr. Najla Badie Ibraheem Al-Dabagh باشراف الاستاذ المساعد الدكتورة نجلاء بديع إبراهيم الدباغ | |
| dc.date.accessioned | 2025-11-23T06:12:47Z | |
| dc.date.issued | 2020 | |
| dc.description | A Thesis Submitted to The Council of the College of Computer Sciences and Mathematics University of Mosul As a partial fulfillment of Requirements for the Degree of Doctor of Philosophy In Computer Sciences | |
| dc.identifier.uri | http://172.20.240.56:4000/handle/123456789/1634 | |
| dc.language.iso | en | |
| dc.relation.ispartofseries | 1502th | |
| dc.subject | Network Intrusion Detection System | |
| dc.subject | Software Defined Network | |
| dc.subject | Deep Learning | |
| dc.subject | Convolutional Neural Network | |
| dc.title | Designing Deep Learning based Network Intrusion Detection System for Software Defined Network | |
| dc.title.alternative | تصميم نظام كشف اختراق الشبكة المستند إلى التعلم العميق للشبكة المعرفة بالبرمجيات | |
| dc.type | Thesis |
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