Enhancing resilience of network intrusion detection system against adversarial attacks using hybrid approach
AsmaTariq(S23A14G05017)
Enhancing resilience of network intrusion detection system against adversarial attacks using hybrid approach - Faisalabad (unpublished) 2025 - vii,74 p. : ill. ; 30 cm. +CD
Submitted in fulfillment of the requirements for the degree of Master of Computer Science in the Faculty of Computing. Thesis supervisor: Dr. Erssa arif Includes references
Thesis (MS)--Riphah International University, 2025
English
Computer science--Data mining--Network--Cyber Attacks--Artificial intelligence--Detection system--Deep learning--Machine learning--FSSH
005 / ASM
Enhancing resilience of network intrusion detection system against adversarial attacks using hybrid approach - Faisalabad (unpublished) 2025 - vii,74 p. : ill. ; 30 cm. +CD
Submitted in fulfillment of the requirements for the degree of Master of Computer Science in the Faculty of Computing. Thesis supervisor: Dr. Erssa arif Includes references
Thesis (MS)--Riphah International University, 2025
English
Computer science--Data mining--Network--Cyber Attacks--Artificial intelligence--Detection system--Deep learning--Machine learning--FSSH
005 / ASM