Javed, Muhammad Awais <br/><br/>
Domain Generating Algorithm (DGA) Malware Detection using Deep Learning Model / 
Muhammad Awais Javed 
 - Rawalpindi,  MCS (NUST),  2026 
 - xix, 139 p 
<br/><br/>Advanced Persistent Threats (APTs) represent one of the most captious<br/>challenges to modern cybersecurity paradigm, particularly for<br/>critical information infrastructures (CIIs), governments and military<br/>networks. These threats employ stealthy and persistent attack strategies<br/>that evade conventional defenses, with Domain Generating Algorithms<br/>(DGAs) serving as a core technique to ensure uninterrupted<br/>communication with Command and Control (C&C) servers. DGAs<br/>are capable of dynamically generating large volumes of domain names,<br/>making blacklist-based detection techniques ineffective and forcing security<br/>systems to operate reactively rather than proactively. The inherent<br/>difficulty in identifying malicious domains generated by DGAs<br/>necessitates the exploration of intelligent, adaptive detection mechanisms. 
<br/><br/><label>Subjects--Topical Terms: </label><br/>PhD Information Security Thesis
<br/><br/><label>Subjects--Geographic Terms: </label><br/>PhD IS Thesis
<br/><br/><label>Dewey Class. No.: </label>005.8,JAV