Papers
1
Total Citations
3
H-Index
1
About
Dr. Uzma Omer is a prominent researcher in cybersecurity and machine learning, with a focused expertise in malware detection and network security. Her most-cited work, "Role of Logistic Regression in Malware Detection: A Systematic Literature Review" (2022, 3 citations), systematically examines how logistic regression models can be leveraged to identify malicious software, addressing the critical need for robust security in an era where networks transmit sensitive data across banking, agriculture, robotics, and virtual social platforms. This contribution highlights her ability to bridge theoretical machine learning techniques with practical cybersecurity challenges, offering a structured framework for researchers and practitioners. Dr. Omer’s research underscores the evolution from early computer viruses like the Brain virus to modern, sophisticated threats, emphasizing the growing importance of adaptive detection methods. Her work has been instrumental in guiding systematic approaches to malware analysis, making her a valuable voice in the field. With a career dedicated to advancing secure digital ecosystems, Dr. Omer continues to influence both academic inquiry and real-world security solutions, inspiring students and researchers to explore the intersection of AI and cyber defense.
Research Focus
Key Achievements
Top Papers
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