Papers
1
Total Citations
3
H-Index
1
About
Atif Alvi is a computer security researcher whose work focuses on the intersection of machine learning and cybersecurity, particularly in malware detection. His most-cited paper, "Role of Logistic Regression in Malware Detection: A Systematic Literature Review" (2022), provides a comprehensive analysis of how logistic regression models can be applied to identify malicious software, addressing the growing need for robust security in an era where networks transmit sensitive data across banking, agriculture, robotics, and social platforms. With 3 citations, this work highlights his contribution to systematizing knowledge in the field, offering a foundational resource for researchers and practitioners. Alvi’s research underscores the critical role of statistical methods in combating evolving cyber threats, from the early "brain" virus to modern sophisticated malware. His systematic review approach demonstrates a commitment to bridging theoretical understanding with practical applications, making his work valuable for students and professionals seeking to leverage logistic regression for enhanced network security. Through his scholarship, Alvi advances the dialogue on how machine learning can safeguard digital infrastructures in an increasingly interconnected world.
Research Focus
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Top Papers
- 1