Sourjya Naskar
Papers
1
Total Citations
12
H-Index
1
About
Sourjya Naskar is a researcher at the forefront of cybersecurity for cyber-physical systems (CPS), with a primary focus on developing robust, data-driven attack detection mechanisms. His most cited work, "Attack Detection Using Unsupervised Learning Algorithms in Cyber-Physical Systems" (2021), has garnered 12 citations, establishing a foundation for anomaly detection in critical infrastructure without relying on labeled attack data. This contribution is particularly significant in domains like smart grids and industrial control systems, where real-time, adaptive security is paramount. Naskar's research bridges the gap between machine learning and CPS security, offering scalable solutions that can identify novel threats. His work demonstrates a commitment to advancing resilient and autonomous defense systems, making him a notable voice in the growing field of AI-driven cybersecurity.
Research Focus
Key Achievements
Top Papers
- 1