Sushil Gupta
Papers
1
Total Citations
2
H-Index
1
About
Sushil Gupta is a cybersecurity researcher whose work focuses on the detection and mitigation of malicious automated threats in online social networks. His primary research areas include social bot detection, learning automata, and cyber threat intelligence on platforms like Twitter. Gupta’s most notable contribution is his pioneering application of learning automata—a reinforcement learning technique—to identify violent social bots that automate interactions, create fictitious profiles, and spread destructive propaganda. His 2022 paper on this topic, which has garnered early citations, addresses a critical gap in detecting bots that disseminate malicious root URLs and reroute requests from social media agents. This work is particularly impactful for countering disinformation campaigns and protecting digital ecosystems from automated abuse. Gupta’s research offers a novel, adaptive approach to bot detection that evolves with emerging threats, making it a valuable resource for students and researchers in cybersecurity, machine learning, and social network analysis. His contributions are especially relevant in an era where social media manipulation poses significant risks to public discourse and information integrity.
Research Focus
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Top Papers
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