46 citations · 64 across the 3 of their papers we have counts for
3 papers
cs.CL2023★ 1 cited
Making Large Language Models Better Data Creators
Dong-Ho Lee, Jay Pujara, Mohit Sewak +2
Although large language models (LLMs) have advanced the state-of-the-art in NLP significantly, deploying them for downstream applications is still challenging due to cost, responsi…
cs.CR2022★ 46 cited
Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Review
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
The cybersecurity threat landscape has lately become overly complex. Threat actors leverage weaknesses in the network and endpoint security in a very coordinated manner to perpetua…
cs.CR2020★ 17 cited
DOOM: A Novel Adversarial-DRL-Based Op-Code Level Metamorphic Malware Obfuscator for the Enhancement of IDS
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
We designed and developed DOOM (Adversarial-DRL based Opcode level Obfuscator to generate Metamorphic malware), a novel system that uses adversarial deep reinforcement learning to…