13 citations · 15 across the 9 of their papers we have counts for
6 papers · 1 filter
LoRA-based Parameter-Efficient LLMs for Continuous Learning in Edge-based Malware Detection
Christian Rondanini, Barbara Carminati, Elena Ferrari +2
The proliferation of edge devices has created an urgent need for security solutions capable of detecting malware in real time while operating under strict computational and memory…
SWaRL: Safeguard Code Watermarking via Reinforcement Learning
Neusha Javidnia, Ruisi Zhang, Ashish Kundu +1
We present SWaRL, a robust and fidelity-preserving watermarking framework designed to protect the intellectual property of code LLMs by embedding unique and verifiable signatures i…
Advancing Honeywords for Real-World Authentication Security
Sudiksha Das, Ashish Kundu
Introduced by Juels and Rivest in 2013, Honeywords, which are decoy passwords stored alongside a real password, appear to be a proactive method to help detect password credentials…
How Good LLM-Generated Password Policies Are?
Vivek Vaidya, Aditya Patwardhan, Ashish Kundu
Generative AI technologies, particularly Large Language Models (LLMs), are rapidly being adopted across industry, academia, and government sectors, owing to their remarkable capabi…
VulBinLLM: LLM-powered Vulnerability Detection for Stripped Binaries
Nasir Hussain, Haohan Chen, Chanh Tran +6
Recognizing vulnerabilities in stripped binary files presents a significant challenge in software security. Although some progress has been made in generating human-readable inform…
Evaluating Synthetic Command Attacks on Smart Voice Assistants
Zhengxian He, Ashish Kundu, Mustaque Ahamad
Recent advances in voice synthesis, coupled with the ease with which speech can be harvested for millions of people, introduce new threats to applications that are enabled by devic…