7 citations · 9 across the 9 of their papers we have counts for
9 papers
Infrastructure Patterns in Toll Scam Domains: A Comprehensive Analysis of Cybercriminal Registration and Hosting Strategies
Morium Akter Munny, Mahbub Alam, Sonjoy Kumar Paul +3
Toll scams involve criminals registering fake domains that pretend to be legitimate transportation agencies to trick users into making fraudulent payments. Although these scams are…
BitBypass: A New Direction in Jailbreaking Aligned Large Language Models with Bitstream Camouflage
Kalyan Nakka, Nitesh Saxena
The inherent risk of generating harmful and unsafe content by Large Language Models (LLMs), has highlighted the need for their safety alignment. Various techniques like supervised…
Robust and Verifiable MPC with Applications to Linear Machine Learning Inference
Tzu-Shen Wang, Jimmy Dani, Juan Garay +2
In this work, we present an efficient secure multi-party computation MPC protocol that provides strong security guarantees in settings with dishonest majority of participants who m…
LiteLMGuard: Seamless and Lightweight On-Device Prompt Filtering for Safeguarding Small Language Models against Quantization-induced Risks and Vulnerabilities
Kalyan Nakka, Jimmy Dani, Ausmit Mondal +1
The growing adoption of Large Language Models (LLMs) has influenced the development of Small Language Models (SLMs) for on-device deployment across smartphones and edge devices, of…
The First Early Evidence of the Use of Browser Fingerprinting for Online Tracking
Zengrui Liu, Jimmy Dani, Yinzhi Cao +2
While advertising has become commonplace in today's online interactions, there is a notable dearth of research investigating the extent to which browser fingerprinting is harnessed…
When AI Defeats Password Deception! A Deep Learning Framework to Distinguish Passwords and Honeywords
Jimmy Dani, Brandon McCulloh, Nitesh Saxena
"Honeywords" have emerged as a promising defense mechanism for detecting data breaches and foiling offline dictionary attacks (ODA) by deceiving attackers with false passwords. In…