6 papers
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…
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…
A Machine Learning-Based Framework for Assessing Cryptographic Indistinguishability of Lightweight Block Ciphers
Jimmy Dani, Kalyan Nakka, Nitesh Saxena
Indistinguishability is a fundamental principle of cryptographic security, crucial for securing data transmitted between Internet of Things (IoT) devices. This principle ensures th…
Is On-Device AI Broken and Exploitable? Assessing the Trust and Ethics in Small Language Models
Kalyan Nakka, Jimmy Dani, Nitesh Saxena
In this paper, we present a very first study to investigate trust and ethical implications of on-device artificial intelligence (AI), focusing on small language models (SLMs) amena…
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…