26 citations · 28 across the 6 of their papers we have counts for
8 papers
NOIR: Privacy-Preserving Generation of Code with Open-Source LLMs
Khoa Nguyen, Khiem Ton, NhatHai Phan +6
Although boosting software development performance, large language model (LLM)-powered code generation introduces intellectual property and data security risks rooted in the fact t…
-STEAL: LLM Stealing Attack with Local Differential Privacy
Kieu Dang, Phung Lai, NhatHai Phan +3
Large language models (LLMs) demonstrate remarkable capabilities across various tasks. However, their deployment introduces significant risks related to intellectual property. In t…
FedChip: Federated LLM for Artificial Intelligence Accelerator Chip Design
Mahmoud Nazzal, Khoa Nguyen, Deepak Vungarala +4
AI hardware design is advancing rapidly, driven by the promise of design automation to make chip development faster, more efficient, and more accessible to a wide range of users. A…
ViGText: Deepfake Image Detection with Vision-Language Model Explanations and Graph Neural Networks
Ahmad ALBarqawi, Mahmoud Nazzal, Issa Khalil +2
The rapid rise of deepfake technology, which produces realistic but fraudulent digital content, threatens the authenticity of media. Traditional deepfake detection approaches often…
SoK: Are Watermarks in LLMs Ready for Deployment?
Kieu Dang, Phung Lai, NhatHai Phan +4
Large Language Models (LLMs) have transformed natural language processing, demonstrating impressive capabilities across diverse tasks. However, deploying these models introduces cr…
Demo: SGCode: A Flexible Prompt-Optimizing System for Secure Generation of Code
Khiem Ton, Nhi Nguyen, Mahmoud Nazzal +6
This paper introduces SGCode, a flexible prompt-optimizing system to generate secure code with large language models (LLMs). SGCode integrates recent prompt-optimization approaches…
PromSec: Prompt Optimization for Secure Generation of Functional Source Code with Large Language Models (LLMs)
Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah +1
The capability of generating high-quality source code using large language models (LLMs) reduces software development time and costs. However, they often introduce security vulnera…
SA-DS: A Dataset for Large Language Model-Driven AI Accelerator Design Generation
Deepak Vungarala, Mahmoud Nazzal, Mehrdad Morsali +4
In the ever-evolving landscape of Deep Neural Networks (DNN) hardware acceleration, unlocking the true potential of systolic array accelerators has long been hindered by the daunti…