201 citations · 215 across the 5 of their papers we have counts for
8 papers
5uGUE: Agentic Hardware-in-the-Loop Fuzzing for 5G Devices and beyond
Guoqiang Hua, Sakshi Udeshi, Matheus Eduardo Garbelini +2
In this paper, we present 5uGUE, a large language model (LLM)-driven hardware-in-the-loop agent, which enables the wireless fuzzing of 5G-enabled devices (such as mobile phones). 5…
AequeVox: Automated Fairness Testing of Speech Recognition Systems
Sai Sathiesh Rajan, Sakshi Udeshi, Sudipta Chattopadhyay
Automatic Speech Recognition (ASR) systems have become ubiquitous. They can be found in a variety of form factors and are increasingly important in our daily lives. As such, ensuri…
Astraea: Grammar-based Fairness Testing
Ezekiel Soremekun, Sakshi Udeshi, Sudipta Chattopadhyay
Software often produces biased outputs. In particular, machine learning (ML) based software are known to produce erroneous predictions when processing discriminatory inputs. Such u…
Towards Backdoor Attacks and Defense in Robust Machine Learning Models
Ezekiel Soremekun, Sakshi Udeshi, Sudipta Chattopadhyay
The introduction of robust optimisation has pushed the state-of-the-art in defending against adversarial attacks. Notably, the state-of-the-art projected gradient descent (PGD)-bas…
Callisto: Entropy based test generation and data quality assessment for Machine Learning Systems
Sakshi Udeshi, Xingbin Jiang, Sudipta Chattopadhyay
Machine Learning (ML) has seen massive progress in the last decade and as a result, there is a pressing need for validating ML-based systems. To this end, we propose, design and ev…
Model Agnostic Defence against Backdoor Attacks in Machine Learning
Sakshi Udeshi, Shanshan Peng, Gerald Woo +3
Machine Learning (ML) has automated a multitude of our day-to-day decision making domains such as education, employment and driving automation. The continued success of ML largely…
Grammar Based Directed Testing of Machine Learning Systems
Sakshi Udeshi, Sudipta Chattopadhyay
The massive progress of machine learning has seen its application over a variety of domains in the past decade. But how do we develop a systematic, scalable and modular strategy to…
Automated Directed Fairness Testing
Sakshi Udeshi, Pryanshu Arora, Sudipta Chattopadhyay
Fairness is a critical trait in decision making. As machine-learning models are increasingly being used in sensitive application domains (e.g. education and employment) for decisio…