665 citations · 922 across the 15 of their papers we have counts for
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On the Necessity of Multi-Domain Explanation: An Uncertainty Principle Approach for Deep Time Series Models
Shahbaz Rezaei, Avishai Halev, Xin Liu
A prevailing approach to explain time series models is to generate attribution in time domain. A recent development in time series XAI is the concept of explanation spaces, where a…
Explanation Space: A New Perspective into Time Series Interpretability
Shahbaz Rezaei, Xin Liu
Human understandable explanation of deep learning models is essential for various critical and sensitive applications. Unlike image or tabular data where the importance of each inp…
Benchmarking Counterfactual Interpretability in Deep Learning Models for Time Series Classification
Ziwen Kan, Shahbaz Rezaei, Xin Liu
The popularity of deep learning methods in the time series domain boosts interest in interpretability studies, including counterfactual (CF) methods. CF methods identify minimal ch…
User-Level Membership Inference Attack against Metric Embedding Learning
Guoyao Li, Shahbaz Rezaei, Xin Liu
Membership inference (MI) determines if a sample was part of a victim model training set. Recent development of MI attacks focus on record-level membership inference which limits t…
An Efficient Subpopulation-based Membership Inference Attack
Shahbaz Rezaei, Xin Liu
Membership inference attacks allow a malicious entity to predict whether a sample is used during training of a victim model or not. State-of-the-art membership inference attacks ha…
Accuracy-Privacy Trade-off in Deep Ensemble: A Membership Inference Perspective
Shahbaz Rezaei, Zubair Shafiq, Xin Liu
Deep ensemble learning has been shown to improve accuracy by training multiple neural networks and averaging their outputs. Ensemble learning has also been suggested to defend agai…
On the Difficulty of Membership Inference Attacks
Shahbaz Rezaei, Xin Liu
Recent studies propose membership inference (MI) attacks on deep models, where the goal is to infer if a sample has been used in the training process. Despite their apparent succes…
Multitask Learning for Network Traffic Classification
Shahbaz Rezaei, Xin Liu
Traffic classification has various applications in today's Internet, from resource allocation, billing and QoS purposes in ISPs to firewall and malware detection in clients. Classi…
A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning
Shahbaz Rezaei, Xin Liu
Due to insufficient training data and the high computational cost to train a deep neural network from scratch, transfer learning has been extensively used in many deep-neural-netwo…