46 citations · 133 across the 34 of their papers we have counts for
10 papers · 1 filter
Attention Deficit is Ordered! Fooling Deformable Vision Transformers with Collaborative Adversarial Patches
Quazi Mishkatul Alam, Bilel Tarchoun, Ihsen Alouani +1
The latest generation of transformer-based vision models has proven to be superior to Convolutional Neural Network (CNN)-based models across several vision tasks, largely attribute…
May the Noise be with you: Adversarial Training without Adversarial Examples
Ayoub Arous, Andres F Lopez-Lopera, Nael Abu-Ghazaleh +1
In this paper, we investigate the following question: Can we obtain adversarially-trained models without training on adversarial examples? Our intuition is that training a model wi…
Fool the Hydra: Adversarial Attacks against Multi-view Object Detection Systems
Bilel Tarchoun, Quazi Mishkatul Alam, Nael Abu-Ghazaleh +1
Adversarial patches exemplify the tangible manifestation of the threat posed by adversarial attacks on Machine Learning (ML) models in real-world scenarios. Robustness against thes…
Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks
Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu +3
Large Language Models (LLMs) are swiftly advancing in architecture and capability, and as they integrate more deeply into complex systems, the urgency to scrutinize their security…
Graph Analytics on Evolving Data (Abstract)
Mahbod Afarin, Chao Gao, Shafiur Rahman +2
We consider the problem of graph analytics on evolving graphs. In this scenario, a query typically needs to be applied to different snapshots of the graph over an extended time win…
That Doesn't Go There: Attacks on Shared State in Multi-User Augmented Reality Applications
Carter Slocum, Yicheng Zhang, Erfan Shayegani +3
Augmented Reality (AR) is expected to become a pervasive component in enabling shared virtual experiences. In order to facilitate collaboration among multiple users, it is crucial…
Learn to Compress (LtC): Efficient Learning-based Streaming Video Analytics
Quazi Mishkatul Alam, Israat Haque, Nael Abu-Ghazaleh
Video analytics are often performed as cloud services in edge settings, mainly to offload computation, and also in situations where the results are not directly consumed at the vid…
Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models
Erfan Shayegani, Yue Dong, Nael Abu-Ghazaleh
We introduce new jailbreak attacks on vision language models (VLMs), which use aligned LLMs and are resilient to text-only jailbreak attacks. Specifically, we develop cross-modalit…
Co(ve)rtex: ML Models as storage channels and their (mis-)applications
Md Abdullah Al Mamun, Quazi Mishkatul Alam, Erfan Shayegani +3
Machine learning (ML) models are overparameterized to support generality and avoid overfitting. The state of these parameters is essentially a "don't-care" with respect to the prim…
Jedi: Entropy-based Localization and Removal of Adversarial Patches
Bilel Tarchoun, Anouar Ben Khalifa, Mohamed Ali Mahjoub +2
Real-world adversarial physical patches were shown to be successful in compromising state-of-the-art models in a variety of computer vision applications. Existing defenses that are…