no code implementations • 24 Jul 2023 • Yi Han, Matthew Chan, Eric Wengrowski, Zhuohuan Li, Nils Ole Tippenhauer, Mani Srivastava, Saman Zonouz, Luis Garcia
We demonstrate that the dynamic nature of EvilEye enables attackers to adapt adversarial examples across a variety of objects with a significantly higher ASR compared to state-of-the-art physical world attack frameworks.
no code implementations • 4 Dec 2022 • Huy Phan, Miao Yin, Yang Sui, Bo Yuan, Saman Zonouz
Considering the co-importance of model compactness and robustness in practical applications, several prior works have explored to improve the adversarial robustness of the sparse neural networks.
no code implementations • 24 Aug 2022 • Xiao Zang, Miao Yin, Lingyi Huang, Jingjin Yu, Saman Zonouz, Bo Yuan
Despite the current development in this direction, the efficient capture and processing of important sequential and spatial information, in a direct and simultaneous way, is still relatively under-explored.
1 code implementation • NeurIPS 2021 • Yang Sui, Miao Yin, Yi Xie, Huy Phan, Saman Zonouz, Bo Yuan
Filter pruning has been widely used for neural network compression because of its enabled practical acceleration.
no code implementations • 18 Jan 2021 • Abhijeet Sahu, Zeyu Mao, Patrick Wlazlo, Hao Huang, Katherine Davis, Ana Goulart, Saman Zonouz
We perform multi-source data fusion for training IDS in a cyber-physical power system testbed where we collect cyber and physical side data from multiple sensors emulating real-world data sources that would be found in a utility and synthesizes these into features for algorithms to detect intrusions.
no code implementations • 3 Apr 2020 • Vidyasagar Sadhu, Saman Zonouz, Dario Pompili
With the increase in use of Unmanned Aerial Vehicles (UAVs)/drones, it is important to detect and identify causes of failure in real time for proper recovery from a potential crash-like scenario or post incident forensics analysis.
no code implementations • 29 Apr 2019 • Vidyasagar Sadhu, Gabriel Salles-Loustau, Dario Pompili, Saman Zonouz, Vincent Sritapan
The agents are involved in capturing the images of the scene using their smartphones (or on-board cameras in case of drones) as directed by the MARL algorithm.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 21 Apr 2019 • Vidyasagar Sadhu, Saman Zonouz, Vincent Sritapan, Dario Pompili
Furthermore, since privacy is a concern in collaborative filtering, a privacy-preserving method is proposed to derive HCFContext model parameters based on the concepts of homomorphic encryption.
no code implementations • 29 Sep 2017 • Vidyasagar Sadhu, Dario Pompili, Saman Zonouz, Vincent Sritapan
Mobile phones provide an excellent opportunity for building context-aware applications.