Arezoo Rajabi

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 27

Top Topics

Transfer Learning

Diversity Measures

Ensemble Feature Selection

Top Venues

Proc. Priv. Enhancing Technol.

Canadian Conference on AI

Publications

Arezoo Rajabi, Reeya Pimple, Aiswarya Janardhanan, Surudhi Asokraj, Bhaskar Ramasubramanian, Radha Poovendran
Double-Dip: Thwarting Label-Only Membership Inference Attacks with Transfer Learning and Randomization. CoRR (2024)
Arezoo Rajabi, Reeya Pimple, Aiswarya Janardhanan, Surudhi Asokraj, Bhaskar Ramasubramanian, Radha Poovendran
POSTER: Double-Dip: Thwarting Label-Only Membership Inference Attacks with Transfer Learning and Randomization. AsiaCCS (2024)
Dinuka Sahabandu, Xiaojun Xu, Arezoo Rajabi, Luyao Niu, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran
POSTER: Game of Trojans: Adaptive Adversaries Against Output-based Trojaned-Model Detectors. AsiaCCS (2024)
Dinuka Sahabandu, Xiaojun Xu, Arezoo Rajabi, Luyao Niu, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran
Game of Trojans: Adaptive Adversaries Against Output-based Trojaned-Model Detectors. CoRR (2024)
Arezoo Rajabi, Surudhi Asokraj, Fengqing Jiang, Luyao Niu, Bhaskar Ramasubramanian, James A. Ritcey, Radha Poovendran
MDTD: A Multi Domain Trojan Detector for Deep Neural Networks. CoRR (2023)
Jinyuan Jia, Zhuowen Yuan, Dinuka Sahabandu, Luyao Niu, Arezoo Rajabi, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran
FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning. NeurIPS (2023)
Arezoo Rajabi, Surudhi Asokraj, Fengqing Jiang, Luyao Niu, Bhaskar Ramasubramanian, James A. Ritcey, Radha Poovendran
MDTD: A Multi-Domain Trojan Detector for Deep Neural Networks. CCS (2023)
Arezoo Rajabi, Dinuka Sahabandu, Luyao Niu, Bhaskar Ramasubramanian, Radha Poovendran
LDL: A Defense for Label-Based Membership Inference Attacks. AsiaCCS (2023)
Dinuka Sahabandu, Arezoo Rajabi, Luyao Niu, Bo Li, Bhaskar Ramasubramanian, Radha Poovendran
Game of Trojans: A Submodular Byzantine Approach. CoRR (2022)
Arezoo Rajabi, Bhaskar Ramasubramanian, Abdullah Al Maruf, Radha Poovendran
Privacy-Preserving Reinforcement Learning Beyond Expectation. CoRR (2022)
Arezoo Rajabi, Mahdieh Abbasi, Rakesh B. Bobba, Kimia Tajik
Adversarial Images Against Super-Resolution Convolutional Neural Networks for Free. Proc. Priv. Enhancing Technol. 2022 (3) (2022)
Arezoo Rajabi, Dinuka Sahabandu, Luyao Niu, Bhaskar Ramasubramanian, Radha Poovendran
LDL: A Defense for Label-Based Membership Inference Attacks. CoRR (2022)
Arezoo Rajabi, Bhaskar Ramasubramanian, Abdullah Al Maruf, Radha Poovendran
Privacy-Preserving Reinforcement Learning Beyond Expectation. CDC (2022)
Arezoo Rajabi, Bhaskar Ramasubramanian, Radha Poovendran
Trojan Horse Training for Breaking Defenses against Backdoor Attacks in Deep Learning. CoRR (2022)
Mantas Mazeika, Dan Hendrycks, Huichen Li, Xiaojun Xu, Sidney Q. Hough, Andy Zou, Arezoo Rajabi, Qi Yao, Zihao Wang, Jian Tian, Yao Tang, Di Tang, Roman Smirnov, Pavel Pleskov, Nikita Benkovich, Dawn Song, Radha Poovendran, Bo Li, David A. Forsyth
The Trojan Detection Challenge. NeurIPS (Competition and Demos) (2021)
Arezoo Rajabi, Rakesh B. Bobba
Resilience Against Data Manipulation in Distributed Synchrophasor-Based Mode Estimation. IEEE Trans. Smart Grid 12 (4) (2021)
Arezoo Rajabi, Rakesh B. Bobba, Mike Rosulek, Charles V. Wright, Wu-chi Feng
On the (Im)Practicality of Adversarial Perturbation for Image Privacy. Proc. Priv. Enhancing Technol. 2021 (1) (2021)
Mahdieh Abbasi, Changjian Shui, Arezoo Rajabi, Christian Gagné, Rakesh B. Bobba
Toward Metrics for Differentiating Out-of-Distribution Sets. ECAI (2020)
Mahdieh Abbasi, Arezoo Rajabi, Christian Gagné, Rakesh B. Bobba
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks. Canadian Conference on AI (2020)
Mahdieh Abbasi, Arezoo Rajabi, Christian Gagné, Rakesh B. Bobba
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks. CoRR (2020)
Arezoo Rajabi, Rakesh B. Bobba
Adversarial Profiles: Detecting Out-Distribution & Adversarial Samples in Pre-trained CNNs. CoRR (2020)
Mahdieh Abbasi, Changjian Shui, Arezoo Rajabi, Christian Gagné, Rakesh Bobba
Toward Metrics for Differentiating Out-of-Distribution Sets. CoRR (2019)
Arezoo Rajabi, Rakesh B. Bobba
False Data Detection in Distributed Oscillation Mode Estimation using Hierarchical k-means. SmartGridComm (2019)
Arezoo Rajabi, Mahdieh Abbasi, Christian Gagné, Rakesh B. Bobba
Towards Dependable Deep Convolutional Neural Networks (CNNs) with Out-distribution Learning. CoRR (2018)
Mahdieh Abbasi, Arezoo Rajabi, Azadeh Sadat Mozafari, Rakesh B. Bobba, Christian Gagné
Controlling Over-generalization and its Effect on Adversarial Examples Generation and Detection. CoRR (2018)
Maryam Ramezani, Hamid R. Rabiee, Maryam Tahani, Arezoo Rajabi
DANI: A Fast Diffusion Aware Network Inference Algorithm. CoRR (2017)
Arezoo Rajabi, Rakesh B. Bobba
A Resilient Algorithm for Power System Mode Estimation using Synchrophasors. ICSS (2016)