A Resilient Algorithm for Power System Mode Estimation using Synchrophasors. - Arezoo Rajabi; Rakesh B. Bobba (ICSS, 2016)

DANI: A Fast Diffusion Aware Network Inference Algorithm. - Maryam Ramezani 002; Hamid R. Rabiee; Maryam Tahani; Arezoo Rajabi (CoRR, 2017)

Towards Dependable Deep Convolutional Neural Networks (CNNs) with Out-distribution Learning. - Arezoo Rajabi; Mahdieh Abbasi; Christian Gagné 001; Rakesh B. Bobba (CoRR, 2018)

Controlling Over-generalization and its Effect on Adversarial Examples Generation and Detection. - Mahdieh Abbasi; Arezoo Rajabi; Azadeh Sadat Mozafari; Rakesh B. Bobba; Christian Gagné 001 (CoRR, 2018)

False Data Detection in Distributed Oscillation Mode Estimation using Hierarchical k-means. - Arezoo Rajabi; Rakesh B. Bobba (SmartGridComm, 2019)

Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks. - Mahdieh Abbasi; Arezoo Rajabi; Christian Gagné 001; Rakesh B. Bobba (Canadian AI, 2020)

Toward Metrics for Differentiating Out-of-Distribution Sets. - Mahdieh Abbasi; Changjian Shui; Arezoo Rajabi; Christian Gagné 001; Rakesh B. Bobba (ECAI, 2020)

Adversarial Profiles: Detecting Out-Distribution & Adversarial Samples in Pre-trained CNNs. - Arezoo Rajabi; Rakesh B. Bobba (CoRR, 2020)

The Trojan Detection Challenge. - 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 001; et al. (NeurIPS (Competition and Demos), 2021)

On the (Im)Practicality of Adversarial Perturbation for Image Privacy. - Arezoo Rajabi; Rakesh B. Bobba; Mike Rosulek; Charles V. Wright; Wu-chi Feng (Proc. Priv. Enhancing Technol., 2021)

Resilience Against Data Manipulation in Distributed Synchrophasor-Based Mode Estimation. - Arezoo Rajabi; Rakesh B. Bobba (IEEE Trans. Smart Grid, 2021)

Privacy-Preserving Reinforcement Learning Beyond Expectation. - Arezoo Rajabi; Bhaskar Ramasubramanian; Abdullah Al Maruf; Radha Poovendran (CDC, 2022)

Trojan Horse Training for Breaking Defenses against Backdoor Attacks in Deep Learning. - Arezoo Rajabi; Bhaskar Ramasubramanian; Radha Poovendran (CoRR, 2022)

Game of Trojans: A Submodular Byzantine Approach. - Dinuka Sahabandu; Arezoo Rajabi; Luyao Niu; Bo Li 026; Bhaskar Ramasubramanian; Radha Poovendran (CoRR, 2022)

Adversarial Images Against Super-Resolution Convolutional Neural Networks for Free. - Arezoo Rajabi; Mahdieh Abbasi; Rakesh B. Bobba; Kimia Tajik (Proc. Priv. Enhancing Technol., 2022)

LDL: A Defense for Label-Based Membership Inference Attacks. - Arezoo Rajabi; Dinuka Sahabandu; Luyao Niu; Bhaskar Ramasubramanian; Radha Poovendran (AsiaCCS, 2023)

MDTD: A Multi-Domain Trojan Detector for Deep Neural Networks. - Arezoo Rajabi; Surudhi Asokraj; Fengqing Jiang; Luyao Niu; Bhaskar Ramasubramanian; James A. Ritcey; Radha Poovendran (CCS, 2023)

FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning. - Jinyuan Jia 001; Zhuowen Yuan; Dinuka Sahabandu; Luyao Niu; Arezoo Rajabi; Bhaskar Ramasubramanian; Bo Li 026; Radha Poovendran (NeurIPS, 2023)

POSTER: Double-Dip: Thwarting Label-Only Membership Inference Attacks with Transfer Learning and Randomization. - Arezoo Rajabi; Reeya Pimple; Aiswarya Janardhanan; Surudhi Asokraj; Bhaskar Ramasubramanian; Radha Poovendran (AsiaCCS, 2024)

POSTER: Game of Trojans: Adaptive Adversaries Against Output-based Trojaned-Model Detectors. - Dinuka Sahabandu; Xiaojun Xu; Arezoo Rajabi; Luyao Niu; Bhaskar Ramasubramanian; Bo Li 026; Radha Poovendran (AsiaCCS, 2024)

Double-Dip: Thwarting Label-Only Membership Inference Attacks with Transfer Learning and Randomization. - Arezoo Rajabi; Reeya Pimple; Aiswarya Janardhanan; Surudhi Asokraj; Bhaskar Ramasubramanian; Radha Poovendran (CoRR, 2024)

Game of Trojans: Adaptive Adversaries Against Output-based Trojaned-Model Detectors. - Dinuka Sahabandu; Xiaojun Xu; Arezoo Rajabi; Luyao Niu; Bhaskar Ramasubramanian; Bo Li 026; Radha Poovendran (CoRR, 2024)