Adversarial Robustness and Deepfake Detection

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Journal Papers

• Agarwal, A.; Ratha, N. (2025). Detection of identity swapping attacks in low-resolution image settings. Journal of Information Security and Applications, 103911.
• Agarwal, A.; Vatsa, M.; Singh, R.; Ratha, N. (2024). Corruption depth: analysis of DNN depth for misclassification. Neural Networks, 106013.
• Agarwal, A.; Vatsa, M.; Singh, R.; Ratha, N. (2023). Parameter agnostic stacked wavelet transformer for detecting singularities. Information Fusion, 415-425.
• Nagpal, S.; Singh, M.; Singh, R.; Vatsa, M.; Ratha, N. (2023). In-group bias in deep learning-based face recognition models due to ethnicity and age. IEEE Transactions on Technology and Society, 54-67.
• Agarwal, A.; Ratha, N.; Vatsa, M.; Singh, R. (2022). Crafting adversarial perturbations via transformed image component swapping. IEEE Transactions on Image Processing, 7338-7349.
• Agarwal, A.; Ratha, N.; Vatsa, M.; Singh, R. (2022). Ibattack: being cautious about data labels. IEEE Transactions on Artificial Intelligence, 1484-1493.
• Agarwal, A.; Vatsa, M.; Singh, R.; Ratha, N. (2021). Damad: Database, attack, and model agnostic adversarial perturbation detector. IEEE Transactions on Neural Networks and Learning Systems, 3277-3289.
• Agarwal, A.; Ratha, N.; Vatsa, M.; Singh, R. (2020). Image transformation-based defense against adversarial perturbation on deep learning models. IEEE Transactions on Dependable and Secure Computing, 2106-2121.
• Goswami, G.; Ratha, N.; Agarwal, A.; Singh, R.; Vatsa, M. (2019). Detecting and mitigating adversarial perturbations for robust face recognition. International Journal of Computer Vision, 719-742.

Conference Papers

• Agarwal, A.; Vatsa, M.; Singh, R.; Ratha, N. (2024). Supervised Mixup: Protecting the Likely Classes for Adversarial Robustness. International Conference on Pattern Recognition, 30-45.
• Agarwal, A.; Ratha, N. (2024). Face Morphing Detection in Social Media Content. IEEE International Conference on Image Processing (ICIP), 801-806.
• Agarwal, A.; Ratha, N. (2024). Deepfake: Classifiers, fairness, and demographically robust algorithm. IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG), 9-Jan.
• Mohammadi, A.; Ratha, N. (2024). Hierarchical Multi-Branch Deepfake Detection Network (HMBDDN). IEEE Western New York Image and Signal Processing Workshop (WNYISPW), 6-Jan.
• Sharma, R.; Jawade, B.; Agarwal, A.; Setlur, S.; Ratha, N. (2023). Attention Guided Multi-attribute Architecture For Deepfake Detection. IEEE Western New York Image and Signal Processing Workshop (WNYISPW), 4-Jan.
• Agarwal, A.; Vatsa, M.; Singh, R.; Ratha, N. (2023). Robustness against gradient based attacks through cost effective network fine-tuning. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 28-37.
• Ojaswee, O.; Agarwal, A.; Ratha, N. (2023). Benchmarking Image Classifiers for Physical Out-of-Distribution Examples Detection. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 4429-4437.
• Agarwal, A.; Ratha, N.; Vatsa, M.; Singh, R. (2022). Exploring robustness connection between artificial and natural adversarial examples. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 179-186.
• Agarwal, A.; Ratha, N.; Vatsa, M.; Singh, R. (2021). Impact of super-resolution and human identification in drone surveillance. IEEE International Workshop on Information Forensics and Security (WIFS), 6-Jan.
• Agarwal, A.; Ratha, N.; Vatsa, M.; Singh, R. (2021). Intelligent and adaptive mixup technique for adversarial robustness. IEEE International Conference on Image Processing (ICIP), 824-828.
• Agarwal, A.; Vatsa, M.; Singh, R.; Ratha, N. (2020). Cognitive data augmentation for adversarial defense via pixel masking. Pattern Recognition Letters, 244-251.
• Goel, A.; Agarwal, A.; Vatsa, M.; Singh, R.; Ratha, N. (2020). DNDNet: Reconfiguring CNN for adversarial robustness. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 22-23.
• Agarwal, A.; Vatsa, M.; Singh, R.; Ratha, N. (2020). Noise is inside me! generating adversarial perturbations with noise derived from natural filters. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 774-775.