Adnan Siraj Rakin
Orcid: 0000-0002-6056-2625
According to our database1,
Adnan Siraj Rakin
authored at least 41 papers
between 2018 and 2024.
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Bibliography
2024
CoRR, 2024
DeepShuffle: A Lightweight Defense Framework against Adversarial Fault Injection Attacks on Deep Neural Networks in Multi-Tenant Cloud-FPGA.
Proceedings of the IEEE Symposium on Security and Privacy, 2024
DRAM-Locker: A General-Purpose DRAM Protection Mechanism Against Adversarial DNN Weight Attacks.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024
DNN-Defender: A Victim-Focused In-DRAM Defense Mechanism for Taming Adversarial Weight Attack on DNNs.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024
Deep-TROJ: An Inference Stage Trojan Insertion Algorithm Through Efficient Weight Replacement Attack.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Threshold Breaker: Can Counter-Based RowHammer Prevention Mechanisms Truly Safeguard DRAM?
CoRR, 2023
DNN-Defender: An in-DRAM Deep Neural Network Defense Mechanism for Adversarial Weight Attack.
CoRR, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
2022
IEEE Trans. Pattern Anal. Mach. Intell., 2022
IEEE Des. Test, 2022
DeepSteal: Advanced Model Extractions Leveraging Efficient Weight Stealing in Memories.
Proceedings of the 43rd IEEE Symposium on Security and Privacy, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
DA<sup>3</sup>: Dynamic Additive Attention Adaption for Memory-Efficient On-Device Multi-Domain Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022
ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
RA-BNN: Constructing Robust & Accurate Binary Neural Network to Simultaneously Defend Adversarial Bit-Flip Attack and Improve Accuracy.
CoRR, 2021
Deep-Dup: An Adversarial Weight Duplication Attack Framework to Crush Deep Neural Network in Multi-Tenant FPGA.
Proceedings of the 30th USENIX Security Symposium, 2021
Proceedings of the IEEE Information Theory Workshop, 2021
Proceedings of the IEEE International Symposium on Information Theory, 2021
NeurObfuscator: A Full-stack Obfuscation Tool to Mitigate Neural Architecture Stealing.
Proceedings of the IEEE International Symposium on Hardware Oriented Security and Trust, 2021
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021
Leveraging Noise and Aggressive Quantization of In-Memory Computing for Robust DNN Hardware Against Adversarial Input and Weight Attacks.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021
2020
Sparse BD-Net: A Multiplication-less DNN with Sparse Binarized Depth-wise Separable Convolution.
ACM J. Emerg. Technol. Comput. Syst., 2020
CoRR, 2020
DeepHammer: Depleting the Intelligence of Deep Neural Networks through Targeted Chain of Bit Flips.
Proceedings of the 29th USENIX Security Symposium, 2020
Robust Sparse Regularization: Defending Adversarial Attacks Via Regularized Sparse Network.
Proceedings of the GLSVLSI '20: Great Lakes Symposium on VLSI 2020, 2020
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
2019
Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness.
CoRR, 2019
Defense-Net: Defend Against a Wide Range of Adversarial Attacks through Adversarial Detector.
Proceedings of the 2019 IEEE Computer Society Annual Symposium on VLSI, 2019
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness Against Adversarial Attack.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019
2018
Defend Deep Neural Networks Against Adversarial Examples via Fixed andDynamic Quantized Activation Functions.
CoRR, 2018
CoRR, 2018
Proceedings of the 2018 IEEE Computer Society Annual Symposium on VLSI, 2018
PIM-TGAN: A Processing-in-Memory Accelerator for Ternary Generative Adversarial Networks.
Proceedings of the 36th IEEE International Conference on Computer Design, 2018
CMP-PIM: an energy-efficient comparator-based processing-in-memory neural network accelerator.
Proceedings of the 55th Annual Design Automation Conference, 2018