| Parametric noise injection: Trainable randomness to improve deep neural network robustness against adversarial attack AS Rakin, Z He, D Fan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 324 | 2019 |
| Bit-flip attack: Crushing neural network with progressive bit search AS Rakin, Z He, D Fan Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 242 | 2019 |
| Tbt: Targeted neural network attack with bit trojan AS Rakin, Z He, D Fan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 235 | 2020 |
| {DeepHammer}: Depleting the intelligence of deep neural networks through targeted chain of bit flips F Yao, AS Rakin, D Fan 29th USENIX Security Symposium (USENIX Security 20), 1463-1480, 2020 | 163 | 2020 |
| Cmp-pim: an energy-efficient comparator-based processing-in-memory neural network accelerator S Angizi, Z He, AS Rakin, D Fan Proceedings of the 55th Annual Design Automation Conference, 1-6, 2018 | 125 | 2018 |
| Deepsteal: Advanced model extractions leveraging efficient weight stealing in memories AS Rakin, MHI Chowdhuryy, F Yao, D Fan 2022 IEEE symposium on security and privacy (SP), 1157-1174, 2022 | 95 | 2022 |
| Defending and harnessing the bit-flip based adversarial weight attack AS Rakin, Z He, J Li, C Chakrabarti, D Fan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 91 | 2020 |
| T-BFA: Targeted Bit-Flip Adversarial Weight Attack AS Rakin, Z He, J Li, F Yao, C Chakrabarti, D Fan IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 7928 …, 2021 | 84 | 2021 |
| Defending bit-flip attack through dnn weight reconstruction J Li, AS Rakin, Y Xiong, L Chang, Z He, D Fan, C Chakrabarti 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 65 | 2020 |
| Defend deep neural networks against adversarial examples via fixed and dynamic quantized activation functions AS Rakin, J Yi, B Gong, D Fan arXiv preprint arXiv:1807.06714, 2018 | 61 | 2018 |
| {Deep-Dup}: An adversarial weight duplication attack framework to crush deep neural network in {Multi-Tenant}{FPGA} AS Rakin, Y Luo, X Xu, D Fan 30th USENIX Security Symposium (USENIX Security 21), 1919-1936, 2021 | 51 | 2021 |
| Low loss and flat dispersion Kagome photonic crystal fiber in the terahertz regime S Rana, AS Rakin, MR Hasan, MS Reza, R Leonhardt, D Abbott, ... Optics Communications 410, 452-456, 2018 | 51 | 2018 |
| Ressfl: A resistance transfer framework for defending model inversion attack in split federated learning J Li, AS Rakin, X Chen, Z He, D Fan, C Chakrabarti Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 46 | 2022 |
| Radar: Run-time adversarial weight attack detection and accuracy recovery J Li, AS Rakin, Z He, D Fan, C Chakrabarti 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), 790-795, 2021 | 46 | 2021 |
| Low loss and low dispersion fiber for transmission applications in the terahertz regime S Rana, AS Rakin, H Subbaraman, R Leonhardt, D Abbott IEEE Photonics Technology Letters 29 (10), 830-833, 2017 | 37 | 2017 |
| Pim-tgan: A processing-in-memory accelerator for ternary generative adversarial networks AS Rakin, S Angizi, Z He, D Fan 2018 IEEE 36th International Conference on Computer Design (ICCD), 266-273, 2018 | 33 | 2018 |
| RA-BNN: Constructing Robust & Accurate Binary Neural Network to Simultaneously Defend Adversarial Bit-Flip Attack and Improve Accuracy A Siraj Rakin, L Yang, J Li, F Yao, C Chakrabarti, Y Cao, J Seo, D Fan arXiv e-prints, arXiv: 2103.13813, 2021 | 26* | 2021 |
| Robust sparse regularization: Defending adversarial attacks via regularized sparse network AS Rakin, Z He, L Yang, Y Wang, L Wang, D Fan Proceedings of the 2020 on Great Lakes Symposium on VLSI, 125-130, 2020 | 26* | 2020 |
| Neurobfuscator: A full-stack obfuscation tool to mitigate neural architecture stealing J Li, Z He, AS Rakin, D Fan, C Chakrabarti 2021 IEEE International Symposium on Hardware Oriented Security and Trust …, 2021 | 25 | 2021 |
| Rep-net: Efficient on-device learning via feature reprogramming L Yang, AS Rakin, D Fan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 24 | 2022 |
Deliang FanAssociate Professor, School of Electrical Computer and Energy Engineering, Arizona State UniversityVerified email at asu.edu
