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ORCIDFarinaz Koushanfar
Person information
- affiliation: University of California, San Diego, USA
- affiliation (former): University of California, Berkeley, USA
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2020 – today
- 2024
[j72]Huili Chen
, Cheng Fu, Bita Darvish Rouhani, Jishen Zhao, Farinaz Koushanfar:
Intellectual Property Protection of Deep-Learning Systems via Hardware/Software Co-Design. IEEE Des. Test 41(2): 23-31 (2024)- [j71]Nasimeh Heydaribeni, Xinrui Zhan, Ruisi Zhang, Tina Eliassi-Rad, Farinaz Koushanfar:
Distributed constrained combinatorial optimization leveraging hypergraph neural networks. Nat. Mac. Intell. 6(6): 664-672 (2024) - [j70]Xinqiao Zhang, Mohammad Samragh, Siam U. Hussain, Ke Huang, Farinaz Koushanfar:
Scalable Binary Neural Network Applications in Oblivious Inference. ACM Trans. Embed. Comput. Syst. 23(3): 45:1-45:18 (2024) - [j69]Nojan Sheybani, Xinqiao Zhang, Siam Umar Hussain, Farinaz Koushanfar:
SenseHash: Computing on Sensor Values Mystified at the Origin. IEEE Trans. Emerg. Top. Comput. 12(2): 508-520 (2024) - [j68]Jeongmin Lim, Young Geun Kim, Sung Woo Chung, Farinaz Koushanfar, Joonho Kong:
Near-Memory Computing With Compressed Embedding Table for Personalized Recommendation. IEEE Trans. Emerg. Top. Comput. 12(3): 938-951 (2024) - [j67]Paarth Neekhara, Shehzeen Hussain, Xinqiao Zhang, Ke Huang, Julian J. McAuley, Farinaz Koushanfar:
FaceSigns: Semi-fragile Watermarks for Media Authentication. ACM Trans. Multim. Comput. Commun. Appl. 20(11): 337:1-337:21 (2024) - [j66]Olivia Weng, Gabriel Marcano, Vladimir Loncar, Alireza Khodamoradi, G. Abarajithan, Nojan Sheybani, Andres Meza, Farinaz Koushanfar, Kristof Denolf, Javier Mauricio Duarte, Ryan Kastner:
Tailor: Altering Skip Connections for Resource-Efficient Inference. ACM Trans. Reconfigurable Technol. Syst. 17(1): 11:1-11:23 (2024) - [c177]Nojan Sheybani, Farinaz Koushanfar:
You Can Have Your Cake and Eat It Too: Ensuring Practical Robustness and Privacy in Federated Learning. AAAI Spring Symposia 2024: 316 - [c176]Ruisi Zhang, Farinaz Koushanfar:
EmMark: Robust Watermarks for IP Protection of Embedded Quantized Large Language Models. DAC 2024: 88:1-88:6 - [c175]Mingjia Huo, Sai Ashish Somayajula, Youwei Liang, Ruisi Zhang, Farinaz Koushanfar, Pengtao Xie:
Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models. ICML 2024 - [c174]Paarth Neekhara, Shehzeen Samarah Hussain, Rafael Valle, Boris Ginsburg, Rishabh Ranjan, Shlomo Dubnov, Farinaz Koushanfar, Julian J. McAuley:
SelfVC: Voice Conversion With Iterative Refinement using Self Transformations. ICML 2024 - [c173]Ruisi Zhang, Rachel Selina Rajarathnam, David Z. Pan, Farinaz Koushanfar:
Automated Physical Design Watermarking Leveraging Graph Neural Networks. MLCAD 2024: 13:1-13:10 - [c172]Ke Huang, Xinqiao Zhang, Farinaz Koushanfar:
Unveiling Analog Aging Trojans (ATs): Vulnerabilities and Detection Strategies. MWSCAS 2024: 678-682 - [c171]Ruisi Zhang, Shehzeen Samarah Hussain, Paarth Neekhara, Farinaz Koushanfar:
REMARK-LLM: A Robust and Efficient Watermarking Framework for Generative Large Language Models. USENIX Security Symposium 2024 - [e1]Yongdae Kim, Jong Kim, Farinaz Koushanfar, Kasper Rasmussen:
Proceedings of the 17th ACM Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2024, Seoul, Republic of Korea, May 27-29, 2024. ACM 2024 [contents] - [i91]Ruisi Zhang, Farinaz Koushanfar:
EmMark: Robust Watermarks for IP Protection of Embedded Quantized Large Language Models. CoRR abs/2402.17938 (2024) - [i90]Mingjia Huo, Sai Ashish Somayajula, Youwei Liang, Ruisi Zhang, Farinaz Koushanfar, Pengtao Xie:
Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models. CoRR abs/2402.18059 (2024) - [i89]Ruisi Zhang, Rachel Selina Rajarathnam, David Z. Pan, Farinaz Koushanfar:
ICMarks: A Robust Watermarking Framework for Integrated Circuit Physical Design IP Protection. CoRR abs/2404.18407 (2024) - [i88]Ruisi Zhang, Rachel Selina Rajarathnam, David Z. Pan, Farinaz Koushanfar:
Automated Physical Design Watermarking Leveraging Graph Neural Networks. CoRR abs/2407.20544 (2024) - [i87]Ruisi Zhang, Farinaz Koushanfar:
Watermarking Large Language Models and the Generated Content: Opportunities and Challenges. CoRR abs/2410.19096 (2024) - [i86]Ari Juels, Farinaz Koushanfar:
Props for Machine-Learning Security. CoRR abs/2410.20522 (2024) - [i85]Seetal Potluri, Farinaz Koushanfar:
SoK: Model Reverse Engineering Threats for Neural Network Hardware. IACR Cryptol. ePrint Arch. 2024: 913 (2024) - 2023
- [j65]Huili Chen, Cheng Fu, Jishen Zhao, Farinaz Koushanfar:
GALU: A Genetic Algorithm Framework for Logic Unlocking. DTRAP 4(2): 21:1-21:30 (2023) - [j64]Mojan Javaheripi, Jung-Woo Chang, Farinaz Koushanfar:
AccHashtag: Accelerated Hashing for Detecting Fault-Injection Attacks on Embedded Neural Networks. ACM J. Emerg. Technol. Comput. Syst. 19(1): 7:1-7:20 (2023) - [j63]Loris Giulivi, Malhar Jere, Loris Rossi, Farinaz Koushanfar, Gabriela F. Ciocarlie, Briland Hitaj, Giacomo Boracchi:
Adversarial scratches: Deployable attacks to CNN classifiers. Pattern Recognit. 133: 108985 (2023) - [j62]Huili Chen, Xinqiao Zhang, Ke Huang, Farinaz Koushanfar:
AdaTest: Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection. ACM Trans. Embed. Comput. Syst. 22(2): 37:1-37:23 (2023) - [j61]Huili Chen, Farinaz Koushanfar:
Tutorial: Toward Robust Deep Learning against Poisoning Attacks. ACM Trans. Embed. Comput. Syst. 22(3): 42:1-42:15 (2023) - [j60]Florian Frank, Wenjie Xiong, Nikolaos Athanasios Anagnostopoulos, André Schaller, Tolga Arul, Farinaz Koushanfar, Stefan Katzenbeisser, Ulrich Rührmair, Jakub Szefer:
Abusing Commodity DRAMs in IoT Devices to Remotely Spy on Temperature. IEEE Trans. Inf. Forensics Secur. 18: 2991-3005 (2023) - [j59]Ruisi Zhang, Shehzeen Hussain, Huili Chen, Mojan Javaheripi, Farinaz Koushanfar:
Systemization of Knowledge: Robust Deep Learning using Hardware-software co-design in Centralized and Federated Settings. ACM Trans. Design Autom. Electr. Syst. 28(6): 88:1-88:32 (2023) - [c170]Xinghan Wang, Nasimeh Heydaribeni, Farinaz Koushanfar, Tara Javidi:
Federated Certainty Equivalence Control for Linear Gaussian Systems with Unknown Decoupled Dynamics and Quadratic Common Cost. Allerton 2023: 1-8 - [c169]Kushal Babel, Mojan Javaheripi, Yan Ji, Mahimna Kelkar, Farinaz Koushanfar, Ari Juels:
Lanturn: Measuring Economic Security of Smart Contracts Through Adaptive Learning. CCS 2023: 1212-1226 - [c168]Shashank Balla, Farinaz Koushanfar:
HELiKs: HE Linear Algebra Kernels for Secure Inference. CCS 2023: 2306-2320 - [c167]Jung-Woo Chang, Mojan Javaheripi, Farinaz Koushanfar:
VideoFlip: Adversarial Bit Flips for Reducing Video Service Quality. DAC 2023: 1-6 - [c166]Nojan Sheybani, Zahra Ghodsi, Ritvik Kapila, Farinaz Koushanfar:
ZKROWNN: Zero Knowledge Right of Ownership for Neural Networks. DAC 2023: 1-6 - [c165]Ruisi Zhang, Mojan Javaheripi, Zahra Ghodsi, Amit Bleiweiss, Farinaz Koushanfar:
AdaGL: Adaptive Learning for Agile Distributed Training of Gigantic GNNs. DAC 2023: 1-6 - [c164]Shehzeen Hussain, Todd Huster, Chris Mesterharm, Paarth Neekhara, Farinaz Koushanfar:
ReFace: Adversarial Transformation Networks for Real-time Attacks on Face Recognition Systems. DSN 2023: 302-312 - [c163]Olivia Weng, Gabriel Marcano, Vladimir Loncar, Alireza Khodamoradi, Nojan Sheybani, Farinaz Koushanfar, Kristof Denolf, Javier Mauricio Duarte, Ryan Kastner:
Adapting Skip Connections for Resource-Efficient FPGA Inference. FPGA 2023: 229 - [c162]Zahra Ghodsi, Mojan Javaheripi, Nojan Sheybani, Xinqiao Zhang, Ke Huang, Farinaz Koushanfar:
zPROBE: Zero Peek Robustness Checks for Federated Learning. ICCV 2023: 4837-4847 - [c161]Jung-Woo Chang, Mojan Javaheripi, Seira Hidano, Farinaz Koushanfar:
RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on Deep Learning-based Video Compression. NDSS 2023 - [c160]Christoph Sendner, Huili Chen, Hossein Fereidooni, Lukas Petzi, Jan König, Jasper Stang, Alexandra Dmitrienko, Ahmad-Reza Sadeghi, Farinaz Koushanfar:
Smarter Contracts: Detecting Vulnerabilities in Smart Contracts with Deep Transfer Learning. NDSS 2023 - [i84]Olivia Weng, Gabriel Marcano, Vladimir Loncar, Alireza Khodamoradi, Nojan Sheybani, Farinaz Koushanfar, Kristof Denolf, Javier Mauricio Duarte, Ryan Kastner:
Tailor: Altering Skip Connections for Resource-Efficient Inference. CoRR abs/2301.07247 (2023) - [i83]Jung-Woo Chang, Nojan Sheybani, Shehzeen Samarah Hussain, Mojan Javaheripi, Seira Hidano, Farinaz Koushanfar:
NetFlick: Adversarial Flickering Attacks on Deep Learning Based Video Compression. CoRR abs/2304.01441 (2023) - [i82]Christoph Sendner, Ruisi Zhang, Alexander Hefter, Alexandra Dmitrienko, Farinaz Koushanfar:
G-Scan: Graph Neural Networks for Line-Level Vulnerability Identification in Smart Contracts. CoRR abs/2307.08549 (2023) - [i81]Patrick McDaniel, Farinaz Koushanfar:
Secure and Trustworthy Computing 2.0 Vision Statement. CoRR abs/2308.00623 (2023) - [i80]Nasimeh Heydaribeni, Ruisi Zhang, Tara Javidi, Cristina Nita-Rotaru, Farinaz Koushanfar:
SABRE: Robust Bayesian Peer-to-Peer Federated Learning. CoRR abs/2308.02747 (2023) - [i79]Nojan Sheybani, Zahra Ghodsi, Ritvik Kapila, Farinaz Koushanfar:
ZKROWNN: Zero Knowledge Right of Ownership for Neural Networks. CoRR abs/2309.06779 (2023) - [i78]Paarth Neekhara, Shehzeen Hussain, Rafael Valle, Boris Ginsburg, Rishabh Ranjan, Shlomo Dubnov, Farinaz Koushanfar, Julian J. McAuley:
SelfVC: Voice Conversion With Iterative Refinement using Self Transformations. CoRR abs/2310.09653 (2023) - [i77]Ruisi Zhang, Shehzeen Samarah Hussain, Paarth Neekhara, Farinaz Koushanfar:
REMARK-LLM: A Robust and Efficient Watermarking Framework for Generative Large Language Models. CoRR abs/2310.12362 (2023) - [i76]Jung-Woo Chang, Ke Sun, Nasimeh Heydaribeni, Seira Hidano, Xinyu Zhang, Farinaz Koushanfar:
Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication Systems. CoRR abs/2311.00207 (2023) - [i75]Nasimeh Heydaribeni, Xinrui Zhan, Ruisi Zhang, Tina Eliassi-Rad, Farinaz Koushanfar:
HypOp: Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks. CoRR abs/2311.09375 (2023) - [i74]Soheil Zibakhsh Shabgahi, Nojan Sheybani, Aiden Tabrizi, Farinaz Koushanfar:
LiveTune: Dynamic Parameter Tuning for Training Deep Neural Networks. CoRR abs/2311.17279 (2023) - [i73]Soheil Zibakhsh Shabgahi, Mohammad Soheil Shariff, Farinaz Koushanfar:
LayerCollapse: Adaptive compression of neural networks. CoRR abs/2311.17943 (2023) - [i72]Yaman Jandali, Nojan Sheybani, Farinaz Koushanfar:
SPAM: Secure & Private Aircraft Management. CoRR abs/2312.00245 (2023) - [i71]Kushal Babel, Mojan Javaheripi, Yan Ji, Mahimna Kelkar, Farinaz Koushanfar, Ari Juels:
Lanturn: Measuring Economic Security of Smart Contracts Through Adaptive Learning. IACR Cryptol. ePrint Arch. 2023: 1338 (2023) - 2022
- [j58]Shehzeen Hussain, Paarth Neekhara, Brian Dolhansky, Joanna Bitton, Cristian Canton Ferrer, Julian J. McAuley, Farinaz Koushanfar:
Exposing Vulnerabilities of Deepfake Detection Systems with Robust Attacks. DTRAP 3(3): 30:1-30:23 (2022) - [j57]Xinghan Wang, Anusha Lalitha, Tara Javidi, Farinaz Koushanfar:
Peer-to-Peer Variational Federated Learning Over Arbitrary Graphs. IEEE J. Sel. Areas Inf. Theory 3(2): 172-182 (2022) - [c159]Shehzeen Hussain, Nojan Sheybani, Paarth Neekhara, Xinqiao Zhang, Javier Mauricio Duarte, Farinaz Koushanfar:
FastStamp: Accelerating Neural Steganography and Digital Watermarking of Images on FPGAs. ICCAD 2022: 41:1-41:9 - [c158]Farinaz Koushanfar:
Intellectual Property (IP) Protection for Deep Learning and Federated Learning Models. IH&MMSec 2022: 5 - [c157]Mojan Javaheripi, Gustavo de Rosa, Subhabrata Mukherjee, Shital Shah, Tomasz Religa, Caio César Teodoro Mendes, Sébastien Bubeck, Farinaz Koushanfar, Debadeepta Dey:
LiteTransformerSearch: Training-free Neural Architecture Search for Efficient Language Models. NeurIPS 2022 - [c156]Thien Duc Nguyen, Phillip Rieger, Huili Chen, Hossein Yalame, Helen Möllering, Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Shaza Zeitouni, Farinaz Koushanfar, Ahmad-Reza Sadeghi, Thomas Schneider:
FLAME: Taming Backdoors in Federated Learning. USENIX Security Symposium 2022: 1415-1432 - [c155]Paarth Neekhara, Shehzeen Hussain, Jinglong Du, Shlomo Dubnov, Farinaz Koushanfar, Julian J. McAuley:
Cross-modal Adversarial Reprogramming. WACV 2022: 2898-2906 - [i70]Yein Kim, Huili Chen, Farinaz Koushanfar:
Backdoor Defense in Federated Learning Using Differential Testing and Outlier Detection. CoRR abs/2202.11196 (2022) - [i69]Mojan Javaheripi, Shital Shah, Subhabrata Mukherjee, Tomasz L. Religa, Caio C. T. Mendes, Gustavo H. de Rosa, Sébastien Bubeck, Farinaz Koushanfar, Debadeepta Dey:
LiteTransformerSearch: Training-free On-device Search for Efficient Autoregressive Language Models. CoRR abs/2203.02094 (2022) - [i68]Jung-Woo Chang, Mojan Javaheripi, Seira Hidano, Farinaz Koushanfar:
Adversarial Attacks on Deep Learning-based Video Compression and Classification Systems. CoRR abs/2203.10183 (2022) - [i67]Paarth Neekhara, Shehzeen Hussain, Xinqiao Zhang, Ke Huang, Julian J. McAuley, Farinaz Koushanfar:
FaceSigns: Semi-Fragile Neural Watermarks for Media Authentication and Countering Deepfakes. CoRR abs/2204.01960 (2022) - [i66]Xinqiao Zhang, Huili Chen, Ke Huang, Farinaz Koushanfar:
An Adaptive Black-box Backdoor Detection Method for Deep Neural Networks. CoRR abs/2204.04329 (2022) - [i65]Huili Chen, Xinqiao Zhang, Ke Huang, Farinaz Koushanfar:
AdaTest: Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection. CoRR abs/2204.06117 (2022) - [i64]Loris Giulivi, Malhar Jere, Loris Rossi, Farinaz Koushanfar, Gabriela F. Ciocarlie, Briland Hitaj, Giacomo Boracchi:
Adversarial Scratches: Deployable Attacks to CNN Classifiers. CoRR abs/2204.09397 (2022) - [i63]Shehzeen Hussain, Todd Huster, Chris Mesterharm, Paarth Neekhara, Kevin An, Malhar Jere, Harshvardhan Sikka, Farinaz Koushanfar:
ReFace: Real-time Adversarial Attacks on Face Recognition Systems. CoRR abs/2206.04783 (2022) - [i62]Zahra Ghodsi, Mojan Javaheripi, Nojan Sheybani, Xinqiao Zhang, Ke Huang, Farinaz Koushanfar:
zPROBE: Zero Peek Robustness Checks for Federated Learning. CoRR abs/2206.12100 (2022) - [i61]Florian Frank, Wenjie Xiong, Nikolaos Athanasios Anagnostopoulos, André Schaller, Tolga Arul, Farinaz Koushanfar, Stefan Katzenbeisser, Ulrich Rührmair, Jakub Szefer:
Abusing Commodity DRAMs in IoT Devices to Remotely Spy on Temperature. CoRR abs/2208.02125 (2022) - [i60]Diego Garcia-soto, Huili Chen, Farinaz Koushanfar:
PerD: Perturbation Sensitivity-based Neural Trojan Detection Framework on NLP Applications. CoRR abs/2208.04943 (2022) - [i59]Ruisi Zhang, Seira Hidano, Farinaz Koushanfar:
Text Revealer: Private Text Reconstruction via Model Inversion Attacks against Transformers. CoRR abs/2209.10505 (2022) - [i58]Shehzeen Hussain, Nojan Sheybani, Paarth Neekhara, Xinqiao Zhang, Javier Mauricio Duarte, Farinaz Koushanfar:
FastStamp: Accelerating Neural Steganography and Digital Watermarking of Images on FPGAs. CoRR abs/2209.12391 (2022) - 2021
- [j56]Mojan Javaheripi, Mohammad Samragh, Bita Darvish Rouhani, Tara Javidi, Farinaz Koushanfar:
Hardware/Algorithm Codesign for Adversarially Robust Deep Learning. IEEE Des. Test 38(3): 31-38 (2021) - [j55]Farinaz Koushanfar:
Provably Secure Sequential Obfuscation for IC Metering and Piracy Avoidance. IEEE Des. Test 38(3): 51-57 (2021) - [j54]Mojan Javaheripi, Bita Darvish Rouhani, Farinaz Koushanfar:
SWANN: Small-World Architecture for Fast Convergence of Neural Networks. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 575-585 (2021) - [j53]Mojan Javaheripi, Mohammad Samragh, Farinaz Koushanfar:
AutoRank: Automated Rank Selection for Effective Neural Network Customization. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 611-619 (2021) - [j52]Karla P. S. Oliveira Esquerre, Mariza Mello, Gabriella Botelho, Zikang Deng, Farinaz Koushanfar, Asher Kiperstok:
Water end-use consumption in low-income households: Evaluation of the impact of preprocessing on the construction of a classification model. Expert Syst. Appl. 185: 115623 (2021) - [j51]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [j50]Malhar Jere, Tyler Farnan, Farinaz Koushanfar:
A Taxonomy of Attacks on Federated Learning. IEEE Secur. Priv. 19(2): 20-28 (2021) - [j49]Siam U. Hussain, M. Sadegh Riazi, Farinaz Koushanfar:
The Fusion of Secure Function Evaluation and Logic Synthesis. IEEE Secur. Priv. 19(2): 48-55 (2021) - [j48]Mojan Javaheripi, Mohammad Samragh, Bita Darvish Rouhani, Tara Javidi, Farinaz Koushanfar:
CuRTAIL: ChaRacterizing and Thwarting AdversarIal Deep Learning. IEEE Trans. Dependable Secur. Comput. 18(2): 736-752 (2021) - [c154]Paarth Neekhara, Shehzeen Hussain, Shlomo Dubnov, Farinaz Koushanfar, Julian J. McAuley:
Expressive Neural Voice Cloning. ACML 2021: 252-267 - [c153]Farinaz Koushanfar:
Machine Learning on Encrypted Data: Hardware to the Rescue. ASHES@CCS 2021: 1 - [c152]Siam Umar Hussain, Mojan Javaheripi, Mohammad Samragh, Farinaz Koushanfar:
COINN: Crypto/ML Codesign for Oblivious Inference via Neural Networks. CCS 2021: 3266-3281 - [c151]Mohammad Samragh, Siam U. Hussain, Xinqiao Zhang, Ke Huang, Farinaz Koushanfar:
On the Application of Binary Neural Networks in Oblivious Inference. CVPR Workshops 2021: 4630-4639 - [c150]Mojan Javaheripi, Farinaz Koushanfar:
HASHTAG: Hash Signatures for Online Detection of Fault-Injection Attacks on Deep Neural Networks. ICCAD 2021: 1-9 - [c149]Huili Chen, Cheng Fu, Jishen Zhao, Farinaz Koushanfar:
ProFlip: Targeted Trojan Attack with Progressive Bit Flips. ICCV 2021: 7698-7707 - [c148]Greg Fields, Mohammad Samragh, Mojan Javaheripi, Farinaz Koushanfar, Tara Javidi:
Trojan Signatures in DNN Weights. ICCVW 2021: 12-20 - [c147]Shehzeen Hussain, Paarth Neekhara, Shlomo Dubnov, Julian J. McAuley, Farinaz Koushanfar:
WaveGuard: Understanding and Mitigating Audio Adversarial Examples. USENIX Security Symposium 2021: 2273-2290 - [c146]Shehzeen Hussain, Paarth Neekhara, Malhar Jere, Farinaz Koushanfar, Julian J. McAuley:
Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples. WACV 2021: 3347-3356 - [i57]Paarth Neekhara, Shehzeen Hussain, Shlomo Dubnov, Farinaz Koushanfar, Julian J. McAuley:
Expressive Neural Voice Cloning. CoRR abs/2102.00151 (2021) - [i56]Xinqiao Zhang, Huili Chen, Farinaz Koushanfar:
TAD: Trigger Approximation based Black-box Trojan Detection for AI. CoRR abs/2102.01815 (2021) - [i55]Paarth Neekhara, Shehzeen Hussain, Jinglong Du, Shlomo Dubnov, Farinaz Koushanfar, Julian J. McAuley:
Cross-modal Adversarial Reprogramming. CoRR abs/2102.07325 (2021) - [i54]Shehzeen Hussain, Paarth Neekhara, Shlomo Dubnov, Julian J. McAuley, Farinaz Koushanfar:
WaveGuard: Understanding and Mitigating Audio Adversarial Examples. CoRR abs/2103.03344 (2021) - [i53]Oliver Lutz, Huili Chen, Hossein Fereidooni, Christoph Sendner, Alexandra Dmitrienko, Ahmad-Reza Sadeghi, Farinaz Koushanfar:
ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learning. CoRR abs/2103.12607 (2021) - [i52]Mohammad Samragh, Hossein Hosseini, Aleksei Triastcyn, Kambiz Azarian, Joseph Soriaga, Farinaz Koushanfar:
Unsupervised Information Obfuscation for Split Inference of Neural Networks. CoRR abs/2104.11413 (2021) - [i51]Greg Fields, Mohammad Samragh, Mojan Javaheripi, Farinaz Koushanfar, Tara Javidi:
Trojan Signatures in DNN Weights. CoRR abs/2109.02836 (2021) - [i50]Mojan Javaheripi, Farinaz Koushanfar:
HASHTAG: Hash Signatures for Online Detection of Fault-Injection Attacks on Deep Neural Networks. CoRR abs/2111.01932 (2021) - [i49]Mehran Abbasi Shirsavar, Mehrnoosh Taghavimehr, Lionel J. Ouedraogo, Mojan Javaheripi, Nicole N. Hashemi, Farinaz Koushanfar, Reza Montazami:
Machine Learning-Assisted E-jet Printing of Organic Flexible Biosensors. CoRR abs/2111.03985 (2021) - 2020
- [j47]Mojan Javaheripi, Mohammad Samragh, Tara Javidi, Farinaz Koushanfar:
AdaNS: Adaptive Non-Uniform Sampling for Automated Design of Compact DNNs. IEEE J. Sel. Top. Signal Process. 14(4): 750-764 (2020) - [j46]Cheng Fu, Huili Chen, Zhenheng Yang, Farinaz Koushanfar, Yuandong Tian, Jishen Zhao:
Enhancing Model Parallelism in Neural Architecture Search for Multidevice System. IEEE Micro 40(5): 46-55 (2020) - [j45]Arslan Munir, Farinaz Koushanfar:
Design and Analysis of Secure and Dependable Automotive CPS: A Steer-by-Wire Case Study. IEEE Trans. Dependable Secur. Comput. 17(4): 813-827 (2020) - [j44]Mohammad Samragh, Mojan Javaheripi, Farinaz Koushanfar:
EncoDeep: Realizing Bit-flexible Encoding for Deep Neural Networks. ACM Trans. Embed. Comput. Syst. 19(6): 43:1-43:29 (2020) - [j43]Huili Chen, Seetal Potluri, Farinaz Koushanfar:
Security of Microfluidic Biochip: Practical Attacks and Countermeasures. ACM Trans. Design Autom. Electr. Syst. 25(3): 27:1-27:29 (2020) - [c145]Siam U. Hussain, Baiyu Li, Farinaz Koushanfar, Rosario Cammarota:
TinyGarble2: Smart, Efficient, and Scalable Yao's Garble Circuit. PPMLP@CCS 2020: 65-67 - [c144]Huili Chen, Rosario Cammarota, Felipe Valencia, Francesco Regazzoni, Farinaz Koushanfar:
AHEC: End-to-end Compiler Framework for Privacy-preserving Machine Learning Acceleration. DAC 2020: 1-6 - [c143]Huili Chen, Siam Umar Hussain, Fabian Boemer, Emmanuel Stapf, Ahmad-Reza Sadeghi, Farinaz Koushanfar, Rosario Cammarota:
Developing Privacy-preserving AI Systems: The Lessons learned. DAC 2020: 1-4 - [c142]