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2020 – today
- 2025
[e5]Zhipeng Cai
, Daniel Takabi, Shaoyong Guo, Yifei Zou:
Wireless Artificial Intelligent Computing Systems and Applications - 18th International Conference, WASA 2024, Qindao, China, June 21-23, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14997, Springer 2025, ISBN 978-3-031-71463-4 [contents]- [e4]Zhipeng Cai, Daniel Takabi, Shaoyong Guo, Yifei Zou:
Wireless Artificial Intelligent Computing Systems and Applications - 18th International Conference, WASA 2024, Qindao, China, June 21-23, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14998, Springer 2025, ISBN 978-3-031-71466-5 [contents] - [e3]Zhipeng Cai, Daniel Takabi, Shaoyong Guo, Yifei Zou:
Wireless Artificial Intelligent Computing Systems and Applications - 18th International Conference, WASA 2024, Qindao, China, June 21-23, 2024, Proceedings, Part III. Lecture Notes in Computer Science 14999, Springer 2025, ISBN 978-3-031-71469-6 [contents] - 2024
- [j12]Adel Rezapour, Mohammad GhasemiGol, Daniel Takabi:
A Systematic Mapping Study on Intrusion Response Systems. IEEE Access 12: 46524-46550 (2024) - [j11]Prajwal Panzade, Daniel Takabi, Zhipeng Cai:
Privacy-Preserving Machine Learning Using Functional Encryption: Opportunities and Challenges. IEEE Internet Things J. 11(5): 7436-7446 (2024) - [j10]Mohammad Hossein Rafiei, Lynne V. Gauthier, Hojjat Adeli, Daniel Takabi:
Self-Supervised Learning for Near-Wild Cognitive Workload Estimation. J. Medical Syst. 48(1): 107 (2024) - [j9]Javad Rafiei Asl, Mohammad Hossein Rafiei, Manar Alohaly, Daniel Takabi:
A Semantic, Syntactic, and Context-Aware Natural Language Adversarial Example Generator. IEEE Trans. Dependable Secur. Comput. 21(5): 4754-4769 (2024) - [j8]Mohammad Hossein Rafiei, Lynne V. Gauthier, Hojjat Adeli, Daniel Takabi:
Self-Supervised Learning for Electroencephalography. IEEE Trans. Neural Networks Learn. Syst. 35(2): 1457-1471 (2024) - [c8]Robert Podschwadt, Parsa Ghazvinian, Mohammad GhasemiGol, Daniel Takabi:
Memory Efficient Privacy-Preserving Machine Learning Based on Homomorphic Encryption. ACNS (2) 2024: 313-339 - [c7]Javad Rafiei Asl, Prajwal Panzade, Eduardo Blanco, Daniel Takabi, Zhipeng Cai:
RobustSentEmbed: Robust Sentence Embeddings Using Adversarial Self-Supervised Contrastive Learning. NAACL-HLT (Findings) 2024: 3795-3809 - [i8]Prajwal Panzade, Daniel Takabi, Zhipeng Cai:
MedBlindTuner: Towards Privacy-preserving Fine-tuning on Biomedical Images with Transformers and Fully Homomorphic Encryption. CoRR abs/2401.09604 (2024) - [i7]Prajwal Panzade, Daniel Takabi, Zhipeng Cai:
I can't see it but I can Fine-tune it: On Encrypted Fine-tuning of Transformers using Fully Homomorphic Encryption. CoRR abs/2402.09059 (2024) - [i6]Javad Rafiei Asl, Prajwal Panzade, Eduardo Blanco, Daniel Takabi, Zhipeng Cai:
RobustSentEmbed: Robust Sentence Embeddings Using Adversarial Self-Supervised Contrastive Learning. CoRR abs/2403.11082 (2024) - [i5]Javad Rafiei Asl, Mohammad Hossein Rafiei, Manar Alohaly, Daniel Takabi:
SSCAE - Semantic, Syntactic, and Context-aware natural language Adversarial Examples generator. CoRR abs/2403.11833 (2024) - 2023
- [j7]Zuobin Xiong, Zhipeng Cai, Chunqiang Hu, Daniel Takabi, Wei Li:
Towards Neural Network-Based Communication System: Attack and Defense. IEEE Trans. Dependable Secur. Comput. 20(4): 3238-3250 (2023) - [c6]Prajwal Panzade, Daniel Takabi:
FENet: Privacy-preserving Neural Network Training with Functional Encryption. IWSPA@CODASPY 2023: 33-43 - [c5]Javad Rafiei Asl, Eduardo Blanco, Daniel Takabi:
RobustEmbed: Robust Sentence Embeddings Using Self-Supervised Contrastive Pre-Training. EMNLP (Findings) 2023: 4587-4603 - [e2]Silvio Ranise, Roberto Carbone, Daniel Takabi:
Proceedings of the 28th ACM Symposium on Access Control Models and Technologies, SACMAT 2023, Trento, Italy, June 7-9, 2023. ACM 2023 [contents] - [i4]Olusesi Balogun, Daniel Takabi:
An Insider Threat Mitigation Framework Using Attribute Based Access Control. CoRR abs/2305.19477 (2023) - 2022
- [j6]Manar Alohaly, Olusesi Balogun, Daniel Takabi:
Integrating Cyber Deception Into Attribute-Based Access Control (ABAC) for Insider Threat Detection. IEEE Access 10: 108965-108978 (2022) - [j5]Robert Podschwadt, Daniel Takabi, Peizhao Hu, Mohammad Hossein Rafiei, Zhipeng Cai:
A Survey of Deep Learning Architectures for Privacy-Preserving Machine Learning With Fully Homomorphic Encryption. IEEE Access 10: 117477-117500 (2022) - [j4]Honghui Xu, Zhipeng Cai, Daniel Takabi, Wei Li:
Audio-Visual Autoencoding for Privacy-Preserving Video Streaming. IEEE Internet Things J. 9(3): 1749-1761 (2022) - [j3]Nipuna Senanayake, Robert Podschwadt, Daniel Takabi, Vince D. Calhoun, Sergey M. Plis:
NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data. Neuroinformatics 20(1): 91-108 (2022) - [j2]Zuobin Xiong, Zhipeng Cai, Daniel Takabi, Wei Li:
Privacy Threat and Defense for Federated Learning With Non-i.i.d. Data in AIoT. IEEE Trans. Ind. Informatics 18(2): 1310-1321 (2022) - [e1]Sven Dietrich, Omar Chowdhury, Daniel Takabi:
SACMAT '22: The 27th ACM Symposium on Access Control Models and Technologies, New York, NY, USA, June 8 - 10, 2022. ACM 2022, ISBN 978-1-4503-9357-7 [contents] - [i3]Prajwal Panzade, Daniel Takabi:
SoK: Privacy Preserving Machine Learning using Functional Encryption: Opportunities and Challenges. CoRR abs/2204.05136 (2022) - 2021
- [c4]Robert Podschwadt, Daniel Takabi:
Non-interactive Privacy Preserving Recurrent Neural Network Prediction with Homomorphic Encryption. CLOUD 2021: 65-70 - [c3]Prajwal Panzade, Daniel Takabi:
Towards Faster Functional Encryption for Privacy-preserving Machine Learning. TPS-ISA 2021: 21-30 - [i2]Robert Podschwadt, Daniel Takabi, Peizhao Hu:
SoK: Privacy-preserving Deep Learning with Homomorphic Encryption. CoRR abs/2112.12855 (2021) - 2020
- [j1]Srinath Obla, Xinghan Gong, Asma Aloufi, Peizhao Hu, Daniel Takabi:
Effective Activation Functions for Homomorphic Evaluation of Deep Neural Networks. IEEE Access 8: 153098-153112 (2020) - [c2]Manar Alohaly, Daniel Takabi:
A Hybrid Policy Engineering Approach for Attribute-Based Access Control (ABAC). SoCPaR 2020: 847-857 - [c1]Robert Podschwadt, Daniel Takabi:
Classification of Encrypted Word Embeddings using Recurrent Neural Networks. PrivateNLP@WSDM 2020: 27-31
2010 – 2019
- 2019
- [i1]Daniel Takabi, Robert Podschwadt, Jeff Druce, Curt Wu, Kevin Procopio:
Privacy preserving Neural Network Inference on Encrypted Data with GPUs. CoRR abs/1911.11377 (2019)
Coauthor Index
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