Saved in:
| Main Authors: | Chi, Zhiming, Ma, Jianan, Yang, Pengfei, Huang, Cheng-Chao, Li, Renjue, Huang, Xiaowei, Zhang, Lijun |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.01642 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
PRUNE: A Patching Based Repair Framework for Certifiable Unlearning of Neural Networks
by: Li, Xuran, et al.
Published: (2025)
by: Li, Xuran, et al.
Published: (2025)
Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach
by: Yuan, Hanyang, et al.
Published: (2024)
by: Yuan, Hanyang, et al.
Published: (2024)
BeniFul: Backdoor Defense via Middle Feature Analysis for Deep Neural Networks
by: Li, Xinfu, et al.
Published: (2024)
by: Li, Xinfu, et al.
Published: (2024)
BadThink: Triggered Overthinking Attacks on Chain-of-Thought Reasoning in Large Language Models
by: Liu, Shuaitong, et al.
Published: (2025)
by: Liu, Shuaitong, et al.
Published: (2025)
DeepProv: Behavioral Characterization and Repair of Neural Networks via Inference Provenance Graph Analysis
by: Hmida, Firas Ben, et al.
Published: (2025)
by: Hmida, Firas Ben, et al.
Published: (2025)
Provable Repair of Deep Neural Network Defects by Preimage Synthesis and Property Refinement
by: Ma, Jianan, et al.
Published: (2025)
by: Ma, Jianan, et al.
Published: (2025)
Verification of Bit-Flip Attacks against Quantized Neural Networks
by: Zhang, Yedi, et al.
Published: (2025)
by: Zhang, Yedi, et al.
Published: (2025)
Defending against Backdoor Attack on Deep Neural Networks
by: Cheng, Hao, et al.
Published: (2020)
by: Cheng, Hao, et al.
Published: (2020)
Revisiting Transferable Adversarial Images: Systemization, Evaluation, and New Insights
by: Zhao, Zhengyu, et al.
Published: (2023)
by: Zhao, Zhengyu, et al.
Published: (2023)
Deep-Lock: Secure Authorization for Deep Neural Networks
by: Alam, Manaar, et al.
Published: (2020)
by: Alam, Manaar, et al.
Published: (2020)
DPAR: Decoupled Graph Neural Networks with Node-Level Differential Privacy
by: Zhang, Qiuchen, et al.
Published: (2022)
by: Zhang, Qiuchen, et al.
Published: (2022)
Navigating the Deep: End-to-End Extraction on Deep Neural Networks
by: Liu, Haolin, et al.
Published: (2025)
by: Liu, Haolin, et al.
Published: (2025)
Efficient Adversarial Input Generation via Neural Net Patching
by: Khan, Tooba, et al.
Published: (2022)
by: Khan, Tooba, et al.
Published: (2022)
Neural Networks with (Low-Precision) Polynomial Approximations: New Insights and Techniques for Accuracy Improvement
by: Zhang, Chi, et al.
Published: (2024)
by: Zhang, Chi, et al.
Published: (2024)
Node-level Contrastive Unlearning on Graph Neural Networks
by: Lee, Hong kyu, et al.
Published: (2025)
by: Lee, Hong kyu, et al.
Published: (2025)
Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach
by: Bhaila, Karuna, et al.
Published: (2023)
by: Bhaila, Karuna, et al.
Published: (2023)
Synth-MIA: A Testbed for Auditing Privacy Leakage in Tabular Data Synthesis
by: Ward, Joshua, et al.
Published: (2025)
by: Ward, Joshua, et al.
Published: (2025)
NeuroDeX: Unlocking Diverse Support in Decompiling Deep Neural Network Executables
by: Li, Yilin, et al.
Published: (2025)
by: Li, Yilin, et al.
Published: (2025)
QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines
by: Fu, Zhenxiao, et al.
Published: (2024)
by: Fu, Zhenxiao, et al.
Published: (2024)
POT: Inducing Overthinking in LLMs via Black-Box Iterative Optimization
by: Li, Xinyu, et al.
Published: (2025)
by: Li, Xinyu, et al.
Published: (2025)
A Robust Adversary Detection-Deactivation Method for Metaverse-oriented Collaborative Deep Learning
by: Li, Pengfei, et al.
Published: (2023)
by: Li, Pengfei, et al.
Published: (2023)
A transformer-BiGRU-based framework with data augmentation and confident learning for network intrusion detection
by: Zhang, Jiale, et al.
Published: (2025)
by: Zhang, Jiale, et al.
Published: (2025)
Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions
by: Diaa, Abdulrahman, et al.
Published: (2023)
by: Diaa, Abdulrahman, et al.
Published: (2023)
Investigating Application of Deep Neural Networks in Intrusion Detection System Design
by: Jeje, Mofe O.
Published: (2025)
by: Jeje, Mofe O.
Published: (2025)
BlockDoor: Blocking Backdoor Based Watermarks in Deep Neural Networks
by: Puah, Yi Hao, et al.
Published: (2024)
by: Puah, Yi Hao, et al.
Published: (2024)
The SkipSponge Attack: Sponge Weight Poisoning of Deep Neural Networks
by: Lintelo, Jona te, et al.
Published: (2024)
by: Lintelo, Jona te, et al.
Published: (2024)
DeepTaster: Adversarial Perturbation-Based Fingerprinting to Identify Proprietary Dataset Use in Deep Neural Networks
by: Park, Seonhye, et al.
Published: (2022)
by: Park, Seonhye, et al.
Published: (2022)
Certified Defense on the Fairness of Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2023)
by: Dong, Yushun, et al.
Published: (2023)
A PUF-Based Approach for Copy Protection of Intellectual Property in Neural Network Models
by: Dorfmeister, Daniel, et al.
Published: (2026)
by: Dorfmeister, Daniel, et al.
Published: (2026)
PiDAn: A Coherence Optimization Approach for Backdoor Attack Detection and Mitigation in Deep Neural Networks
by: Wang, Yue, et al.
Published: (2022)
by: Wang, Yue, et al.
Published: (2022)
Vulnerability Detection in C/C++ Code with Deep Learning
by: Huang, Zhen, et al.
Published: (2024)
by: Huang, Zhen, et al.
Published: (2024)
CryptGNN: Enabling Secure Inference for Graph Neural Networks
by: Sen, Pritam, et al.
Published: (2025)
by: Sen, Pritam, et al.
Published: (2025)
On the Evaluation of User Privacy in Deep Neural Networks using Timing Side Channel
by: Shukla, Shubhi, et al.
Published: (2022)
by: Shukla, Shubhi, et al.
Published: (2022)
THEMIS: Towards Practical Intellectual Property Protection for Post-Deployment On-Device Deep Learning Models
by: Huang, Yujin, et al.
Published: (2025)
by: Huang, Yujin, et al.
Published: (2025)
MPAT: Building Robust Deep Neural Networks against Textual Adversarial Attacks
by: Zhang, Fangyuan, et al.
Published: (2024)
by: Zhang, Fangyuan, et al.
Published: (2024)
ArcGen: Generalizing Neural Backdoor Detection Across Diverse Architectures
by: Yang, Zhonghao, et al.
Published: (2025)
by: Yang, Zhonghao, et al.
Published: (2025)
Adaptive Pruning of Deep Neural Networks for Resource-Aware Embedded Intrusion Detection on the Edge
by: Broggi, Alexandre, et al.
Published: (2025)
by: Broggi, Alexandre, et al.
Published: (2025)
Beyond One-Size-Fits-All: Neural Networks for Differentially Private Tabular Data Synthesis
by: Chen, Kai, et al.
Published: (2025)
by: Chen, Kai, et al.
Published: (2025)
ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
by: Cheng, Zhan, et al.
Published: (2025)
by: Cheng, Zhan, et al.
Published: (2025)
Can LLMs Patch Security Issues?
by: Alrashedy, Kamel, et al.
Published: (2023)
by: Alrashedy, Kamel, et al.
Published: (2023)
Similar Items
-
PRUNE: A Patching Based Repair Framework for Certifiable Unlearning of Neural Networks
by: Li, Xuran, et al.
Published: (2025) -
Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach
by: Yuan, Hanyang, et al.
Published: (2024) -
BeniFul: Backdoor Defense via Middle Feature Analysis for Deep Neural Networks
by: Li, Xinfu, et al.
Published: (2024) -
BadThink: Triggered Overthinking Attacks on Chain-of-Thought Reasoning in Large Language Models
by: Liu, Shuaitong, et al.
Published: (2025) -
DeepProv: Behavioral Characterization and Repair of Neural Networks via Inference Provenance Graph Analysis
by: Hmida, Firas Ben, et al.
Published: (2025)