Cloudleak: large-scale deep learning models
WebCloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples. H Yu, K Yang, T Zhang, YY Tsai, TY Ho, Y Jin. NDSS, 2024. 99: ... 2024. 97: 2024: Robust adversarial objects against deep learning models. T Tsai, K Yang, TY Ho, Y Jin. Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 954-962, 2024. 67: WebCloudLeak: Large-scale deep learning models stealing through adversarial examples. In 27th Annual Network and Distributed System Security Symposium (NDSS’20), San …
Cloudleak: large-scale deep learning models
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WebCloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples. In NDSS. Google Scholar; Jialong Zhang, Zhongshu Gu, et al. 2024. Protecting intellectual property of deep neural networks with watermarking. AsiaCCS (2024). Google Scholar; Jingjing Zhao, Qingyue Hu, et al. 2024. AFA: Adversarial fingerprinting authentication ... WebDec 31, 2024 · Open Access Cloud-based Machine Learning as a Service (MLaaS) is gradually gaining acceptance as a reliable solution to various real-life scenarios. These services typically utilize Deep Neural Networks (DNNs) to perform classification and detection tasks and are accessed through Application Programming Interfaces (APIs). …
WebApr 7, 2024 · On Efficient Training of Large-Scale Deep Learning Models: A Literature Review Li Shen, Yan Sun, Zhiyuan Yu, Liang Ding, Xinmei Tian, Dacheng Tao The field … WebCloudleak: Large-scale deep learning models stealing through adversarial examples. In Proceedings of Network and Distributed Systems Security Symposium (NDSS). Google …
WebSep 1, 2024 · Deploying deep neural networks on mobile devices is a challenging task due to computation complexity and memory intensity. Current model reduction methods (e.g., matrix approximation using SVD ... WebDOI: 10.14722/ndss.2024.24178 Corpus ID: 211268411; CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples …
WebMar 17, 2024 · 论文标题：CloudLeak：Large-Scale Deep Learning Models Stealing Through Adversarial Examples 会议：Network and Distributed Systems Security (NDSS) …
Web[NDSS20] CloudLeak- Large-Scale Deep Learning Models Stealing Through Adversarial Examples. (image) Distributed Learning or Federated Learning [USENIX20] Justinian’s GAAvernor- Robust Distributed Learning with Gradient Aggregation Agent. [USENIX20] Local Model Poisoning Attacks to Byzantine-Robust Federated Learning. code of conduct nhs walesWebThis work launches the first imitation attack on LLCMs by querying a target LLCM with carefully-designed queries and collecting the outputs, and systematically investigates the effectiveness of launching imitation attacks under different query schemes and different LLCM tasks. Recent progress in large language code models (LLCMs) has led to a … code of conduct nurse ukWebCloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples. H Yu, K Yang, T Zhang, YY Tsai, TY Ho, Y Jin. NDSS ... Spectral clustering based on local PCA. E Arias-Castro, G Lerman, T Zhang. The Journal of Machine Learning Research 18 (1), 253-309, 2024. 91: 2024: Multivariate generalized Gaussian distribution: Convexity ... code of conduct of clicksWebFederated learning is good for building better cooperative intelligent transportation system (C-ITS). Intellectual property protection in C-ITS brings many benefits to all vehicles. Although the protection of model intellectual property by watermark has received much research attention, the existing works only deploy watermark in centralized ... code of conduct nsw healthWebYun-Yun Tsai. CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples. Proceedings of the IEEE/CVF Conference on Computer Vision … calories in one piece of dove dark chocolateWebCloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples. Network and Distributed…. Cloud-based Machine Learning as a Service (MLaaS) is … calories in one piece of turkey baconWebOur attack framework can steal large-scale deep learning models with high accuracy, few queries and low costs simultaneously. The same trend appears while we use different transfer architectures to steal black-box target model. 24 A Comparison to prior works. Proposed Attacks Parameter Size Queries Accuracy Black-box? Stealing Cost calories in one piece of swiss cheese