Towards Reverse-Engineering Black-Box Neural Networks-Reference-Cited by-同舟云学术

Towards Reverse-Engineering Black-Box Neural Networks

Published:2019 Issue: Volume: Page:121-144
ISSN:0302-9743
Container-title:Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
language:
Short-container-title:

Author:

Oh Seong Joon,Schiele Bernt,Fritz Mario

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-28954-6_7

Reference34 articles.

1. Ateniese, G., Mancini, L.V., Spognardi, A., Villani, A., Vitali, D., Felici, G.: Hacking smart machines with smarter ones: how to extract meaningful data from machine learning classifiers. Int. J. Secur. Netw. 10(3), 137–150 (2015)

2. Caruana, R., Lou, Y., Gehrke, J., Koch, P., Sturm, M., Elhadad, N.: Intelligible models for healthcare: predicting pneumonia risk and hospital 30-day readmission. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1721–1730. ACM (2015)

3. Chen, P.Y., Zhang, H., Sharma, Y., Yi, J., Hsieh, C.J.: Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models. In: Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, pp. 15–26. ACM, New York (2017)

4. Dabkowski, P., Gal, Y.: Real time image saliency for black box classifiers. In: Advances in Neural Information Processing Systems, pp. 6967–6976 (2017)

5. Fong, R.C., Vedaldi, A.: Interpretable explanations of black boxes by meaningful perturbation. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 3449–3457. IEEE (2017)

Cited by 99 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Trait-level predictors of human performance outcomes in personnel engaged in stressful laboratory and field tasks;Frontiers in Psychology;2024-09-09

2. Bio-Rollup: a new privacy protection solution for biometrics based on two-layer scalability-focused blockchain;PeerJ Computer Science;2024-09-09

3. EdgePro: Edge Deep Learning Model Protection via Neuron Authorization;IEEE Transactions on Dependable and Secure Computing;2024-09

4. BIC-Based Mixture Model Defense Against Data Poisoning Attacks on Classifiers: A Comprehensive Study;IEEE Transactions on Knowledge and Data Engineering;2024-08

5. Knowledge Leaks in Data-Driven Business Models? Exploring Different Types of Knowledge Risks and Protection Measures;Schmalenbach Journal of Business Research;2024-07-30