Hu et al., 2018 - Google Patents
GANFuzz: A GAN-based industrial network protocol fuzzing frameworkHu et al., 2018
- Document ID
- 14568229546796839133
- Author
- Hu Z
- Shi J
- Huang Y
- Xiong J
- Bu X
- Publication year
- Publication venue
- Proceedings of the 15th ACM International Conference on Computing Frontiers
External Links
Snippet
In this paper, we attempt to improve industrial safety from the perspective of communication security. We leverage the protocol fuzzing technology to reveal errors and vulnerabilities inside implementations of industrial network protocols (INPs). Traditionally, to effectively …
- 238000005516 engineering process 0 abstract description 4
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Hu et al. | GANFuzz: A GAN-based industrial network protocol fuzzing framework | |
| Anton et al. | Anomaly-based intrusion detection in industrial data with SVM and random forests | |
| Samy et al. | Fog-based attack detection framework for internet of things using deep learning | |
| Ortet Lopes et al. | Towards effective detection of recent DDoS attacks: A deep learning approach | |
| CN106663167B (en) | Identifying behavioral changes of an online service | |
| Garcia et al. | A deep learning-based intrusion detection and preventation system for detecting and preventing denial-of-service attacks | |
| Bodström et al. | State of the art literature review on network anomaly detection with deep learning | |
| Torres et al. | Active learning approach to label network traffic datasets | |
| Liang et al. | FARE: enabling fine-grained attack categorization under low-quality labeled data | |
| Dou et al. | Pc 2 a: predicting collective contextual anomalies via lstm with deep generative model | |
| Alhayali et al. | Optimized machine learning algorithm for intrusion detection | |
| Rovetta et al. | Bot or not? a case study on bot recognition from web session logs | |
| Usama et al. | The adversarial machine learning conundrum: can the insecurity of ml become the achilles' heel of cognitive networks? | |
| EP4435649A1 (en) | Apparatus and method for automatically analyzing malicious event log | |
| Berghout et al. | EL-NAHL: Exploring labels autoencoding in augmented hidden layers of feedforward neural networks for cybersecurity in smart grids | |
| KR102692350B1 (en) | Malicious event log automatic analysis device and method | |
| Vijayalakshmi et al. | Hybrid dual-channel convolution neural network (DCCNN) with spider monkey optimization (SMO) for cyber security threats detection in internet of things | |
| Zarai | Recurrent Neural Networks & Deep Neural Networks Based on Intrusion Detection System | |
| Chakraborty et al. | Industrial control system device classification using network traffic features and neural network embeddings | |
| He et al. | Reinforcement learning meets network intrusion detection: a transferable and adaptable framework for anomaly behavior identification | |
| Meena Siwach | Anomaly detection for web log data analysis: A review | |
| Yang et al. | Cloud-edge coordinated traffic anomaly detection for industrial cyber-physical systems | |
| Djenouri et al. | Interpretable intrusion detection for next generation of Internet of Things | |
| Saheed et al. | ResNet50-1D-CNN: A new lightweight resNet50-One-dimensional convolution neural network transfer learning-based approach for improved intrusion detection in cyber-physical systems | |
| Eshak Magdy et al. | A Comparative study of intrusion detection systems applied to NSL-KDD Dataset |