Next Generation Intrusion Detection: Autonomous Reinforcement Learning of Network Attacks
By Cannady, D. James. 2000
88 citations recorded by the source corpus.
Subfields: Reinforcement Learning, Safety, Robustness & Interpretability
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Reinforcement Learning
- Mohammad Ali Salahuddin
- Sara Ayoubi
- Dipankar Dasgupta
- Raouf Boutaba
- Michael P. Wellman
- Noura Limam
- Nicolas Papernot
- Wolfgang Banzhaf
In Safety, Robustness & Interpretability
- Nicolas Papernot
- Patrick Drew McDaniel
- Michael P. Wellman
- Arunesh Sinha
- Nicholas Carlini
- Ian J. Goodfellow
- Dawn Song
- Yanjun Qi
Citations in the corpus
- Towards the Science of Security and Privacy in Machine Learning (2016, background): “Finally, consider the same intrusion-detection problem given access to metrics of system state indicator (CPU load, free memory, network load, etc.) [20].”
- SoK: Security and Privacy in Machine Learning (2018, background): “em falls under the scope of unsupervised learning. Finally, consider the same intrusion-detection problem given access to metrics of system state indicator (CPU load, free memory, network load, etc.) [20]. This variant of the intrusion detector can then be viewed as an agent and the system state 2 i”
- An immunity-based technique to characterize intrusions in computer networks (2002, background): “Other approaches also build models to predict the future behavior of systems or processes based on the present and past states [4], [5], [14], [17], [23].”
- A comprehensive survey on machine learning for networking: evolution, applications and research opportunities (2018, methodology): “A less conventional application of RL is [85], which consists of an online IDS based on adaptive NNwithmodified RL.”
- The use of computational intelligence in intrusion detection systems: A review (2010, background): “This is the main reason that Cannady [41] [42] applied CMAC to autonomously learn new attacks.”