Anomaly Detection for Consortium Blockchains Based on Machine Learning Classification Algorithm.
Dongyan HuangBin ChenLang LiYong DingPublished in: CSoNet (2020)
Keyphrases
- pairwise
- anomaly detection
- classification algorithm
- machine learning
- support vector machine
- intrusion detection
- learning algorithm
- network anomaly detection
- detecting anomalies
- network traffic
- naive bayes
- unsupervised learning
- knn
- k nearest neighbor
- training set
- anomalous behavior
- intrusion detection system
- network intrusion detection
- decision trees
- concept drift
- machine learning algorithms
- class labels
- supervised learning
- feature selection
- semi supervised
- text classification
- active learning
- pattern recognition
- one class support vector machines
- cumulative sum
- model selection
- computer vision
- text mining
- natural language processing
- information extraction
- data analysis
- negative selection algorithm
- detecting anomalous
- nearest neighbor
- reinforcement learning
- detect anomalies
- training data
- data mining
- real world