Intrusion Detection With Deep Learning Classifiers: A Synergistic Approach of Probabilistic Clustering and Human Expertise to Reduce False Alarms.
Abdoul-Aziz MaigaEdwin AtaroStanley GithinjiPublished in: IEEE Access (2024)
Keyphrases
- intrusion detection
- false alarms
- deep learning
- unsupervised learning
- anomaly detection
- intrusion detection system
- worm detection
- number of false alarms
- network security
- detection rate
- network intrusion detection
- network traffic
- clustering algorithm
- false positives
- detecting anomalous
- machine learning
- data mining
- k means
- supervised learning
- training data
- probabilistic model
- mental models
- training set
- feature selection
- data mining techniques
- generative model
- decision trees
- alert correlation
- weakly supervised
- data points
- face detection
- association rules
- support vector
- knowledge discovery
- expectation maximization
- model selection
- real world
- network intrusions