Performance evaluation of full-cloud and edge-cloud architectures for Industrial IoT anomaly detection based on deep learning.
Paolo FerrariStefano RinaldiEmiliano SisinniF. ColomboF. GhelfiDavide MaffeiMatteo MalaraPublished in: MetroInd4.0&IoT (2019)
Keyphrases
- anomaly detection
- deep learning
- cloud computing
- unsupervised learning
- intrusion detection
- anomalous behavior
- network traffic
- network intrusion detection
- detecting anomalies
- intrusion detection system
- network anomaly detection
- one class support vector machines
- negative selection algorithm
- detect anomalies
- mental models
- data management
- image segmentation
- machine learning
- image processing
- information retrieval