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Deep Dict: Deep Learning-based Lossy Time Series Compressor for IoT Data
We propose Deep Dict, a deep learning-based lossy time series compressor designed to achieve a high compression ratio while maintaining decompression error within a predefined range.
Host-Based Network Intrusion Detection via Feature Flattening and Two-stage Collaborative Classifier
Performance of XGBoost, which represents conventional ML, is evaluated.
Machine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats
Advanced persistent threat (APT) is prominent for cybercriminals to compromise networks, and it is crucial to long-term and harmful characteristics.
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