This paper analyzes CNNs for malware detection in cloud IaaS.
arXiv research
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The paper proposes a SeqGAN model to generate balanced log messages for anomaly detection.
Log messages are now widely used in software systems. They are important for classification as millions of logs are generated each day. Most logs are unstructured which makes classification a challenge. In this paper, Deep Learning (DL) methods called Auto-LSTM, Auto-BLSTM and Auto-GRU are developed for anomaly detecti…
Method uses Seq2Seq learning to automatically generate recovery commands for ICT systems.
Anomaly detecting as an important technical in cloud computing is applied to support smooth running of the cloud platform. Traditional detecting methods based on statistic, analysis, etc. lead to the high false-alarm rate due to non-adaptive and sensitive parameters setting. We presented an online model for anomaly det…