![]() Machine learning faces two obstacles: obtaining a sufficient training set of malicious and normal traffic and retraining the system as malware evolves. Using machine learning, these traffic patterns can be utilized to identify malicious software. One way to identify malware is by analyzing the communication that the malware performs on the network. Malware is constantly evolving and changing. Original post on the topic appeared at Cisco blog For more details, please refer to our articles published in ECML PKDD 2015 proceedings. This page gives a high level overview of our research on Learning Detectors of Malicious Network Traffic. Learning Detectors of Malicious Network Traffic Projects / Network Security / Malicious Network Traffic Detection ![]()
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