Machine Learning for Encrypted Malicious Traffic Detection: Approaches, Datasets and Comparative Study. (arXiv:2203.09332v1 [cs.CR] CROSS LISTED)

As people's demand for personal privacy and data security becomes a priority,
encrypted traffic has become mainstream in the cyber world. However, traffic
encryption is also shielding malicious and illegal traffic introduced by
adversaries, from being detected. This is especially so in the post-COVID-19
environment where malicious traffic encryption is growing rapidly. Common
security solutions that rely on plain payload content analysis such as deep
packet inspection are rendered useless. Thus, machine learning based approaches
have become an important direction …

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