| Paper | Summary | Published |
| Review Deep Learning for Network Traffic Monitoring and Analysis (NTMA): A Survey | network ids Table 3 A summary of works on network traffic classification. flow based traffic classification Big data approach Real time analysis Intrusion Detection Malware analysis | Elsevier, 2021 |
| Machine Learning for Traffic Analysis: A Review | flow analysis is based on the identification of anonymity networks [4][5]. There are many techniques used to analyse network traffic, such as self-similarity and TES, which are based on communication system analysis and attacks discovery [3] | Elsevier, 2020 |
| Encrypted Malware Traffic Detection via Graph-based Network Analysis | stream attributes, ST-Graph explores spatial and temporal characteristics of network behaviours based on a graph representation learning algorithm and integrates all available information to boost the detection decision. | RAID ’22: Proceedings of the 25th International Symposium on Research in Attacks, Intrusions and Defenses |
| A Study on Detection of Malicious Behavior Based on Host Process Data Using Machine Learning | Nice overview and explicitly targets APTs. Describes the data collection. However, operates on local “process” data, not network traffic data. | Applied Sciences 2023 |
| Artificial intelligence in cyber security: research advances, challenges, and opportunities | not available online | Springer 2022 |
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