Network Traffic Analysis

Research focused on the application of data analysis methods to network security and anomaly detection at network level. Some explored topics are: traffic characterization and classification; covert channels; network attacks, anomalies and misconfigurations; analysis methodologies and frameworks; feature selection; analysis of large networks and the Internet Background Radiation (aka darkspaces).

Traffic Flow Mapping tool

TFM is a tool for online visualization of traffic based on representation learning.

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NTA Database: Curation of Network Traffic Analysis Research

With the NTA Database we aim to collect relevant information about the research in network traffic analysis conducted during the last years. To this end, we have curated related papers from journals and conferences and stored the extracted data in JSON files. You can access database files, first meta-analysis results and data structure descriptions here.

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Feature Vectors for Network Traffic Analysis

We study the discriminant power of network features for traffic analysis, classification and attack detection network level. We compare existing feature sets previouly proposed in the literature and study new proposals. We aim to obtain lightweight vectors able to deal with modern network traffic challenges, such as: encryption, big data, stream data, fast extraction and preprocessing, prompt responses, host/flow/network behaviour modeling, network monitoring, etc.

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Analysis of the IBR based on AGM vectors

We analyzed captures from the Internet Background Radiation (aka darkspaces) by using the AGM format. Time series, plots, descriptions of classes and datasets are available for consultation.

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