Volume 9 - Issue 2
A visual analytics approach for the cyber forensics based on different views of the network traffic
- Igor Kotenko
Laboratory of Computer Security Problems, St. Petersburg Institute for Informatics and Automation (SPIIRAS), 39, 14-th Liniya, Saint-Petersburg, 199178, Russia, Saint-Petersburg ITMO University, 49, Kronverksky Prospect, St. Petersburg, Russia
- Maxim Kolomeets
Laboratory of Computer Security Problems, St. Petersburg Institute for Informatics and Automation (SPIIRAS), 39, 14-th Liniya, Saint-Petersburg, 199178, Russia, Saint-Petersburg ITMO University, 49, Kronverksky Prospect, St. Petersburg, Russia
- Andrey Chechulin
Laboratory of Computer Security Problems, St. Petersburg Institute for Informatics and Automation (SPIIRAS), 39, 14-th Liniya, Saint-Petersburg, 199178, Russia, Saint-Petersburg ITMO University, 49, Kronverksky Prospect, St. Petersburg, Russia
- Yannick Chevalier
Saint-Petersburg ITMO University, 49, Kronverksky Prospect, St. Petersburg, Russia
Keywords: network forensics, visual analytics, data visualization, traffic analysis, cyber-attack investigation.
Abstract
Network forensics is based on the analysis of network traffic. Traffic analysis is a routine procedure,
but it allows one to not only identify the cause of the security breach, but also step by step to recreate
the whole picture of what happened. To analyze the traffic, investigators usually use Wireshark, a
software that has the graphical interface and has greater capabilities for sorting and filtering packets.
But even with it, packet analysis takes a lot of time. In this paper, we propose an approach for cyber
forensics based on different views on the network traffic. Using this approach, it is possible to significantly
improve the efficiency of forensic scientists, including the rapid localization of anomalies and,
importantly, the creation of easily understandable graphical proofs and histories of computer attacks.
The example of the investigation of the attack SSL-strip is a way to classify different views (slices)
of traffic and a scheme for using for these slices different models of visualization. Also provides an
assessment and recommendations for the application of visual analytics methods.