Simulation of Dark Network Scene Based on the Big Data Environment

Abstract

In the era of big data, the amount of information on dark network resources has exploded. Massive dark network data contain abundant information. To detect dark network resources and obtain dark network information, in-depth understanding of the dark network is a prerequisite. However, due to the high anonymity of dark network, it is usually difficult to be found by traditional search engines. Users need to register strictly and use specific tools to log in dynamically. In this paper, we explore the simulation of dark network scene in the big data environment. The Tor network is built on the openstack platform, which simulate the dark network scene. By using wireshark software to analyze network traffic, and using nmon tool to analyze network performance, the results show that the dark network scene can be simulated realistically.