![]() ![]() To get a feel for the scale of the data visualization challenge, I ran the tool on my own laptop for just 15 seconds – enough time for me to visit, the homepage of our Connected Data Visualization Consortium. The Wireshark protocol analyzer is one of the best-known tools for collecting network packet data. Let’s create an example dataset of network traffic for our demo. They rely on network or link analysis to understand the relationships behind the data, and forensic timeline analysis methods to reveal the exact sequence of data points. But it’s a daunting challenge – how do you reveal insight from such vast amounts of densely-connected data? ![]() ![]() Whether for network monitoring and performance management, cyber security or lawful intercept intelligence, analysts need to make sense of this traffic fast. The numbers are incomprehensible – some estimates put global IP traffic in the order of tens of exabytes per day (one exabyte being 1,000,000,000,000,000,000 bytes).Įach IP packet contains data arranged according to some protocol, such as Transmission Control Protocol (TCP – used by website browsing and email), User Datagram Protocol (UDP – used in video conference calls), and a whole raft of proprietary formats that connect our devices. The computers and internet-enabled devices we use every day have a ceaseless torrent of network packet data running in the background. Forensic timeline analysis: one of the many popular use cases for KronoGraph timeline analysis Why forensic timeline analysis? In this blog post, we demonstrate how to use network visualization and forensic timeline analysis to make sense of complex, high-velocity network traffic. ![]()
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