Cobwebs Visual Link Analysis Tool Allows Investigators to Visualize Digital Fingerprints

The Cobwebs visual link analysis tool allows investigators to find and visualize real relationships between pieces of information from various sources located on the web in an organized and dynamic graphic.

In the event of a major event, such as a natural disaster, authorities need to collect and analyze big data as quickly as possible for disaster relief. Additionally, investigators rely on big data collection and analysis to gain actionable intelligence to conclude their investigations.

In all of these cases, data is collected from open sources such as the surface, deep and dark web, social media, online platforms, blogs, message boards, and online articles.

When collecting these huge volumes of OSINT data, link analysis is needed to visualize the digital footprints left by, for example, a stranded or missing natural disaster victim or a threat actor.

Link analysis helps understand behaviors, tastes and preferences to locate victims or identify threat actors by connecting and visually mapping these digital footprints into interactive node-links. Such visualization allows analysts and investigators to detect patterns and anomalies for in-depth understanding of collected data.

Advanced visual link analytics reveal and visualize hidden and connected web data and present it as a map displaying influential nodes and social communities to reveal patterns.

Link analysis is therefore crucial, especially as the volume and complexity of online data to be collected and analyzed continues to grow.

To solve this problem, more and more companies, institutions and government organizations are opting for a data visualization platform, such as Cobwebs’ AI-powered WEBINT platform, to automatically obtain fast and accurate insights into big data collected for tracking. .

Such a platform provides link analysis and timeline visualization to understand data connections and extract useful and actionable insights in near real-time, allowing to:

  • Smarter surveys, since all data sources are merged;
  • Information sharing for informed operational decisions, such as rescue operations;
  • Quickly and advanced view of data collected from all intelligence sources in a single interactive workspace;
  • Minimize time spent on manual administrative tasks by creating, reviewing and delivering actionable insights in a timely manner using an AI-powered WEBINT platform;
  • Create a centralized knowledge repository to maintain investigative intelligence that can be used by analysts in the future for other events or investigations.

To conclude, timeline visualization and link analysis allow analysts and investigators to get a clear view of the large amounts of big data being collected. They will be able to see patterns in sequences of events as well as map the links between them for tracking.

It allows them to conduct analysis and investigations to obtain the information they need to make the right decisions with limited resources in very dynamic circumstances.

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