Open Source Intelligence (OSINT)

Siren for Open Source Intelligence (OSINT)

Open Source Intelligence Processing

Maximize OSINT data assets for the Intelligence mission

As valuable as open source information can be to gather vital intelligence required to solve a crime, understand threats and sentiment, it also produces tremendous amounts of data that can cripple an organization. This case study shows how a Siren customer used Siren’s template solution for OSINT to maximize the potential of open source data by incorporating it in their daily operations.

THE PROBLEM

High Volume of Open Source Data to Analyse & No Automation

The customer had a high volume of open source datasets from varied sources to be analysed at a large scale (>800M docs/month). It was difficult to analyse that information and make sense out of it – more challenging because of the mixed ability of the analyst team. Training and onboarding was difficult. Natural Language Processing (NLP) which was often noisy and ambiguous, needed to be revised and cleaned-up by an analyst. There was a need to automate and control the intelligence workflow.

THE SOLUTION

Siren for Open Source Intelligence (OSINT)

Siren offered its unique ability to onboard data, rapidly and get it into the hands of the analysts quickly. The customer was able to fuse the new data with existing case details in a single pane of glass and in a seamless manner with Siren’s template OSINT solution. This deployment was fully implemented in under 2.5 months. Siren Platform supported the full spectrum of data used in open source intelligence. Among the sources were: Social media, commercial news feeds, news aggregators, and the darkweb. The NLP support was provided to allow for sentiment scoring, entity extraction with revision capabilities where analysts wanted to improve the NLP accuracy.

Siren’s Enterprise Workgroup Services offered dataspaces for analysts to work in a controlled and secure team working environment. Integrated case management with JIRA provided fully automated workflow authorization and processes. Dissemination of intelligence to confluence dashboards supported the lifecycle management of investigation.

THE OUTCOME

Analyse Large Scale Data at Speed & Increased Efficiency

The client is now able to process and analyse, in real-time, open source data, producing intelligence insights and reports in 50% of the time it had taken previously. There has been enthusiastic reception by analysts in the simplification of all the analytic processes. Local integrators trained to support, maintain, and evolve the system. Adoption has focused on 3 levels of users; leadership, high level analyst, and advanced analyst user. High levels of workflow automation encouraged wider collaboration and increased efficiency.

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