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Data-Driven Threat Intelligence: Metrics On Indicator Dissemination And Sharing

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Published on Dec 28, 2015

by Alex Pinto & Alexandre Sieira

For the past 18 months, Niddel have been collecting threat intelligence indicator data from multiple sources in order to make sense of the ecosystem and try to find a measure of efficiency or quality in these feeds. This initiative culminated in the creation of Combine and TIQ-test, two of the open source projects from MLSec Project. These projects have been improved upon for the last year and are able to gather and compare data from multiple Threat Intelligence sources on the Internet.

We take this analysis a step further and extract insights form more than 12 months of collected threat intel data to verify the overlap and uniqueness of those sources. If we are able to find enough overlap, there could be a strategy that could put together to acquire an optimal number of feeds, but as Niddel demonstrated on the 2015 Verizon DBIR, that is not the case.

We also gathered aggregated usage information from intelligence sharing communities in order to determine if the added interest and "push" towards sharing is really being followed by the companies and if its adoption is putting us in the right track to close these gaps.

Join us in an data-driven analysis of over an year of collected Threat Intelligence indicators and their sharing communities!

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