Cyber threat intelligence (CTI) is one of the hottest topics in our industry right now and the noise surrounding it is deafening. Gartner and Forrester are covering the sector. Run a quick Google search and you’ll find nearly 2 million results, including a wave of product offerings and the creation of dedicated intelligence teams to help you build those offerings.

What is CTI? Ah, definitions! But yes, semantics do matter. To borrow a line from the Chris Farley comedy, Tommy Boy, “Just because you slap a label on it that says cyber threat intelligence, doesn’t make it intelligence...” Much like the now ubiquitous banner of cloud computing, cyber threat intelligence risks becoming a watered-down phrase, the purpose of which is to sell existing technology solutions. That is, unless we are careful to use the term consistently and in the right way.

I find it critically important to recognize the fundamental difference between raw or processed information and real intelligence. The former supports the latter but they are distinctly different in their value. A useful comparison of the difference between information and intelligence is summarized below. It is largely driven from the pioneers in the field of intelligence, our governments and militaries around the world, as well as the information science community.

Table 1: Info v Intel

Our militaries and governments have spent thousands of years (and much in the way of resources) to create and disseminate useful intelligence. Even if they don’t do it perfectly, nor always move as quickly on new threats or new technologies as we would like, we can clearly turn to them as experts in defining CTI. For example, the FBI has a published definition for intelligence that is useful: “simply defined, intelligence is information that has been analyzed and refined so that it is useful to policymakers in making decisions – specifically, decisions about potential threats to our national security.” Substitute “security and business professionals” for “policy makers” and change “national” to “corporate” or “organizational” and you’ve got a good working definition.

Similarly, information science gives the Data, Information, Knowledge, Wisdom (DIKW) hierarchy, in which data supports information which in turn can be used to create knowledge and ultimately enable wisdom. An example: all sensor data points could be data, and all the alerts within that data could be information. But knowledge comes with added context to those alerts, and wisdom could be the set of knowledge distilled into the skill of the security operator who is an expert on the process of distilling data to context and could create new automated technologies to do the same.

So going back to your challenge of figuring out how to leverage cyber threat intelligence in your organization, Gartner has published a useful definition: “evidence-based knowledge, including context, mechanisms, indicators, implications and actionable advice about an existing or emerging menace or hazard to assets that can be used to inform decisions regarding the subject’s response...” That’s definitely more than data and information.

More data, more problems
As you approach your specific implementation, don’t equate cyber threat intelligence with raw information. Security teams and the technologies they employ don’t need more raw data or raw information -- they’re already swimming in it. Haystacks of haystacks of event data pile in from

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