In the wake of public breaches of large enterprises, organizations are quickly realizing the need to develop cybersecurity strategies that include developing or acquiring technical and analytical solutions to support network defenders and decision makers alike. As a result, there has been a noticeable boon in the global cybersecurity industry, which is expected to grow to $155.7 billion by 2019, according to a report from Cybersecurity Ventures, a world market research organization.
One capability being offered by many of these cybersecurity companies is cyberthreat intelligence, which usually encompasses a fusion of technical and threat analysis. Vendors promote their analytic capabilities to deliver accurate, timely threat information in order to provide advanced warning or decision-making advantage to their customers.
However, one challenge that all private security companies have in this space is getting the proper guidance and information from customers, which could be used to improve and focus analysis. An intelligence production cycle will typically have these components, though some organizations may have an added or subtracted step:
- Setting requirements
- Gathering data
- Interpreting gathered data
- Analyzing and reporting
- Disseminating final product
During the setting-requirements phase is when a customer will engage with an intelligence unit to identify and determine the issues that need to be covered and shape any intelligence requirements that need to be addressed. Granted, there are those occasions when customers may not know exactly what they want or don’t know how to communicate it via their intelligence requirements. At these times, it is incumbent upon intelligence analysts to help educate and inform customers about the potential pitfalls that may result if requirements are not more advantageously scoped.
This is a critical stage of the process because if questions are not properly scoped and prioritized, collection strategies will be impacted, and the finished intelligence product may not be responsive or may be too vague to be useful. Time invested up front in setting prioritized focused requirements will prevent this from happening.
This is particularly important with cyber-intelligence because organizations can provide information unique to their particular environment and receive indicators and intelligence that help shape their cybersecurity postures. Indeed, Carnegie Mellon’s Software Engineering Institute (SEI) echoes this sentiment in a January 2013 report reviewing how private companies conduct cyber-intelligence. SEI’s key findings cited scoping the cyber-environment to an organization’s mission as one of its recommended best practices for the cyber-intelligence industry.
Ultimately, intelligence analysis should be looked upon as less of a service and more of a partnership whose success relies on the full commitment and engagement of both intelligence producer and intelligence consumer. Organizations that adopt the intelligence cycle into their business practices will find that the more they provide to the process, the more they will receive. Sharing pertinent data such as technical data collected from hostile activity transpiring against networks, and providing advanced notice of business activities, will help focus analytic efforts on the most pertinent cyberthreats against the enterprise. In turn, this information can contribute to the larger community via threat indicators, thereby strengthening the greater collective’s cybersecurity efforts.