I was recently invited to discuss context-rich and context-aware security solutions with a group at the Department of Defense. I wanted to be crystal clear, so I started with the definition from the Gartner IT Glossary:

Context-aware security is the use of supplemental information to improve security decisions at the time they are made, resulting in more accurate security decisions capable of supporting dynamic business and IT environments.

The most commonly cited context information types are environmental (such as location and time). However, context information valuable to information security exists throughout the IT stack, including IP, device, URL, and application reputation; business value context; and the threat context in which the decision is made.

I took this as an opportunity to raise the awareness of what is needed to improve our nation’s cybersecurity efficacy and efficiency: the leverage of connected architectures, threat-intelligence data, orchestration, and automation.

More to the point, timely protection and response in the face of advanced targeted attacks are major challenges for security teams across every sector. Most organizations rely on a multivendor, siloed security infrastructure, where products do not communicate with one another. A shortage of trained security staff and a lack of automated processes result in inefficiencies and protection gaps. Existing security infrastructures typically do not have any integration between the inspection, intelligence gathering, analytics, and enforcement components. These form the technology underpinnings of cybersecurity best practices known as the detect, protect, and correct process of incident response

Integration Advantage 

Integration improves effectiveness. The active sharing of data and accelerated cross-control processes makes it possible for each security control to leverage the strengths and experiences of the other security tools. An adaptive threat-prevention model is quickly replacing traditional, unintegrated architectures as security teams work to achieve a sustainable advantage against complex threats. Instead of treating each malware interaction as a standalone event, adaptive threat prevention integrates processes and data through an efficient messaging layer. This approach reinforces levels of inspection and analysis, which are informed by expanded forms of intelligence. It also connects end-to-end components to generate and consume as much actionable intelligence as possible from each contact and process. 

The shift to adaptive threat prevention helps overcome the all-too-common functional fences that impede detection, response, and any chance of improved prevention. Silos of data and point products complicate operations and increase risk. For example, the information each security control generates and the context of each situation are poorly captured and seldom shared within an organization, let alone among a larger community of trust. A firewall may block a payload coming from an untrusted domain because it knows about communications, not malware. It will permit the same payload if it comes through a trusted domain. Similarly, anti-malware could block unknown payloads received from known bad addresses if it is enabled to look within the payload to examine IP addresses. 

Unintegrated security functions like these keep organizations in firefighting mode, always reacting and pouring human resources into every breach. Process inefficiency exhausts scarce investigative resources and lengthens the timeline during which data and networks are exposed to determined attackers. The length of time from breach to detection has a direct correlation to the extent of damage. These islands of security products, data sets, and operations provide sophisticated attackers with ample space and white noise that they can use to their advantage while their malicious code enters, hides, and persists within and throughout an organization. Without context, actions and events have no meaning.