When Data Isn’t Keenly Analyzed to Raise it to the Level of Finished Intelligence, it Can Only Answer the Questions an Organization Knows to Ask
It’s no secret that the widespread adoption of automation has revolutionized our modern-day economy. Across countless professions, and industries, machines capable of unprecedented precision and efficiency continue to outperform and replace many of the humans whose inputs were once integral to the workforce. And while these technologies were initially created to overtake simple, repetitive tasks and painstaking physical labor, rapid advancements in the fields of machine learning and artificial intelligence (AI) have, in some cases, wrongfully been determined as suitable replacements even for humans whose roles require keen intuition, skilled social and emotional agility, and unparalleled subject matter expertise.
I’ve witnessed firsthand just how drastically automation can change an industry. At Flashpoint, automation plays a crucial role in our efforts to produce intelligence. Not only does it enable our analysts to spend significantly less time on mundane tasks like routine data collection, it gives them more time to glean intelligence from some of the most exclusive corners of the Deep & Dark Web. Without automation, analysts spend more time digging and less time interpreting information as only human can do, to produce true intelligence. It’s a critical factor in a team’s ability to scale.
But it is not a standalone intelligence product.
To illustrate my point, let’s look at claims of “automated intelligence.” This increasingly popular term refers to the data collected by automated tools from various online sources, and then is packaged as finished intelligence, when it’s merely just a step above threat feeds, and can only be finished when an analyst reviews that automated data for slang, lingo, code words, sarcasm, credibility — all of which require human judgment to assess. More important, understanding the language and culture of these malicious channels is something that only highly skilled analysts can accomplish.
When data isn’t keenly analyzed to raise it to the level of finished intelligence, it can only answer the questions an organization knows to ask. Our job as intelligence professionals is to highlight to organizations their threats and risks, whether they be malicious actors or insiders, so they can ask smarter questions and take faster action. Even the most advanced automated technologies cannot truly mimic the intuition, intelligence, and expertise of humans.
Aside from limiting the analysis and contextualization required to evolve data to intelligence, in many cases, sole automation intelligence or risk analysis solutions can only analyze information from the open web. Although good data, we’re back to it being only data. This data is sent to organizations as intelligence, when in reality, by the time it makes it to the surface web it is an alert, but it is not a finished intelligence product that can help impact the security and bottom line of a business. While important to provide, data automated from the open web should only serve as potential indicators of what may be occurring in the Deep & Dark Web. It’s an indicator of sorts, not an answer.
Regardless of where the data comes from, if it is derived solely from automation, it will never be fully-contextual, finished intelligence. This means the organizations that consume it as such may be doing themselves a disservice but not ascertaining all of the information they need to make smarter, quicker decisions about their security across the enterprise.
