The answer comes in the form of predictive security measures. These practices can help anyone from regular people to major corporations protect sensitive data, information and images from falling into the wrong hands. As bad actors become more sophisticated, numerous improvements have been made to security apps, programs and software to thwart their nefarious attempts. Despite that, the hackers sometimes manage to gain the upper hand.
News travels fast and businesses around the world are paying close attention to the scandals and adopting predictive security measures to prevent themselves from making tomorrow’s headlines. As one expert explains, there are two key reasons why predictive security is on the rise.
“The first and most obvious (reason) is the way that companies are going about this today just isn’t working,” explains Dr. Andy Jennings, chief analytics officer for FICO. “We read a lot about increasing number of data breaches and increasing magnitudes of data breaches. It’s not just the number of them; it’s the time lag between when a compromise might occur, and when it actually gets discovered.”
The second reason, says Jennings, revolves around the evolution of the technology and analytics that assist with breach prevention and network traffic analysis.
“Technology is now advanced such that the analytic technology exists to be able to look at network traffic in close to real time, understand where anomalies are occurring and have models that can adapt in real time to changing patterns that are occurring within a network,” he says.
Jennings likens this to credit card fraud, another area that FICO has explored over the years.
“What we’re doing at FICO is basically extending the idea that those ideas that we created over the years with credit card and transaction fraud detection are very similar,” he says. “You’ve got lots of transactions coming in, and you’re trying to figure out which one amongst millions in aggregate or any one for a particular consumer might be a problem. If you extend that analogy to network traffic, you’ve got lots of computers that are communicating with one another inside or outside of the network, and you can model that to see if any one of them looks to be anomalous.”
Predictive security practices, if deployed properly, can help to thwart the actions of hackers. As these practices continue to progress, they will allow enterprises to take an automated approach to breach prevention.
“It will enable companies to automate the response to the breach,” says Jennings. “If you think about it today, companies write rules in order to try and figure out if there is something anomalous (on their network). They’re thinking of moving the rules to not try and decide what’s anomalous, but using the rules to then try and bring back some remediation.”
Analytics and big data have become crucial components of predictive security techniques. They help businesses get to the heart of the matter quickly so that the problems can be resolved in due course. To illustrate this, Jennings likened these elements to the ways in which vehicular engines stream usage data.
“They promote efficiency, faster discovery and faster remediation of situations,” he says. “If you think about jet engines, for example, they are streaming data to the ground all the time (while in flight). The engine in your car has the potential to stream data about its functions. In that sort of context, one can be much more efficient and observe what’s going on in the moment as opposed to waiting for after the event (occurs).”
Unstructured data, which includes social media posts, emails and phone conversations are another area of focus for hackers. This data type was exploited in the many hacking scandals that occurred in 2014, most notably the Sony email breach. As a result, Jennings believes that now is the time to implement a proper analysis of this type of data and shift it to a more structured format.
“Unstructured data has been around for a long time, and the majority of data in the world is unstructured,” he explains. “It’s not as easy to manipulate and the technology has now gotten to the point where we can process that information quickly enough to be able to structure it.
“The trick is that unstructured data generally needs to be structured in order for it to be put into models or to be able to report on it and create dashboards,” continues Jennings. “The technology has now progressed to the point where we can do that quickly enough so that the information that is locked up in the unstructured data can add enough value to what we know from the structured world that we’re used to living in.”
Going forward, it’s expected that more enterprises will adopt predictive security practices to keep their sensitive material under wraps. The hackers of today may be smart and sophisticated with their methods –but it’s still very possible for businesses to stay two steps ahead of their digital adversaries.
“We’re going to see more and more predictive applied (by companies). Hacking is a good, organized business and people make money from it, so it’s not suddenly going to stop,” Jennings says. “We need more effective ways of combating data breaches, and predictive analytics would appear to be way in which the industry needs to move forward.
“What we’re also going to see is more of a convergence of security and detection,” he adds. “The techniques that have been applied to the detection world are going to migrate into the security world, and the types of platforms, software tools, analytics and techniques that companies deploy are going to merge over the coming years.”
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