Network anomaly detection is an analytical technique for identifying and stopping cyberattacks before your data has been compromised. Since it’s getting harder and harder to stop the network breaches, your best option is to catch the hackers before they can do any harm.
But let’s back up.
The list of major organizations struck by cybercrime in the last year alone is astounding. When you stop to think about how many reputable organizations have had their networks breached recently, it becomes clear that even our best methods for preventing cyberattacks aren’t working.
The computer networks at most large organizations are so big and so wide reaching, it’s becoming harder and harder to put up walls to keep the cybercriminals out. There are just too many possible points of entry.
How to identify hackers with network anomaly detection
So what can you do? If stronger firewalls aren’t enough, should you simply raise your hands in resignation and admit that dealing with cybercrime is the price we pay in a modern, data-filled world?
Of course not. But you should admit that preventive methods aren’t enough, and start making plans now for catching the hackers once they’re inside your networks.
In fact, you have to assume they have already breached your network. This isn’t hyperbole, and it’s not meant to scare you. It’s simply true. But here’s the good news: It can work to your advantage to know they are in there.
So what does a network breach look like? Well, it’s hard to see because it can happen slowly and steadily over a period of months as the hackers are learning their way around your network and making steady progress to infiltrate deeper into your systems where the most secure data lives.
In fact, many of the compromises you’ve heard about in the news involved hackers who were in the network for months before being detected. You can think of the first few months of activity as a quiet, fact-finding mission.
We describe this as low-and-slow reconnaissance activity because the hackers are working so quietly and methodically that their movements inside your network often go undetected. The only way to know it’s happening is to have a system in place that tracks normal network behavior and compares it to current activity, searching continuously for new and unusual patterns. This is network anomaly detection.
Why analytics are key for network anomaly detection
Here’s the challenge, though: The computer networks of most large organizations are processing hundreds of thousands of events per second during normal business hours. It’s not unusual to see tens of billions of machine-to-machine records daily on an average network. Monitoring that activity, processing it in flight and identifying unusual patterns takes a lot of analytical power.
Network anomaly detection can do that and more. The method uses event stream processing to understand network activity within the appropriate business context. In other words, the system learns what abnormal activity looks like in your networks. For example, it might mean a series of IP addresses that are never active at night suddenly are. Or it might mean computers from the sales department that never transmit information to the HR organization suddenly are. These types of behaviors could be happening in the background without you ever knowing.