No Detail is Too Small: Is Your Network Behavior Analysis Up to the Task?
A network is very much like an organism. Just as a small cough or a very faint fever could mean that someone may be coming down with something, a very small difference in your network activity could mean that your organization is in the early stages of an attack. But it’s not always possible for people to catch these small details while performing network behavior analysis. A technology solution (i.e., a network intrusion detection systems or a network traffic analytics product), on the other hand, can do a much better job of finding a suspicious needle in your network haystack. If it’s smart enough, that is.
Sweat the Small Stuff
Compared to ten years ago, the average network infrastructure has transformed from a bustling small town to a large, dynamic city. These infrastructures perform like digital ecosystems, with myriad diverse components working (mostly) together.
Unfortunately, this increase in complexity makes it very hard to secure the network. Small, seemingly insignificant changes in the network can indicate far grander threats. Relying on big red flags like malware signatures or known malicious IP addresses is a mistake as bad actors have gotten very good at leveraging network complexity to hide indicators of compromise (IoCs). Advanced malware, for example, can even fragment itself into easy-to-miss bits, and spread across the system undetected, or avoid detection by automatically changing its code so no two files are exactly alike, resulting in unique signatures.
Moreover, attacks may not even involve malware directly. Instead, there may be network intrusions by bad actors who have acquired login credentials. These network intrusions will look, in nearly every respect, like an employee performing their daily tasks. And this can be incredibly difficult to identify even for those who are looking for evidence of suspicious behavior.
To protect your network, you need to be able to spot small changes that may initially seem benign, and you need to be able to connect the dots – the seemingly disparate anomalies, each of which appears benign – in order to see the sum of these parts that add up to a malicious threat. Network intrusion detection systems collect incredibly detailed information from the entire network and, using known details about malicious behaviors, recognize when events are in fact pieces of a coordinated attack. Not only will this lead to catching more threats, but it also reduces the chances of false positives and technician fatigue.
What Should Network Intrusion Detection Systems Scan?
An advanced solution for network traffic analytics will identify a number of differences throughout the system, many of which a human technician wouldn’t be able to see. Using pattern recognition and AI-powered analysis, the network intrusion system can learn over time what the network’s regular activity looks like. Once it has a clear picture of how the network typically operates, it is able to detect anomalies. Combining these with known malicious behavior details, the system can detect the following with minimal false positives:
- Reputation Information. A network activity monitor will be able to identify when bad domains, URLs, or IPs are being used throughout the network, which could indicate that the network has been breached. Advanced activity monitors have in-depth, current databases that are able to track this information.
- Protocol Anomalies. A network behavior solution can detect protocol anomalies including DNS tunneling and DNS zone transfers, which could be redirecting employees or data to other areas of the web. When DNS is compromised, data can be captured easily – and without notice.
- Traffic Anomalies. Advanced network traffic analytics can identify unusual traffic throughout the network, which could include cryptocurrency mining activity, remote file execution, or port scanning. Traffic anomalies can indicate large threats that don’t have any hallmarks of known threats, such as an advanced, undetectable exploit that is attempting to exfiltrate large volumes of information.
- Host Anomalies. A network solution can identify more subtle issues, such as unusual traffic volumes, logins from strange places, and periodic check-ins that could indicate a cybercriminal testing out login credentials. If social engineering results in a cybercriminal compromising login information, a host anomaly will show the individual logging in from a different IP.
All of the above could be serious signs that the network itself has been breached, and none of them are likely to be caught during routine security checks.
As I hope is now clear, solutions that provide network traffic analysis need to identify a very large number of threats. But it isn’t enough to be broad in scale; the network monitoring application also needs to be deep. Modern organizations aren’t connecting only their own internal devices to their network; they’re also using remote desktops, laptops, tablets, and smartphones. Security must encompass every endpoint that connects to the network, which may also include a number of IoT and mobile devices that potentially haven’t been secured.
It’s time for your organization to protect itself from these growing threats. To do so, you need a next-generation system that can learn from and protect your network, incorporating every detail – no matter how small – into its analysis to ensure advanced threats are detected with minimal false positives that waste time and energy.
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