Prevent, Detect, and Mitigate Novel Threats with Advanced NDR Solutions
Modern data threats are evolving.
Employing increasingly sophisticated techniques, malicious actors are becoming ever more proficient at gaining access and remaining undetected in networks belonging to businesses across every industry. IBM reports that in 2022 it took an average of 277 days to identify and contain a data breach. As such, defending critical networks in the modern world has become an issue of visibility as much as defense. And when you consider that networks themselves are also constantly growing and changing, it creates a situation in which IT security operations centers (SOC) face a nearly limitless range of threats, targeting a constantly-shifting attack surface.
Still, the truth is that many of the most devastating breaches that crowd today’s headlines could have been prevented. When network data is too valuable to risk, top businesses rely on network detection and response solutions.
What Is Network Detection and Response?
Network detection and response (or NDR) is a type of network security tool that applies machine learning and big-data analytics to provide a complete view of every interaction occurring on a network. These solutions can then better understand and diagnose any anomalous behavior while also recognizing the patterns associated with such behaviors to help optimize the identification of and response to possible future intrusions.
In other words, NDR places your network under a microscope, allowing you to more closely monitor the IT systems that keep your organization in business. Of course, how NDR performs these functions warrants a little more explanation.
How Does NDR Work?
As previously addressed, modern network security relies heavily on unobstructed visibility into network traffic. Unfortunately, that’s a fairly large mandate. North-south (into and out of private networks) and east-west (within private networks) traffic must all be closely monitored to ensure network integrity. And this is the basis of what makes NDR so effective.
NDR sensors within the network collect and inspect every packet, allowing for not only near-perfect data visibility, but also enhanced data analytics. Likewise, by applying artificial-intelligence and machine-learning solutions, NDR tools can learn and improve, modeling malicious tactics and correlating patterns and events over time. This makes it possible to detect threats with unmatched speed and accuracy. And once threats are detected, top NDR solutions can then respond using built-in security capabilities or through seamless integration with other trusted security tools.
NDR gives SOC analysts and security teams the insights and visibility they need to better understand their current security posture, the potential threats facing their networks, and any suspicious connections that might occur.
What Are the Benefits of NDR?
For as long as cybersecurity has existed, it has traditionally been built around a cause-and-effect approach to network protection. The cause (damage caused by a network breach) sets off alerts within the system, leading to the effect (the security analyst initiates the incident response process). But there’s a major flaw in this approach. Namely, once the incident response occurs, it’s already too late. The network has already been breached, and the threat actor (whether a living person or an automated program) may have already done untold damage to the network or its data.
At the same time, many of these legacy security tools rely heavily on signature-based detection. This means that if the specific attack methodology being employed hasn’t before been encountered (such as with zero-day exploits and new variations on existing attacks), then the attack may fly completely under the radar and go unaddressed for days, months, or longer. And the number of days it takes to contain a breach can mean a difference of millions of dollars in terms of costs and lost revenue.
With so much at stake, playing catch up with cyber criminals is no longer a viable option. NDR employs the latest in threat detection capabilities, evaluating and correctly categorizing the earliest and most obscure signs of a data breach to intelligently identify issues before they can turn into problems. And by learning as it goes, NDR can also recognize novel threats that would never register with signature-based detection systems.
What to Look for in NDR Solutions
Given the many advantages of NDR, it’s little surprise that businesses are seeing a surge in available NDR solutions. In fact, the NDR market was valued at ~$2.24 billion in 2021 and is expected to reach $4.60 billion by 2026. With so many NDR options to choose from, it can be difficult to know what separates the best-in-class NDR solutions from the rest.
When considering an NDR solution, the most important features to keep in mind are as follows:
- Contextual Network Visibility
At the heart of NDR is visibility. Without total transparency into your networks, your organization will not have the data and context it needs to effectively identify and address possible threats in real-time. Contextual, network-wide visibility is visibility into every aspect of your on-premises, cloud-based, or hybrid networks, including entities, devices, and traffic flowing into, out of, and laterally throughout your system. NDR solutions depend on this kind of visibility, making it perhaps the single most important element of NDR.
- Behavioral, Non-Signature Detection
When security tools can only address the kinds of attacks they’ve experienced before, they are completely at the mercy of anything new. Signature-based attacks offer poor protection against novel threats, which is why behavioral detection in NDR is absolutely vital.
- Accelerated Threat Response
With full visibility, advanced analytical capabilities, and behavior detection in place, NDR tools are in a unique position to address potential data breaches more proactively than any other type of security tool on the market. The top NDR solutions take things even further, by allowing teams to automate response solutions and automatically prioritize alerts based on the levels of risk they represent. This means faster time to remediation and a significantly decreased chance of suffering major damages as a result of a data breach.