Multiple types of cybersecurity solutions are necessary to defeat sophisticated criminals, but there’s a significant drawback with many conventional security tools. Often, these tools are on the lookout for anomalous activity in user behavior or network traffic, which creates the basis for an infinite set of anomalies. This means the alerts they produce are based on probability, creating many thousands of “maybe” alerts that must be investigated before they can be classified as an attack requiring a response.
Deception technology comes at the problem differently. A deception solution also looks for anomalies, but instead of infinite possibilities, they are reduced to “yes” or “no.” A malicious actor has either engaged with deception or has not. In this equation, there are no “maybes.” A “yes” alert brings with it highly useful, real-time data, including which deception was tripped, where and precisely when.
As organizations realize what this technology can do to stop criminals who have already breached their perimeter, they are looking at deception-based solutions as alternatives. In this eWEEK Data Points article, Ofer Israeli, CEO and founder of Illusive Networks, discusses the persistent myths about deception technology that must be dispelled in order for more organizations to feel comfortable and confident with this solution.
eWEEK Editor in Chief Chris Preimesberger recently recorded an eSPEAKS interview Mr. Israeli. You can view it here.
Data Point Myth No. 1: Deception is hard.
Today’s deception technology is stunningly easy to implement, operate and manage. It automatically generates multiple deceptions tailored to each endpoint that look like the genuine article to attackers but that alert defenders to their presence as soon as they engage with the fake objects. They’re such good fakes that they fool even the most experienced attackers—but they don’t require the drawn-out agent deployment and baseline tweaking of most anomaly-based solutions.
Data Point Myth No. 2: Deception is only for big, mature enterprises.
Quite the contrary; deception is particularly helpful for smaller organizations that lack the staff and budget to use more complex tools. These smaller security teams benefit from the improved visibility that deception technology brings and are gaining confidence in their ability to protect their internal attack surface. Smaller companies that wouldn’t require a full SOC can easily benefit from the deterministic alerts produced by a deception solution. In fact, some of the most successful deception deployments have been at small businesses that had to quickly get their security posture up to speed.
Myth No. 3: Deception is good for threat intelligence but not detection.
Honeypots were the original form of deception, and they trapped invaders to study their late-stage attack behaviors. Today’s endpoint deceptions are quite different; they are lures placed where attackers will find them early on in the attack process. The minute an attacker interacts with a lure, the system sends out a high-fidelity notification that shows precisely what happened and where. Modern deception technology has actually become the earliest and most effective way to detect and stop attackers.
Myth No. 4: Deception should be the last thing you implement.
There’s no reason for deception technology to be your cybersecurity “Hail Mary.” Standard anomaly detection tools need a big budget and a highly trained security team, but deception is not like that. Deception is the easiest way to see the most dangerous threats without having to wade through countless false positives and a long implementation phase. The proof is in the red team success—if you can be beaten by a red team, then you have a clear security gap. Remember, if a red team can get in, an attacker can too. Deception technology is proven to beat red teams definitively, so the risk threshold is essentially non-existent. That’s why it shouldn’t be last on the list but part of a comprehensive security strategy from the start.
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