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Deception-Based Breach-Detection Software Keeps Hackers Guessing

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Unlike traditional signature-based detection or vulnerable machine learning, deception technologies reduce false positive alerts and are manageable from a centralized console.

By populating networks with fake assets, deception puts the burden of success on attackers. To succeed, they must carry out a flawless attack without falling for a single decoy, misdirection, or trap.

Empowering Proactive Defense with Deception Technology

Eliminate False Positives

False positives cripple security team productivity and can drag IT and CISOs through convoluted triage workflows, wasting valuable time that could be better spent engaging attackers and detecting breaches. According to one study, businesses lose $1.3 trillion annually due to false alarms. Deception-based breach software eliminates false positives by changing the game for adversaries. Cyberattackers can be detected and engaged by populating the network with unique breadcrumbs and decoys that mimic IT and IoT assets.

Unlike traditional security solutions that rely on signatures and susceptible machine learning algorithms, deception technologies don’t throw out a flood of alerts. Instead, they raise the threshold on malicious events, so attackers are triggered by their actions and forced to interact with deception targets to continue the attack.

This approach provides a low signal-to-noise ratio for day-to-day operations, which reduces the likelihood of triggering legitimate security events and alert fatigue. It also ensures that defenders can track and respond to alerts quickly and accurately, ensuring they aren’t wasted on noise.

A good deception solution will automatically enrich a high-confidence alert with context. It should also be able to map an attack’s previous activities on the target and assemble detailed forensic information for rapid remediation.

Detect Malicious Activity Immediately

Deception technology deploys many realistic-but-fake assets (domains, databases, servers, applications, files, credentials, and cookies) throughout the network alongside legitimate ones. The system triggers a silent alarm when an attacker tries to access one of these false assets. This alert, combined with the detailed IOCs produced by each decoy, gives analysts critical intelligence to stop attacks and respond quickly.

When compared to point solutions that typically detect a single threat artifact, deception offers far greater visibility into the entire kill chain – from reconnaissance through privilege escalation, lateral movement, and data theft. This visibility helps reduce detection time, which decreases the attacker’s dwell time on your systems.

In addition to reducing the number of false positives, deception can qualify medium-risk alerts that other security tools would have otherwise ignored. This is a standard attack technique hackers use to gain privileged access.
Additionally, deception can mimic key elements within healthcare-specific environments.

Save Your Analyst’s Time

Deception platforms can detect threats at every step of the kill chain, from survey through lateral movement and data theft. By populating your environment with fake endpoints, servers, databases, files, and users, you can trigger a response when attackers interact with any of them. This provides valuable attack intelligence, stops lateral movement, and allows security analysts to leverage automated remediation.
Existing detection technologies are often overwhelmed by noise and need help accurately detecting sophisticated attacks. They use static signatures and heuristics that are quickly outdated and can trigger false positive alerts. They are also prone to blind spots in the network, including cloud environments, SCADA/ICS, and IoT.

By contrast, deception uses a proactive and low-false positive detection model. It does not rely on static signatures and heuristics, so it is highly effective at detecting new or unknown threats. It also only produces a few false positives, so you can spend more time investigating real threats.

Deception can complement security orchestration, automation, and response (SOAR) tools by provoking and analyzing bad actors in real time. This can reduce the time it takes to identify and respond to a threat, helping to prevent attackers from stealing your sensitive data.

Generate Detailed Attack Intelligence

Deception can distract attackers from the actual targets by deploying deceptive systems, files, credentials, and services throughout the network that mimic real assets. Attempts to interact with these bogus resources are suspicious at best and malicious at worst, which triggers alerts that can be acted upon immediately. Deception technologies also generate threat intelligence about the tools, tactics, and procedures that attackers use to identify weaknesses in existing defenses and gain access.

The combination of these capabilities can significantly close gaps in detection by reducing the mean time to detect (MTTD) and dwell time and providing visibility into exposed attack paths. This enables security teams to identify and engage attackers quickly and effectively without disrupting normal operations or compromising future protections.

Unlike traditional monitoring solutions that send many alerts, most of which are false positives, deception technology can detect attackers in progress and deliver actionable threat intelligence to the security team. This helps analysts reduce the work they need to do, allowing them to spend more time on high-risk threats.

There are several ways to leverage deception-based breach detection, ranging from low interaction traps that only engage specific threats to a full range of attack surface decoys, including deceitful assets that imitate real servers, networks, applications, and IoT devices. These tools can be deployed and managed at scale, across thousands of endpoints, from a central management console.

Also Read: Scope of Artificial Intelligence and Machine Learning

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