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Zscaler Recognized as Leader in 2023 GigaOm Radar for Deception Technology

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Attacker tactics are ever-evolving, and unless detection methods evolve with them, your organization could be at risk. This conundrum is addressed head-on by deception technology (DT), which enables defenders to construct traps for attackers and collect useful data for better decision making. Zscaler has been recognized as a leader among all vendors evaluated in the 2023 GigaOm Radar for Deception Technology Solutions. The comprehensive industry report asserts that deception technology vendors are developing advanced platforms that can detect, analyze, and defend against zero-day and advanced attacks early with low rates of false positives.

In the report, you will learn when you begin to examine the deception technology vendor landscape and solutions in this market, there are specifics to each company's application of the technology. These distinctions give this market the breadth necessary for practically any size business to choose a solution that meets its requirements. There are various methods for integrating and utilizing DT in a contemporary organization. Some businesses may decide to work with a vendor to manage the solution because they value simplicity and effectiveness equally, while others may opt for autonomy in their deception solution to boost the productivity of their current team.

The vendor solutions that are plotted by the GigaOm Radar are distributed among a set of concentric rings, with those that are closer to the center having a higher overall value. According to the placement of Zscaler in Figure 1, it’s a feature-rich solution and a well-designed product that has a good mix between platform play, innovation, and maturity. The research claims that Zscaler Deception successfully blends state-of-art deception technology and implements all defined key criteria to offer a comprehensive range of security services resulting in a powerful and harmonious solution. The solution offers a wide array of features combined with a broader platform, features that aren’t typically available from a single vendor.

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Figure 1

Zscaler Deception earned this leading position by providing crucial capabilities including actionable insights which turn data into useful information for security and IT teams. Zscaler creates a risk-based score metric for each event. When multiple events are correlated, the risk score grows exponentially. Its seamless integration with other Zscaler products makes it an integral part of the risk assessment process. GigaOm notes that “The platform’s threat intelligence sources stand out. They comprise internet-based sensors that are capable of detecting targeted attacks aimed specifically at your organization and the Zscaler global cloud furnishes data on an impressive 280 billion transactions daily.” 

The GigaOm report states that “Zscaler blends state-of-art deception technology with a comprehensive range of services resulting in a powerful and harmonious solution. It is a meticulously crafted solution with a wide range of features when combined with the broader platform, features that are not typically available from a single vendor”.

Zscaler Deception is used to detect compromised users, identity-based attacks, stop lateral movement, and defend against human-operated ransomware, hands-on keyboard threats, supply chain attacks, and malicious insiders. The solution covers the environment with decoys and fake attack paths to derail active threats without adding operational overhead or false positives. Zscaler Deception reduces detect/response time, generates private threat intelligence, and boosts SOC efficiency with high-fidelity alerts. Read more about how Zscaler Deception can be used to respond to security events faster, in a more coordinated manner, and reduce reliance on overburdened security and SOC response teams.

To better understand how improving Deception Technology in threat detection, analysis, and response can improve your security posture, download the 2023 GigaOm Radar for Deception Technology report.

 

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