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4 Challenges of Using Anonymous User Data for UEBA

User and entity behavior analytics (UEBA) tools support a cybersecurity strategy by looking for anomalies. These tools establish a baseline usage for users, devices, and networks, then flag cybersecurity teams about significant deviations from those norms. People are highly interested in how user behavior analytics could cut cyberattack risks. One market analysis showed that the UEBA sector was worth $1.2 billion in 2022. However, researchers believe it will get to $4.2 billion by 2026.

However, the push towards anonymizing user data for the sake of privacy could hinder that growth. User and entity behavior analytics work best when decision-makers at the companies using the technology can narrow down potential problems. Anonymous UEBA data would limit the trends it's possible to pinpoint. Here's a closer look at why anonymized information is not a good fit for UEBA platforms.

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What Will AI Bring to the Cybersecurity Space in 2022

Over the last year, artificial intelligence (AI) has become a huge part of our everyday lives, which is something of a mixed bag that has brought along a wide variety of both positive and negative influences. On one hand, there are algorithms that are designed to perform a largely marketing-related series of tasks, which are perhaps those best known to individuals outside of the technical space. Think of the algorithms curating your TikTok feed and personalizing suggestions on YouTube. The AI that calculates your fastest morning commute based on virtual maps, your vehicle, and current traffic conditions is also a fairly visible one that has had its share of media attention.

A particular area, though, in which AI has become crucial is cybersecurity. Cybercriminals are increasingly harnessing AI to automate breaches and crack complex systems. Sophisticated, large-scale social engineering attacks and deep fakes are prime examples of this trend. Perhaps more subtle techniques, such as those involving AI-driven data compression algorithms, will soon become an even more important part of the space in the year to come.

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MTD Myths Vs. Reality: What Leaders Need to Know About Mobile App Risk

Since the advent of the iPhone, security teams have longed for mobile endpoint security that rivals antivirus and antimalware capabilities for PCs. Although Mobile Threat Defense (MTD) has captured attention from regulated industries and government, it doesn’t provide the price/performance value to justify the investment. Mobile app vetting offers a stronger, cost-effective approach to managing mobile risk.

MTD solutions install agents on a mobile device and watch for unusual or malicious behavior at the device, user, or app level. They alert users and the IT security team to take action and may offer additional features depending on the vendor. By contrast, mobile app vetting solutions run in the cloud to assess mobile apps for security, privacy, and compliance issues by dynamically testing the binary on real iOS and Android mobile devices.