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Trend Micro Launches XGen For Multi-Layered Endpoint Protection

Security giant Trend Micro has launched XGen, a new approach to endpoint security blending multiple layers of threat protection, in a bid to head off what it claims are the over-hyped claims of rivals with narrower feature sets.

XGen is not a product in its own right but instead references a “cross-generational” mix of threat defense techniques combining everything from signature-based protection up to advanced machine learning.

Trend Micro claimed this new approach was necessary in order to effectively combat the huge volume and wide variety of attacks facing organizations today.

Its Smart Protection Network now blocks half a million such threats each day – including ransomware, phishing, advanced targeted attacks, mobile malware and more.

Each new category of threat requires a purpose-built technique to combat, the firm said.

However, many self-titled ‘next generation’ endpoint security vendors today make over-hyped claims for their products, promising that machine learning or sandboxing, for example, can provide effective protection across all threats, Trend Micro argued.

“There are many new ‘next-gen’ endpoint players that claim to be the shiny silver bullet to resolve your endpoint security problems,” Trend Micro cybersecurity consultant, Bharat Mistry, told Infosecurity.

“However, these vendors only focus on one type of protection technique. And we know from industry experts and analyst firms like Gartner that multiple blended techniques are needed in conjunction with established and tested processes and procedures, coupled with user awareness and training to promote safe online habits.”

As part of the XGen announcement, Trend Micro unveiled new ‘high fidelity’ machine learning technology designed to catch any threats that slip through signature- and behavior-based security filters.

It works by extracting a file’s features and applying algorithms to determine whether that file is malicious.

Crucially, it extracts and analyzes those characteristics both before and during the file’s execution which – in concert with census and whitelist checking – improves accuracy and reduces the chance of false positives.

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