ProtectWise Expands Capabilities Of Enterprise Security Platform With Next Generation, Deep File Analysis Solution

DENVER, Feb. 17, 2016 /PRNewswire/ -- ProtectWise, provider of the industry's first Cloud Network DVR for complete detection, visibility and response to enterprise threats, today announced the availability of ProtectWise™ File DVR, a powerful new approach to file analysis. Current file analysis solutions rely on blacklisting and whitelisting to identify malicious files, but struggle to keep pace with today's continually evolving threats. ProtectWise File DVR applies artificial intelligence, machine learning and data science capabilities to analyze the characteristics of suspicious files, in real-time and retrospectively, and as a result expedites forensic investigations and incident response.

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The ProtectWise File DVR leverages the automated, continuous real-time and retrospective threat detection of full fidelity network traffic of the ProtectWise Cloud Network DVR and applies it to files. Using its latest threat intelligence and knowledge of new developments in the threat landscape, ProtectWise can discover malicious files that may have been previously unknown by analyzing historic file metadata automatically. This 'look back' capability reduces the dwell time of file-related threats on the network.

"We built our Cloud Network DVR as a way for organizations to store full fidelity network data, creating an accurate representation of the actors, applications and network traffic flowing across all network segments," said Ramon Peypoch, chief product officer at ProtectWise. "ProtectWise File DVR taps into that value provided by our Cloud Network DVR, and discovers malicious files that may have been previously unknown by analyzing historic file metadata automatically. As a result, security teams are freed up to focus on other, more critical projects."

Additional features of ProtectWise File DVR include:

• Complementary existing sandbox investments. It provides a full set of indicators of compromise (IOCs) and the option to integrate with sandboxing tools. 
• Instantaneous deployment. As part of the extensible ProtectWise Enterprise Security Platform, File DVR is delivered as a value-added service. There is no new hardware or software to deploy, but simply requires turning the service on from within ProtectWise's Visualizer.
• Fast, intuitive search. Search your network haystack back three or six months to quickly determine if a file has previously been seen on the network.

ProtectWise File DVR relies on the latest threat intelligence and knowledge of new developments in the threat landscape to enable incident response teams to quickly identify, investigate and respond to malicious files. Learn more about ProtectWise File DVR by visiting the ProtectWise website.

About ProtectWise

ProtectWise™ is disrupting the network security industry with its Cloud Network DVR, a virtual camera in the cloud that records everything on the network. The service allows security professionals to see threats in real time and continuously goes back in time to discover previously unknown threats automatically. By harnessing the power of the cloud, ProtectWise provides an integrated solution with complete detection and visibility of enterprise threats and accelerated incident response. The Cloud Network DVR delivers unique advantages over current network security solutions, including an unlimited retention window with full-fidelity forensic capacity, the industry's only automated smart retrospection, advanced security visualization, and the ease and cost-savings of an on-demand deployment model. 

Founded in April 2013, the company is based in Denver and led by a team of security and SaaS industry veterans from McAfee, IBM, Mandiant and Proofpoint. ProtectWise has raised more than $37 million in funding and was named to Network World's list of "10 Security Start-Ups to Watch." For more information, visit www.protectwise.com.

Contact: Tracey Workman, [email protected]

SOURCE ProtectWise

Related Links

https://www.protectwise.com