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Real-Time Detection & Remediation of Encrypted Cyber-attacks - Without Decryption

Real-Time Detection & Remediation of Encrypted Cyber-attacks - Without Decryption

Barac’s unique security technology, uses AI, Machine Learning and behavioural analytics, to locate and stop cyber-attacks hidden in encrypted traffic in real-time, without having to decrypt. We can send alerts to SIEM or SOC, and are integrated with QRadar, Splunk & Arcsight. Easy to deploy and manage, Public or Private Cloud, SAAS, or physical or virtual server. We detect attacks and abnormalities in (milliseconds) across the whole IT infrastructure of a business, with 99% accuracy and reduce false positives by more than 95%. Barac’s ETV can help protect against the increased risks of cyber-attacks resulting from the deployment of TLS 1.3, which does not allow you to decrypt and test for malware. Our approach has received widespread industry recognition. we were invited to join GCHQ’s prestigious Cyber Accelerator programme. Run by GCHQ’s National Cyber Security Centre, provides support to companies that GCHQ considers ground breaking in improving the UK’s cyber security In a recent global survey of 500 CIOs conducted by Vanson Bourne on behalf of security vendor Venafi, 90 percent said they already have experienced or expect to experience, a network attack using SSL/TLS. About 86 percent expressed concern about stolen digital certificates and encryption keys becoming a big market for cybercriminals in the next few years while 87 percent believed their defenses were less effective because of the trend by criminals to use encryption to hide attacks. Barac gives organization the ability to collect and analyse encrypted data using complex behavioural analytics in real time, to spot attacks on encrypted traffic and detect abnormal activities. We detect attacks and abnormalities in (milliseconds) across the whole IT infrastructure of a business, with 99% accuracy and reduce false positives by more than 95%.

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Webinar Details

30th April from 12:00 PM - 1:00 PM

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