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Modernize your information management with certified experts
Unlock the full potential of your information management solution
Turn support into your strategic advantage
Extend IT teams with certified OpenText application experts
Discover training options to help users of all skill levels effectively adopt and use OpenText products
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Cyberbit uses behavioral analysis to detect and respond to threats
Analyze large volumes of endpoint data to detect indications of cyber-attacks.
Using big data, behavioral analysis, and machine learning to detect cyber threats that bypass conventional security systems. The organization’s endpoints (workstations and servers) are the primary gateways for cyber attackers into the company network, where they access restricted, sensitive data. Conventional antivirus systems are no longer effective for endpoint protection, because they detect threats by comparing them to known virus databases or signature lists.
However, today’s (zero-day) attacks are far more advanced. They do not appear on signature lists or in virus databases and often bypass conventional security systems. Sensitive organizations such as financial institutions, large enterprises, and governments are continuously targeted by sophisticated cyber attackers and require an alternative approach.
Effective endpoint security including detection of unknown zero day threats requires collecting massive volumes of events and rapid processing using multiple cybersecurity behavioral algorithms.
Cyberbit, a global provider of cybersecurity products, developed the Cyberbit Endpoint Detection and Response (EDR), an advanced endpoint security solution, which uses behavioral analysis to detect and respond to threats that go undetected by conventional systems. Rather than using signatures to inspect files and processes, Cyberbit’s EDR uses behavioral analysis algorithms to examine events collected from endpoints across the entire network, identify malicious behavior, and alert the security teams, allowing them to respond to the attack or investigate it further.
To provide effective detection, Cyberbit’s EDR continuously records events from the organization’s endpoints. Such events include: reading and writing to the registry, file access and enumeration, loading of processes and DLLs, and more. This data is collected across the entire network and sent to a central Analytics Platform, where behavioral analysis algorithms identify clusters of related events that indicate an attack. Machine learning algorithms are used to differentiate between malicious and benign behaviors.
These algorithms adapt themselves to the customer’s environment, resulting in highly effective detection.
Vertica’s (now OpenText) performance and speed provided the ideal big data platform for our EDR platform’s needs.
With gigabytes of data recorded every minute, a highly efficient ETL process – extracting, transforming, and loading data – is critical for effective threat detection. The Analytics solution provides Cyberbit with near real-time data insertion at the scale of hundreds of thousands of endpoints, resulting in enterprise-grade threat detection quality.
OpenText (formerly Vertica) Analytics provides several capabilities that make it an optimal cybersecurity big data platform:
Cyberbit’s EDR is used by large, highly targeted organizations. Cyberbit therefore required credible, robust, and scalable big data technology that will be trusted by its customers, which include governments, financial institutions, utility providers, and telecom operators. The OpenText (formerly Vertica) brand was an asset in this respect, while the robust system supported Cyberbit’s large-scale deployments across hundreds of thousands of endpoints.
Created to protect the most high-risk organizations in the world, Cyberbit secures enterprises and critical infrastructure against advanced cyber threats.