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SAS® for Cybersecurity

Fast detection of cyberthreats through big data analytics

Protect your data and network from both insider and outsider threats. Quickly detect potentially malicious activity hidden in massive volumes of data. SAS for Cybersecurity arms you with sophisticated analytics that enable you to take a proactive, targeted approach to identifying and countering cyberthreats – before the damage is done.


Gain true situational awareness.

See the full scope of cyberevents – from entry into the network environment to data access over extended periods of time. With SAS, you can bring together all relevant data – from network monitoring devices, policy compliance and event logs, and other internal and external sources – for a holistic view that provides true situational awareness.

Safeguard systems and information.

Identify possible threats and predict future attacks far enough in advance to forestall cyberattacks. We combine network behavior analysis with traditional threat intelligence and other detection techniques to identify more suspicious cyberactivities than any one method alone. By recognizing potential threats sooner, you can take action to prevent data loss and system breaches.

Monitor huge data volumes – in near-real time and over time.

Detect hostile activity anywhere on your network with near-real-time monitoring of massive amounts of data. Powerful analytic techniques can reveal anomalies and connections that would otherwise be missed. You can uncover hidden relationships and identify subtle patterns of behavior that may indicate zero-day and advanced persistent threats (APT), such as low-and-slow attacks, which are much harder to detect because they happen over time.

Stay on top of changing cybersecurity trends – and adversaries.

A self-learning feedback loop keeps your analytic models up-to-date with tactics, techniques and procedures (TTP) that change often to evade detection. The models evolve continuously throughout the analytic life cycle, ensuring that as your adversaries get more sophisticated, so do your detection methods.

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  • Data management. Aggregate, correlate and merge data from all network monitoring devices.
  • Big data analytics. A variety of high-performance analytic methods – including grid, appliance, in-database, in-memory and cloud based analytics – provide the fastest, most reliable insights for complex problems. 
  • Hybrid analytic approach. Multiple analytic techniques are used to detect more complex scenarios and signals buried in massive amounts of data.
  • Visual analytics. Visually explore all your data, no matter the size of your organization – or your data.
  • Alert management and reporting. Alerts are scored and automatically routed for investigation to ensure that investigative resources work on the highest priority alerts. Multiple reporting options (Web portals, email, etc.) are available to meet a variety of needs.
  • Case management. Alerts and other results can be fed into existing case management systems or into SAS Enterprise Case Management.

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