Cyber Security

SQream Technologies delivers a high-performing Next Generation GPU-powered analytics database that quickly relieves Big Data and complex Analytics pains. With minimum cost, hardware and infrastructure changes, SQream enables entities to easily ingest, store and analyze heavy analytical workloads in near real-time. Instead of querying one week or one month back, the company gives its users the ability to query years back, at a much higher speed.

SQream DB can be used as an analytical database or as an accelerator to an existing data warehouse to accelerate reports and analytics.

SQream DB uses GPU technology to improve the performance of columnar queries by at least 20x on large data sets. At the same time reduce the hardware required to perform the query, typically a single 2U server equipped with Nvidia K80 GPU is equivalent to a 42U rack full of servers.

With SQream, a deep analysis can be acted upon quickly, with a clear impact on near real-time decision-making and business responsiveness.

 

 

SQream Technologies empowers CISOs with a more effective way to proactively detect, prevent and remediate rapidly-increasing cyber-attacks, by connecting and correlating high volume of multi-sources data. With SQream, organizations are able to identify patterns and suspicious behavior, track down the activity and mobility to the source, and prevent or mitigate cyber-attacks. By combining big data analytics with security technologies, organizations are able to stay ahead of evolving threats with a strong defense posture.

Big data analytics tightly integrated with the security environment provides high-speed, automated analysis of network activity for detection and prevention of threats, shortens the time-to-remediation when attacks occur, and improves compliance.

 

Cyber Security + SQream = Enhanced Defense Posture

  • Cyber security as a competitive advantage in the marketplace
  • Control over massive amounts of data pinpointing to security threats, deriving from different sources such as: insider threats, mobility and cloud, network
  • Rapid actionable intelligence for quick incidence response
  • Identification of complex patterns
  • Significantly upgraded forensics capabilities and traceability

 

Forensics and Investigation: Identifying Cyber Attackers’ “DNA”

The cyber attacker has a digital equivalent of genotype and phenotype. The SQream DB big data analytics database can store and analyze hundreds of terabytes of data, and can therefor assist when integrated with advanced IT security products, in discovering and determining the identity, lineage, and provenance of the attacker. This can be done through tracing the attacker’s “DNA” back to the “crime scene”.

Big data analytics for Cyber defense and investigation:

  • Storing and analyzing massive amounts of data collected, identified and characterized.
  • Insights from the properties and relationships derived from collected digital artifacts of software, data, and/or users.
  • “Digital artifacts” are collected from computers, distributed information systems such as ‘cloud computers’,” wired or wireless networks, and more.

 

Ultra-Fast Actionable Intelligence – Quick Incidence Response

Leveraging of storage and performance capabilities of mature/emerging Cyber Security technologies – up to 100 terabytes on a single standard 2U server and a GPU card – leads to more comprehensive insights.

  • High-speed automated analytics on massive amounts of data – up to petabytes
  • Connection and correlation of high volume of multi-sources data
  • Ultra-fast detection and prevention of threats
  • Shortening time to remediation when attacks occur
  • Improved compliance
  • Decrease in negative-false/positive-false outcomes

 

Comparing Today’s Data with Yesterday’s

CIOs need to know what is going on now, and be able to compare it to previous months. They need to be able to store and analyze millions of logs, for:

  • Identification and prediction of performance problems, optimization
  • Root cause analysis
  • Security-related issues (who misused or corrupted what data, when and where)
  • Capacity planning
  • Predictions of applications and infrastructure changes’ impact on IT reliability
  • Auditing and archiving purposes of every business transaction

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