Cloudwick One® Open Source Adaptive Security (OSAS)

In today’s world of one data breach after another, enterprises are faced with a hostile information security environment. It’s crucial to invest in a threat discovery and protection solution that monitors and analyzes at big data scale. Cloudwick One® OSAS is a managed solution for enterprises that provides comprehensive visibility into operational and security threats by performing advanced analytics at cloud scale.

Advanced Analytics Performed at Cloud Scale

Cloudwick One® OSAS, built on Open Network Insight (ONI), gives visibility into security threats facing dynamic data centers by providing advanced intelligence using big data analytics performed at cloud scale. It accelerates the ability for enterprises to expose suspicious connections and previously unseen attacks using flow and packet analysis, and breaches are identified within hours rather than weeks.

Analyzes Billions of Events Per Day

Most existing security solutions rely on signature matching and rules and can only analyze millions of daily events. Cloudwick One® OSAS analyzes billions of events to detect suspicious activities and insider attacks and diagnose dark areas. Existing tools also produce too many false positives due to poor rule writing, while Cloudwick One® OSAS delivers fewer false positive alerts by triangulating data with context to assure alerts are legitimate.

Machine Learning Separates Benign from Bad Traffic

Using machine learning as a filter for separating bad traffic from benign and identifying unique traffic behavior, Cloudwick One® OSAS applies a proven process of context enrichment, noise filtering, whitelisting and heuristics to produce a shortlist of most likely security threats.

Insights on Data Already Being Collected

While other solutions often require new processes for sensing data, calling for additional infrastructure investments, Cloudwick One® OSAS analyzes the data that’s already there (DNS packets, net flow, etc.) to detect suspicious activities and insider attacks.

Cloudwick One® OSAS Advantage

  • Suspicious Connects: Use machine learning to filter out normal traffic and look for patterns in unusual network connections. Patterns can be triaged and high risk traffic or connections can be reported to incident response, medium passed through to the machine learning, and low risk removed.
  • Suspicious DNS: Machine learning filters out normal DNS traffic to show patterns in an underlying graph, such as unusual rank order, network or geographical context as it relates to the domain and external threat intelligence.
  • Storage Prediction: Future storage needs can be predicted based on data accumulation over a period of time, and the more data that exists, the more accurate the prediction.
  • Incident Response: Take a specific IP address (i.e., one believed to be a potential risk) and gather details and characteristics of its associated communications to build a timeline of the conversations that originated with it.
  • Storyboard: Communicate threat intelligence across the organization by presenting results in a storyboard, showing details of the events including: what (impact), how (incident progression), where (geolocation), and when (timeline). Communicate results via interactive visualization as well as text, with a high-level summary for an executive audience, as well as details to address deeper questions.

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