Authentication Fraud

The Problem
Metered attacks that generate low volume log-in attempts, from diverse IPs and across extended time frames, are designed to avoid the "3 strikes in 24 hours" business rules in authentication applications and the more complex analysis of log analytics / SIEM platforms. Batch solutions by definition cannot react until after a compromise has occurred while all real-time solutions impose time windows -- any data falling outside these rolling windows, no matter how important, is simply not processed. Either way, that means important patterns are missed and attempts succeed before you can stop them.
The Solution
Quine's changes the status quo by continuously assessing newly arriving events for their match to all known attack patterns, including the identification and tracking of partial behavior matches across any time frame, and billions or trillions of users/devices/applications, until a behavior pattern is fully observed. Once an attack pattern is fully detected, events are generated immediately to trigger an investigation alert or an automated remediation workflow. Quine's continuous analysis of event streams means there are not time windows to manage, and thus no windows for attackers to engineer their attacks around. And Quine provides this extended time frame of analysis without incurring the cost of SIEM solutions, sifting through data from multiple sources to find and store only the patterns that matter – in this case, the ones that indicate a low and slow attack is underway.

Key Value Delivered

Continuously track behavior patterns across billions/trillions of devices, users, and applications
Provide analyst a complete record of historical actions by user, device, or application
Operate on one domain/customer, or across domains/customers
Costs effective vs. log analysis / SIEM data store quotas

What people are saying

thatDot Platform’s advanced Novelty Scoring for categorical data feature is the future of anomaly detection. Its speed powers our new real-time services while also significantly reducing false-positive findings for our customers.

Gery Szlobodnyik

CEO

The security industry is headed towards leveraging knowledge graphs of all the relevant evidence provided by threat groups, network indicators and endpoint artifacts to quickly identify and mitigate threats. The security companies that can most confidently extract relevant context from these graph and then immediately action on findings to mitigate threats will be the winners. This is exactly the problem Quine aims to address.

Evan Wright

Staff Data Scientist

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If you think Streaming Graph or Novelty might be for you, contact us to see them in action.

Authentication Fraud

The Problem

The Solution

Key Value Delivered

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