We Calculate r

The correlation coefficient reveals relationships invisible to conventional analysis

In 1880, Francis Galton invented r to measure statistical relationships between variables. Today, we apply this fundamental mathematical principle to cybersecurity—detecting coordinated attacks by analyzing correlations between seemingly unrelated events.

Pearson Correlation Coefficient
r=Σ(xi - x̄)(yi - ȳ)
√[Σ(xi - x̄)²] · √[Σ(yi - ȳ)²]
Calculated Correlation
r = 0.947
Coordinated Attack Detected5 Events3 Users7 Days
0.94
Minimum Correlation
for Alert Threshold
2.4B
Event Correlations
Analyzed Daily
1.8%
False Positive
Rate Average
47
Behavioral Variables
in Matrix Analysis

The rSecure Platform

Correlation analysis at scale across your entire security infrastructure. Each product in the rFamily uses correlation analysis as its foundation, working together to calculate r across billions of data points in real-time.

rTable.ai

Red Team cybersecurity tabletop exercises for training and education of incident response, crisis management, and disaster recovery for enterprise teams.

rGate.ai

Secure web gateway tool that aids enterprises gain more granularity in control over data flows to AI tools, visibility into this flow, and protections against DLP. Protection against common ransomware and phishing attacks.

rHook.ai

Phishing testing platform that creates campaigns, executes them, collects data, and guides training and awareness. Tools for email phishing, executive spearphishing, voice phishing (vishing), and other social engineering assessments.

The Mathematics of Threat Detection

Sophisticated attackers operate in the correlation sweet spot: r values between 0.6 and 0.9. Too random, and they're ineffective. Too predictable, and they're obvious. Traditional signature-based detection fails in this range because it's looking for exact matches, not statistical relationships.

We calculate r across 47 behavioral dimensions simultaneously, constructing correlation matrices that reveal coordinated attacks invisible to conventional security tools. This isn't artificial intelligence guessing at patterns—it's mathematical certainty measuring relationships.

The universe runs on patterns. And if you can measure the pattern, you can predict what happens next.

Francis Galton · Statistician · 1880

How Correlation Analysis Works

Traditional security tools analyze events in isolation. We analyze relationships. When five seemingly unrelated events show r = 0.94, that's not coincidence—that's a coordinated attack.

Identify the Sweet Spot

Sophisticated attackers operate in the correlation sweet spot: r values between 0.6 and 0.9. Too random, and they're ineffective. Too predictable, and they're obvious. That's where we hunt.

Calculate at Scale

No human analyst can calculate r for 50,000 simultaneous events per hour. But our AI can. And it does. We analyze covariance matrices across 47 different behavioral indicators simultaneously.

Reveal the Pattern

Traditional SIEM tools analyze events in isolation. We analyze relationships. When five seemingly unrelated events show r = 0.94, that's not coincidence—that's a coordinated attack.

Real-Time Correlation Analysis
r = 0.94

Coordinated Attack Detected Across Platform

See Correlation Analysis in Action

The universe runs on patterns. And if you can measure the pattern, you can predict what happens next. That's what we do at rSecurity.ai. Get started to see how correlation detection can reveal threats in your environment.