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PFP Cybersecurity

Using PFP's patented power analytics algorithms to monitor the integrity and enhance security of embedded devices. PFP(Power Fingerprint) is a complete identification, analysis, and monitoring solution to capture a baseline of activity and then continuously scan for deviations to determine whether an intrusion or cyber-attack has occurred. With PFP’s unique PowerIQ analytics to detect both active and dormant attacks at the hardware and firmware levels, enterprises and government agencies can now find zero-day threats immediately by monitoring and detecting power consumption anomalies.

P2Scan

PC based software containing PFP’s patented power analytics algorithms

pMon

Nework-based digitizer for data acquisition and signal processing

Accurate and Fast

PFP’s PowerIQ technology detects anomalies from trusted baselines in machine time. Using the laws of physics, PowerIQ is nearly impossible to evade or detect.
Fully Customizable

P2Scan provides a user friendly interface with point-and-click simplicity. Monitoring parameters, sensitivity, and metrics are fully customizable by the user
Complete Solution

The P2Scan kit includes all of the necessary probes, amplifiers, and analysis software to immediately begin using PFP capability.
Analog Data Capture

The baseline references, which uniquely identify the execution of a given software routine, are extracted during a controlled “learning” phase before the system is deployed.

The included pMon seamlessly integrates with P2Scan to allow easy data capture from the user’s devices.
Baseline Extraction with Machine Learning

“Baseline Extraction” guides the user through a series of straightforward steps to create the baseline using PFP algorithms.
Runtime Monitoring

Once the baseline is created, P2Scan monitors the user’s system with a simple button push. From that point, P2Scan continuously looks for deviations from the baseline to determine whether an intrusion has occurred.

During Runtime Monitoring, P2Scan provides a number of data views which allow the user to review and interpret the system performance in real time. A persistent graph provides a quick, easy display showing status. For example, a red point indicates an anomaly.