What we learned about crowdsourcing data for security

No working model exists

Crowd-sourcing security data offers enormous promise: real-time, ground-truth intelligence for everyone in the network. But any crowd-sourcing effort comes with significant challenges. With more than 7 billion potential intel sources, crowd-sourced reporting needs some controls for reliability. Current models for security information are consumer-centric and do not have mechanisms to protect proprietary or sensitive company data. More importantly, these models leave organizations without the structure they need to safeguard large numbers of people effectively.

…so we’re building one.

Leveraging professionals, vested stakeholders, and Artificial Intelligence (AI) , we’re tackling each of these problems. The concept is simple: develop a broad, trusted network for intelligence-sharing and validation of open-source data to keep one another safe.

Here’s how it works. A user-generated report gets passed to the security manager (or similar role), who confirms the report and shares it to her organization and passes it up to Stabilitas. Our software does a final analysis, then anonymizes and shares the report across our ecosystem while still keeping your company’s data secure and partitioned. There’s trust-based human verification at each level, supported by pattern recognition, sentiment analysis, and other machine learning (more AI) processes the whole way through.

We believe this will provide unparalleled speed, accuracy, and granularity in risk information. Security leaders at Fortune 500 companies have told us how excited they are about this project, particularly when combined with our intelligence and communication platform. What do you think? Reply below or send us an email. We’d love to hear from you!