API security and ML pipeline
API security as a service to shrink the growing API attack surface, backed by an AI/ML pipeline that ingests high-volume data in real time and pre-processes it for each requirement.
A blockchain-secured approach to managing urban air mobility fleets. HCISS combines UAV authentication, verified service data, AI/ML analytics and an Autonomous Breach Protection Dashboard to support safe, reliable and autonomous operations.
Built as a Chainlink decentralized oracle cloud network application, the platform brings API security, ML-driven analytics and an interactive security agent together.
API security as a service to shrink the growing API attack surface, backed by an AI/ML pipeline that ingests high-volume data in real time and pre-processes it for each requirement.
AI/ML prediction-based security analytics with KYT reporting. A graph database interface with integrated ML inferences lets users find insights without writing query code.
A cloud-based security interactive agent that delivers alerts, threat modeling analysis and reporting in an intuitive, conversational way.
Flows are refined as detailed requirements arrive, and implementation follows agile development methods.
GNSS provides each UAV with 3D coordinates, speed and time; base stations provide network coverage and controller communications.
The core of the secure UAM infrastructure. It authenticates UAVs joining the network through broadcast certificates and digital signatures, manages registered services, verifies service responses and data integrity, and evaluates node credit through service feedback.
Persistent storage for UAV certificates, service records, hash values, credit evaluations and UAV services.
Controllers and user UAVs that handle control and configuration such as location and landing-point settings.
| Stage | HCISS operations |
|---|---|
| Flight planning | Provide and validate traffic data and reports; collect and validate flight data |
| Pre-flight | Allocate command and control (C2) and detect-and-avoid (DAA) coverage along the flight route |
| Departure & beginning of flight | Verify C2; verify DAA |
| In flight | Monitor airspace and flight path; UAV integrity checks; hazard detection, management and analytics |
Supports and automates hazard and threat identification through a selection of hazard and threat analysis techniques.
A drone-based risk management approach powered by blockchain and smart contracts, so risk-related processes run effectively and efficiently.
Continuous monitoring across HCISS microservices.
Scanning and monitoring for vulnerabilities in smart contract code.
Alerts and threat modeling through BSECABot.
Further research, analysis and business model development within Boeing's digital twin UAM project initiative.
It is the coordination of drones and other urban air vehicles across planning, pre-flight, departure and in-flight stages, including authentication, route verification, hazard detection and reporting.
A blockchain edge service can authenticate UAVs joining the network, verify service data and keep tamper-evident records of certificates, services and evaluations that every participant can trust.
It is an HCISS research and case-study initiative. We welcome conversations with UAM operators, manufacturers and research programs.
Talk to HCISS about securing UAV fleets, flight data and the services around them.