ROSSLYN, Va. - Shift5 in Rosslyn, Va. has released the Shift5 GPS Integrity Module, a platform-agnostic solution applicable for military, aviation, rail, maritime, and space industries. It is designed to detect and alert operators to GPS spoofing attacks in real-time by analyzing onboard data. The module employs anomaly detection methods to assess changes in navigational position and provide immediate notifications of spoofing incidents as they occur.
Over three months, the Shift5 GPS Integrity Module detected 24 instances of degraded GPS performance among Shift5 customers.
GPS spoofing poses significant threats to national defense and commercial transportation systems, potentially leading to navigational errors and compromised safety. According to Gartner, global navigation satellite systems (GNSS) face increasing unreliability due to jamming, spoofing, and other forms of interference, posing risks to safety-critical applications such as aircraft landing and autonomous vehicle control.
Related: War zone GPS spoofing is threatening civil aviation
Using algorithmic position analysis and GPS data validation, the Shift5 GPS Integrity Module identifies significant position deviations and discrepancies indicating tampering, triggering immediate notifications for operators to initiate Standard Operating Procedures (SOPs) to mitigate risks.
The Shift5 GPS Integrity Module offers detection and alerting capabilities for GPS spoofing attempts, including physics-based spoofing detection and advanced analysis of enriched data from various sources. It provides real-time notifications to operators and seamlessly integrates with existing platforms.
Shift5's platform is adaptable to new spoofing techniques and can be deployed using existing onboard resources or optional hardware. Shift5 alerts can be integrated into existing SOPs, and metadata about spoofing incidents can be utilized for threat mapping and route avoidance in geospatial systems. Data collected by the module enriches other Shift5 modules, including the cybersecurity and predictive maintenance modules.
