Built specifically for the SDV era, the PlaxidityX Vehicle Detection & Response (VDR) platform is a unified, AI-powered software solution that seamlessly integrates in-vehicle monitoring with advanced cloud-based analytics. By fusing detection, prevention and response in a single platform, VDR enables a commercially viable and operationally optimized security posture for the entire fleet.
Siloed tools see only parts of the attack, while data overload is driving OpEx costs to unsustainable levels. SDVs are left vulnerable to both remote network exploits and physical keyless theft. PlaxidityX VDR fixes this by converging in-vehicle monitoring with advanced cloud-based analytics into a single, AI-powered, unified infrastructure. VDR eliminates vendor sprawl, neutralizes complex threats, and drastically cuts SOC overhead.
VDR employs in-vehicle software agents to perform local correlation and noise filtering through IDXR, while also leveraging VPCC – a cloud-based, experience-driven AI model – to identify and highlight genuine security attacks.
Drastically reduces cellular data usage by ~80% and saves SOC analysts hours of tedious investigation time through AI-driven smart filtering.
Creates a single, reliable source of truth by ingesting, filtering and normalizing data from any 3rd-party agent or legacy sensor, eliminating the need to completely replace the current agents.
Streamlines operations by running cyber protection and keyless theft prevention on a common platform, removing the friction of managing isolated systems and siloed data.
Enriches alerts with TARA findings (AutoDesigner), vulnerability data (SSCS), and telematics context.
Pushes new detection rules and security configurations to vehicles instantly from the cloud without FOTA.
Automatically triggers recording of detected threats and uploads deep forensic evidence.
Built-in support for UNR155 and GB/T standards, with automated reporting and evidence collection.
Sensors across the vehicle (CAN, Ethernet, Host) monitor raw traffic and system calls.
The Edge Engine analyzes these signals locally, using advanced signal analysis and AI algorithms to filter out false positives (noise), detect immediate threats, and compress the data before transmission.
The Cloud Core’s AI correlates Indicators of Compromise (IoCs) fleet-wide, learning from active exploits to hunt matching threat vectors across different vehicle architectures. This intelligence is instantly enriched with AutoDesigner TARA logic and SSCS vulnerability data to validate the attack kill chain and expose the true impact.
Upon detection of a threat, IDXR can respond locally by triggering an immediate mitigation (e.g., block message). Based on a continuous feedback loop, VPCC pushes new detection rules and security configurations back out to the entire fleet to protect against evolving threats.
This cross-platform manager aggregates and standardizes security events from Linux, QNX, Android, and AUTOSAR ECUs into a unified format. By applying smart filtering, it transforms raw data into prioritized Qualified Security Events (QSEvs), ensuring regulatory compliance while drastically reducing data noise and SOC alert fatigue.
Monitor CAN network traffic, detect anomalies and the signs of a threat, and prevent major risks including denial-of-service and brute-force attacks.
Protect in-vehicle networks with comprehensive network monitoring, threat detection, and attack prevention as an ECU library or pre-integrated into switch firmware.