embedded world 2023 Best in Show Winners: Security
March 13, 2023
Winners have been chosen based on a 15-point rubric that considers solutions’ Design Excellence (5 points), Relative Performance (5 points), and Market Impact/Disruption (5 points).
The Embedded Computing Design editorial staff is pleased to present this year’s embedded world Best-in-Show winners in the Security category:
- Digi International’s Digi ConnectCore Security Services: Taking device security to the next level, Digi ConnectCore® Security Services are a collection of advanced services and tools that ensure the security of products during their entire lifecycle — solving the challenge of keeping products secure after release. ConnectCore Security Services include the analysis and monitoring of a custom software bill of material (SBOM) and binary image running on Digi ConnectCore SOMs for security risks and vulnerabilities. To help remediate identified issues, the services provide a curated vulnerability report highlighting critical concerns, a security software layer including patches for common vulnerabilities, and consulting services.
- Exein’s Exein runtime: Exein Runtime is a cutting-edge runtime threat detection and response solution (XDR) for Linux and RTOS-based IoT systems. It defends IoT devices against all types of cyber threats and facilitates real-time detection and response to known and unknown attacks. The system is powered by Exein Pulsar, an open-source kernel observability framework that uses Rust for optimum performance in embedded environments. Exein Runtime caters to companies that require protection against IoT security threats, like OEMs. It offers state-of-the-art security for IoT devices in real-time, thereby ensuring complete protection against external threats.
- BG Networks’ AnCyR Anomaly Detection and Cyber Resilience Automotive ECU Security Software: Patent pending, AnCyR (Anomaly Detection and Cyber-Resilience) host-based software anomaly detection technology provides a real-time front line of defense for embedded connected devices. Based on five years of research at the University of Arizona with support from the National Science Foundation, AnCyR combines statistical, probabilistic, and machine learning algorithms to accurately detect attacks with best-in-class false positives, latency, and overhead. AnCyR is the only solution with the high performance but low overhead needed to be the front line of monitoring and defense for automotive ECUs and other safety-critical connected IoT devices.