Solving software and cybersecurity challenges for robust smart camera applications on Xilinx Kria SoMs
Vision systems are rapidly evolving using algorithms based on Machine Learning (ML) to enable detection and complex elaboration in often uncontrolled environments. Total system performance is determined by carefully matching the ML inference subsystem with the Pre- and Post-video processing, ideally integrating in a single device to reduce power consumption and total cost of ownership. Addressing such a system from a software perspective is usually the biggest challenge.
In addition, connectivity on these camera systems coupled with their often accessible physical locations imply exposing devices to world-wide security threats. The attack surface is mainly software, but the integrity of the software can only be ensured by a root of trust in the hardware along with remote attestation of the software and firmware. Similarly, the protection of cryptographic material requires hardware security features. Thus, managing security for Industrial IoT involves setting up security requirements very early in development, achieving in the process of a proper secure by design approach.
During the webinar we present a tutorial based on Xilinx Kria SoM that explains how to acquire video from an camera module, preprocess it using the programmable logic, run inference using pretrained and to-be-trained models and stream the results. We will do all of this using an integrated GStreamer pipeline without HDL coding, and with all the security requirements and aspects taken into consideration. Kria SOMs ability to support secure and measured boot with a hardware root of trust to build a IEC 62443 compliant system is also covered.
Who should attend?
• Software Engineers and Product Managers who are exploring the norms to comply with or the requirements to cover their vision AI technology roadmap
• Cybersecurity Managers or IT Managers who desire to cover the “product” part within their approach
• R&D Managers who are actively developing ML for Vision Applications
Date & time
Tuesday, April 05, 2022, 02:00 PM Central European Summer
What you will learn:
• Added-Value of ML (Machine Learning) for your ecosystem with use case examples
• What is the risk if you don’t consider implementing security into your Industrial IoT system
• Key elements to avoid mistakes and best practices to develop Secured Software & ML on Kria SoMs
• Chetan Khona, Director Industrial, Vision, Healthcare & Sciences, AMD
• Julien Bernet, Security Manager, Witekio
• Stefano Tabanelli, Embedded Software Specialist, South Europe, Avnet Silica
Original Source: Avnet Silica