Rome, Italy. — July 22, 2020 — Exein today announced it has joined NVIDIA Inception, a program designed to nurture startups revolutionizing industries with advancements in AI and data sciences. Exein has developed a whole new approach to edge security, using advanced machine learning technologies to secure small embedded devices. This is made possible using the computational power of NVIDIA GPUs, which handle compute-intensive tasks such as training thousands of ML models that secure Exein customer devices. NVIDIA Inception helps startups during critical stages of product development, prototyping and deployment. Every Inception member gets a custom set of ongoing benefits, including NVIDIA Deep Learning Institute credits, marketing support and preferred pricing on GPUs, enabling early-stage startups with fundamental tools to help them grow.

About Exein

Exein looks to tackle the huge security threat posed by connected smart devices and the vulnerabilities carried within their firmware. IoT and smart-connected platforms are well-secured and optimized using the most recent security standards, however, the firmware is not. Hardware manufacturers are racing to make the cheapest hardware possible. The fall-out from this is that insufficient budget is set aside for the firmware and only 1% is allocated to security, leaving huge vulnerabilities. In addition to the firmware budget problems, there are over a decade of technological backwardness in the field of firmware security. Attacks that target routers, cameras, and other non-personal computer devices are on the rise and common solutions use handwritten rules and vulnerabilities. These specific firmware security techniques detect known threats and attacks but leave devices vulnerable to any unknown attack. This is why Exein has developed the first Open Source security framework for IoT, SCADA firmware systems. It operates as an embedded component from within the hardware, acting from the firmware core and stopping any external threat. Exein Technology uses Convolutional Neural Networks to learn the expected behavior of a device and uses this understanding to constantly monitor its functioning and protect it from cyber-threats, both known and unknown ones.