Artificial Intelligence (AI) has revolutionized the way businesses operate. However, with the rapid growth of AI, security concerns are rising. Companies must protect their data from cyberattacks, comply with data protection regulations, and ensure their AI models are ethical and transparent. One solution to these challenges is deploying AI at the Edge. In this article, we'll explore how the Edge can provide a secure infrastructure for private, compliance, and secure AI deployment.
By controlling data closer to its source and therefore deciding which data needs to be sent to the cloud, the cybersecurity risks of theft or improper access to information are much lower with Edge Computing.
In IoT deployments, it is common to hear the term Edge. Many IoT solution vendors, especially in the industrial environment, acknowledge the capabilities of the Edge to generate business value. But what is IoT Edge and what is its relationship with Edge Computing?
Cybersecurity is increasingly becoming a fundamental part of every company's strategy. For industrial companies operating with state-of-the-art technology, security is a key business element as these are infrastructures that can be "critical" in the event of a cyberattack if they do not have a medium-term digital plan. Something that could be solved with cybersecurity systems based on artificial intelligence at the edge.
Edge computing, or the ability to store and process data on servers close to the source or destination of that data, is becoming increasingly fashionable. The IT world has been using it for years with regional data centers that serve content more efficiently. What is new today is the beginning of its incursion into industrial environments.
These are the conclusions reached by Barbara, which presents research on cybersecurity in this sector. Forty percent of industrial organizations have already experienced at least one security incident in the last year, with the industrial and energy sectors being the most vulnerable.