{"id":4399,"date":"2025-12-24T07:36:00","date_gmt":"2025-12-24T06:36:00","guid":{"rendered":"https:\/\/enthec.com\/?p=4399"},"modified":"2025-12-24T07:36:00","modified_gmt":"2025-12-24T06:36:00","slug":"edge-computing-what-it-is-and-why-it-poses-a-new-cybersecurity-challenge","status":"publish","type":"post","link":"https:\/\/enthec.com\/en\/edge-computing-what-it-is-and-why-it-poses-a-new-cybersecurity-challenge\/","title":{"rendered":"Edge computing: what it is and why it poses a new cybersecurity challenge"},"content":{"rendered":"

For years, the cloud computing model has been the driving force behind digital transformation. Centralizing data and processes appeared to be the most logical option. However, the growth of the Internet of Things (IoT), the need for real-time responses, and the proliferation of connected devices have spurred the adoption of another approach: <\/span>edge computing<\/b>.<\/span><\/p>\n

Understanding what edge computing is, how it works, and its security implications is now crucial for any organization managing critical data or distributed infrastructure. While edge computing offers speed and efficiency, it also raises new cybersecurity challenges that cannot be ignored. <\/span><\/p>\n

Before we get into the subject, it’s worth noting something important:<\/span> the more processing points and devices a system has, the larger the attack surface. <\/b>. And that’s where solutions like Kartos by Enthec begin to play a strategic role.<\/span><\/p>\n

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Edge computing, what exactly is it?<\/b><\/h2>\n

When we ask the question, “What is edge computing?” we refer to a model in which data processing is performed as close as possible to its point of generation, rather than sending it to a centralized data center or the cloud.<\/span><\/p>\n

In practice, this means that sensors,<\/span> IoT devices,<\/a> <\/span>local servers, or gateways<\/span> process information in real time, reducing latency and bandwidth consumption. <\/b>Only the necessary or already filtered data is then sent to the central systems.<\/span><\/p>\n

This approach is instrumental in environments where<\/span> every millisecond counts, such as industry, healthcare, or intelligent transport systems.<\/span><\/p>\n

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How edge computing works in practice<\/b><\/h2>\n

To understand how edge computing works, it’s helpful to imagine a distributed architecture with several layers:<\/span><\/p>\n

Edge processing<\/b><\/h3>\n

Devices located at the “edge” of the network (sensors, cameras, industrial machines, smart routers) collect and analyze data in real time. <\/span>Here, decisions are made quickly, without depending on the cloud.<\/b><\/p>\n

Selective communication with central systems<\/b><\/h3>\n

Not all information travels to central servers. <\/span>Only aggregated data, alerts, or historical information are transmitted,<\/b> thereby reducing costs and improving efficiency.<\/span><\/p>\n

Cloud integration
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Edge computing doesn’t eliminate cloud computing; it complements it. The cloud remains key for advanced analytics, long-term storage, and global coordination. <\/span><\/p>\n

This hybrid model is powerful, but also<\/span> more complex to protect<\/b>.<\/span><\/p>\n

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Edge computing and examples in different sectors<\/b><\/h2>\n

Examples of edge computing help to understand why this technology is spreading so rapidly:<\/span><\/p>\n