What is Edge Computing?

A Gartner report from 2020 described Edge Computing as “part of a distributed computing topology in which information processing is located close to the edge — where things and people produce or consume that information.”

The International Data Corporation predicts that more than half of new enterprise infrastructure will be at the edge by 2023, and worldwide spending on edge computing will reach $250 billion by 2024. According to Gartner Inc.’s research, data generated at the edge will increase from 10% today to 75% by 2025. Further growth will be fueled by this data, the intelligence it generates, and other innovations. This is nothing new for those in the data and technology sectors.

The idea of edge computing was born out of a desire to reduce data transmission costs over long distances. The traditional method for storing and processing data involved transferring it to a centralized system for storage, analysis, and eventual return to the end-user. This paradigm has shifted to cloud-based services in recent years.

Latency was another factor that drove systems closer to the point of need. In the financial sector, for example, the speed of the algorithm largely replaced human sentiment as a market determinant.

We will see below how Edge Computing has become an integral part of global technology. The boom is due to the proliferation of IoT devices, both industrial and personal, as well as 5G telecommunications. Keeping things close minimizes the journey of data, but expanding who has access to those secrets presents new risks.

HUB Security’s Confidential Computing strategy is designed to capitalize on those benefits and keep them secure. By implementing a confidential computing strategy, data is only processed on hardware where and when necessary and only by those who need it.

Here is a closer look at Edge computing to gain a better understanding.

Edge in Practice

An MIT study found that health care and life sciences account for more than 30% of all data storage worldwide. Each US hospital bed has at least 15 connected devices, according to the report. They provide real-time information, like heart monitoring, so they have to have the shortest latency possible.

It takes a CD to store a single MRI scan. Doctors must access these hundreds of times a day in a modern hospital, sometimes even during an operation. There is a vast cost in bandwidth to access this data via the cloud or central servers. Increasingly, the healthcare industry is adopting an edge model in which storage and processing occur near the point of treatment using sensors to guide treatment.

With 5G transforming rural communities, the benefits of edge computing are already being felt in the rural healthcare sector. In recent years, WLAN networks and even fast broadband have been patchy, forcing the use of edge devices. Otherwise, the disparity between rural and urban healthcare would be much worse.

Autonomous Vehicles

The advent of autonomous vehicles is driving the development of AI for Edge devices. Consider that ‘ the camera sensors on a vehicle should be able to detect and recognize its surrounding environment without relying on computational resources in the cloud within 3ms and with high reliability (99.9999%). For a vehicle with 120 km/h speed, 1ms round-trip latency corresponds to 3 cm between a vehicle and a static object or 6 cm between two moving vehicles.’

As events occur in milliseconds, onboard devices with high processing power are needed to keep up with connected vehicles and, increasingly, smart highways and navigation systems.

A table drawn from the same article eloquently describes this:

Autonomous vehicles table

I would not get in a car connected to the cloud after reading this!

Edge is revolutionizing numerous other industries. These include;

  • Petroleum and gas: many facilities are located in remote locations that require constant monitoring in real-time. Edge computing reduces the reliance on high-speed connections to clouds or centralized services.
  • Domestic IoT devices such as fridges, ovens, lighting, heating, security alarms, and the like are becoming more prevalent. Edge computing can mitigate the issues of remote processing related to cost, speed, and security.
  • Manufacturers can monitor their machinery for health with analytical sensors that provide real-time information about its well-being. Such monitoring allows them to intervene before expensive failures occur.

While the list is long, one commonality between many of the applications is their use in critical infrastructure and industries. As a result, edge computing is frequently employed in areas where failure can severely harm an individual, such as healthcare, or society as a whole, such as water treatment.

Thus, Edge computing security challenges are of utmost importance. It is a long journey from the edge to the cloud, and it is vulnerable to various attacks. Reducing the length of this journey reduces this risk. As IT evolves, malicious actors quickly catch up with the cyber defense systems designed to deter them. What solutions does Hub Security offer for keeping edge technology secure?

Confidential Computing consists of hardware-based mechanisms to protect data in use. In the classic version, compute, and data are isolated in memory. However, edge cybersecurity needs additional controls to protect other components. These include the applications and operating layers such as OS, VM, and Containers. Thus, our vision of confidential computing seeks to secure computation and data across the entire stack using an integrated hardware and software platform, as the pictogram below depicts.

Confidential computing for integrated hardware and software platform

Edge computing is the fastest-growing area that will transform lives and lead to massive economic growth. HUB aims to make edge cyber security an integral part of the ecosystem.