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Local governments have options to deal with the rapid rate of adoption for edge devices.

State and local governments are embracing edge computing in a big way. Spending on edge solutions worldwide is expected to be $208 billion in 2023, rising to $317 billion in 2026, according to IDC’s latest study.

Several factors are contributing to this increased investment. At the state and local level, edge is the backbone of smart cities. For example, a Philadelphia district uses edge computing as part of a smart city initiative to gain real-time insights into air quality, transportation modes, weather and more.

Combined with artificial intelligence, edge computing can:

  • Reveal useful insights
  • Help identify problems before they impact the population
  • Make public services (emergency response, transportation management) more efficient

However, citizens are rightly sensitive to the collection, storage and potential misuse of data collected and processed at the edge. Fortunately, there are options for securing this complex and growing environment: security automation and observability.

Automation Takes the Guesswork out of Risk Discovery

The first step to securing the edge is gaining transparency into the devices deployed in these environments. Edge devices are coming online at a rapid rate — IBM predicts 21.5 billion edge devices will be connected by 2025 — and network topologies are evolving quickly. For these reasons, it can be difficult to completely understand what devices are accessing the network, their relationships, how they communicate and their security profiles. Automation can help.

Using automated network device discovery, agencies can better understand the footprint of all edge devices and their security posture. This approach also can discover malicious or rogue devices as well as those that are vulnerable to cyberthreats. For example, sensors and devices often collect data from residents and assets. Should these fall into the wrong hands, hackers can conduct surveillance of unsuspecting citizens or hijack the device and use it to interrupt critical public services, such as transportation systems or emergency response networks.

Automation Closes Vulnerabilities on Edge Devices

Edge devices create an enormous attack surface and can number into the thousands (think parking lot sensors, smart lighting, traffic controls, intelligent transportation and lane optimization systems). These technologies advance smart city initiatives and improve citizen services, and protecting them from attacks is crucial.

Security automation is key to closing potential security gaps quickly and proactively. For example, a hacker will scan edge networks looking for vulnerabilities, such as unpatched software or applications. This was the case in Oldsmar, Fla., where threat actors hacked an out-of-date supervisory control and data acquisition system at the city’s water plant and altered the amount of sodium hydroxide in the water.

Since many edge devices are supported by third-party applications, ensuring they are up to date is arduous and time-consuming. With automation, however, agencies can automatically scan their networks for unpatched devices and promptly push out updates before hackers can exploit any vulnerabilities.

Visualizing the Entire Hybrid Infrastructure

The distributed nature of edge computing brings more devices and a larger attack surface, but gaining insights into the security performance of complex edge environments is tricky. These infrastructures comprise sensors, cloud, 5G and virtualized environments, and it can be incredibly difficult to detect and remediate security issues on all endpoints.

This presents a potential danger to any urban or smart city ecosystem. IDC predicts that, in 2023, more than 50 percent of enterprise IT infrastructure will be deployed at the edge instead of in data centers. With so much data flowing and being generated every millisecond, agencies struggle to protect edge devices. Indeed, the smarter the city, the greater the risk.

While agencies can’t fully protect themselves from every cyberattack, they must do everything possible to make sure the services citizens rely on continue working correctly and safely.

One way to get a handle on security performance in the vast edge computing ecosystem, especially in hybrid environments, is through security observability. Observability goes beyond basic security monitoring. It combines technology like artificial intelligence, machine learning and data analytics to help agencies better understand the complexities within edge environments while providing real-time visibility to help detect security issues and minimize response time. Automation takes things further, allowing the system to remediate security issues without human intervention.

Automation and Observability Are Key to Edge Security

A secure edge is a crucial and strategic enabler for transforming public services and infrastructure. Still, agencies that deploy edge must deal with constant technology updates, an expanding attack surface and new security issues. To reduce risk and protect sensitive data, agencies should automate wherever possible while ensuring proactive observability into potential problems across this complex environment. Through automation and observability, complex tasks are simplified and problems are quickly identified even as edge deployments continue to grow.

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Autor(en)/Author(s): Brandon Shopp

Quelle/Source: State Tech Magazine, 11.05.2023

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