The Internet of Things can only get better

The rapid expansion of the Internet of Things (IoT) has changed how digital systems interact with the physical world. Millions, if not billions, of connected devices, from household appliances to industrial machinery, environmental sensors, medical diagnostic tools, and more, collect and exchange data with minimal human intervention.

This growing “network” has led to the automation of many mundane tasks as well as enormous improvements in efficiency across all these areas and beyond. However, researchers writing in the International Journal of Critical Infrastructures warn that the increasing complexity of the digital world brings with it vulnerabilities. This is perhaps of growing interest and concern as artificial intelligence is incorporated into the way in which IoT devices work.

The team explains that many IoT devices have limited computing resources, and so they are constrained in terms of how well they can address security issues. As a result, many devices are security targets and can, for instance, be added to so-called botnets, networks of affected machines used to carry out bigger attacks on networks and infrastructure using Distributed Denial of Service (DDoS) attacks and other methods.

Addressing these problems is vital if critical IoT systems are to be protected in energy grids, medical environments, factories, and across so-called smart cities. The research focuses on anomaly detection as a powerful strategy for identifying potential threats and system failures. Unlike standard rule-based security systems that use predefined patterns of known threats, anomaly detection can use machine learning to identify patterns based on training data and algorithmic analysis rather than explicit programming.

As IoT technology spreads, anomaly detection in real time is an essential part of implementation and a requirement for maintaining system integrity. Failures or breaches in interconnected systems could have cascading effects, disrupting essential services and undermining public trust.

Ultimately, securing IoT networks through this kind of proactive monitoring is not just a technical necessity but a safeguard for infrastructure that depends on all those millions of devices.

Xu, J. (2026) ‘Integrating IoT and machine learning for scalable anomaly detection in smart city infrastructure’, Int. J. Critical Infrastructures, Vol. 22, No. 10, pp.1–16.