It is well known that the connected devices ecosystem has grown at a robust rate. In fact, Transforma Insights’ forecasts state that the number of devices will grow at a CAGR of 9%, from 21 billion IoT devices in 2025 to reach 48 billion by 2035. IoT devices are being deployed across every sphere of life, from connected smart home devices to critical infrastructure. Therefore, the security risks associated with IoT networks also increase and require advanced technological solutions to combat cyber-risks. This becomes more important as IoT systems often consist of a large number of distributed devices that collect and transmit significant volumes of data from remote locations, frequently operating under constraints such as limited connectivity, restricted computational resources, and inconsistent security controls, resulting in limited visibility and making them vulnerable to cyber-attacks. According to Palo Alto Networks’ 2025 Device Security Threat Report, ~21% of IoT devices have at least one vulnerability and 2% of IoT devices are susceptible to Known and Exploited Vulnerabilities (KEV), implying that cyber-attackers are actively exploiting these vulnerabilities.
Curbing cyberattacks is important for enterprises to safeguard their infrastructure and keep their operations and systems running smoothly. Imagine a cyberattack targeting a nation’s critical energy infrastructure, such as its national power grid. Such an attack could not only result in widespread blackouts but could also create serious national security risks. For instance, in December 2025, in Poland, a cyberattack targeted around 30 distributed energy sites, including wind, solar, heat, and power facilities. The attackers compromised Remote Terminal Units and the communication infrastructure used to monitor and manage these assets.
This blog explores why enterprises need to adopt a robust IoT network security solution to guard connected devices from cyberattacks. It talks about the rise of IoT network anomaly and threat detection (ATD) solutions and the key capabilities of such solutions that help enterprises to protect their deployed IoT devices. For more information on IoT network anomaly and threat detection, please read Transforma Insights’ recently published reports: ‘IoT network anomaly and threat market landscape’ and ‘IoT network anomaly and threat detection vendor profiles’.
There are numerous challenges associated with protecting IoT and OT environments, which must be addressed to realise the benefits linked to connecting these devices. Some of the key issues are that connected device ecosystems often: are associated with legacy systems; are deployed in resource-constrained environments; have weak device authentication and communication protocols; and adopt a multi-vendor approach. These are highlighted below in the infographic in more detail.
The objective of IoT network anomaly and threat detection solutions is to identify connected devices on the network, map them across asset types and risk categories, and then monitor device communications over the network for irregularities. The moment any unusual network or device behaviour is observed, such solutions can flag it and raise security incidents, and some solutions can even take automated action on compromised devices to ensure that the network remains protected and the threat stays contained to the affected device only.
These solutions monitor network traffic by analysing captured network data against a baseline of normal network behaviour. Solutions vary, based on the type and depth of data collected and analysed; but generally, they reveal information on source and destination addresses, ports, packet size, communication frequency, and traffic volume. Most IoT network anomaly and threat detection solutions offer an overview of network metadata without much insight into payload information. Some solutions, however, analyse full packet data, capturing entire data packets, which supports more detailed inspection of network protocols.
In either case, the IoT network and anomaly and threat detection solutions use three ways to monitor network traffic:
Often, connected devices with low processing power, limited memory, and computing capabilities are deployed in resource-constrained environments, making it difficult to install security features onboard. Besides, they often have limited network connectivity, resulting in limited visibility. Moreover, many IoT devices are supplied with default passwords and lack robust authentication measures, such as unique device identifiers or strong identity management mechanisms, making them easy targets for cyberattacks. Thus, the availability of IoT network anomaly and threat detection (ATD) solutions becomes essential as they can identify connected devices on the network, map the risks associated with them, and ensure that only authorised users access those devices. With the increasing adoption of AI, AI-enabled solutions will become the norm for performing automated anomaly and threat detection and taking preventive steps to stop the spread of cyberattacks.
