Juniper Research predicts IoT cybersecurity revenue will grow from $27.1 billion in 2024 to $60.6 billion in 2029, reflecting a 17 percent CAGR. This 120 percent+ increase in spending will be driven by the rapid adoption of enterprise IoT devices, which, if unsecured, pose significant cyber-attack risks and financial losses.
The network layer will be the most critical aspect to protect, accounting for over 45 percent of global cybersecurity spending in 2025.
Enterprises will need to adopt advanced network security solutions like NGFWs (Next Generation Firewalls) to counter AI-driven attack methods.
Comprehensive security strategies must cover the network, cloud, and endpoints, with XDR (Extended Detection and Response) playing a key role in unifying and automating IoT security.
Cybersecurity platforms must offer unified threat detection and security management to mitigate endpoint vulnerabilities and reduce network complexity, Michelle Joynson, the author of the report, said.
Forescout, a cybersecurity company, revealed that in 2023 the world’s critical infrastructures suffered 13 cyberattacks every second, with over 420 million attacks between January and December.
While IoT ecosystems enhance business efficiency, analytics, and connectivity, they also introduce significant cybersecurity risks, as each connected device serves as a potential entry point for cyberattacks. A single compromised device can grant intruders access to the entire network, allowing lateral movement to sensitive data. This makes IoT systems attractive and high-value targets for cybercriminals.
IoT botnets are a growing concern, accounting for 40 percent of all DDoS traffic in 2023, according to a Nokia Threat report. To mitigate risks, businesses must implement strong passwords, security patches, and robust device configurations. Network monitoring and intrusion detection are essential for identifying botnet activity, and IoT cybersecurity providers should integrate these solutions into comprehensive security platforms.
OTA (Over-the-Air) updates offer an efficient way to distribute security patches across IoT networks, reducing manual updates. However, manufacturers and OEMs must implement encryption and authentication to secure these updates. As attacks become more sophisticated, IoT cybersecurity vendors and device manufacturers must proactively enhance security measures, monitor attack patterns, and continuously adapt their solutions to emerging threats.
AI and machine learning play a crucial role in IoT cybersecurity by enhancing real-time threat detection, vulnerability assessment, and automated responses. Their advanced analytics help identify network anomalies, detect malware — including zero-day attacks — and improve overall security.
However, AI requires vast amounts of high-quality data to function effectively, and in its early stages, it may produce false positives or negatives. This can be mitigated through better data quality, improved algorithms, sandbox testing, and continuous monitoring, the report said.
AI’s ongoing training demands make it expensive to maintain, with environmental concerns such as high water consumption for cooling data centers. Additionally, AI can be exploited by cybercriminals to launch more sophisticated attacks or become a security vulnerability itself. To counteract these risks, vendors and service providers must collaborate and share threat intelligence to strengthen cybersecurity defenses.
Baburajan Kizhakedath
