A recent surge in the deployment of private 5G networks across various industries has raised concerns regarding security vulnerabilities due to a lack of communications technology (CT) expertise.
According to a joint study conducted by Trend Micro and CTOne, organizations may be at risk of exposing their private 5G networks to cyber threats despite implementing AI security solutions. Private 5G networks are becoming increasingly popular in sectors like energy, military, logistics, healthcare, and manufacturing.
Survey findings from Trend Micro indicate that the vast majority of respondents either currently use (86%) or are considering deploying (14%) private 5G networks. Furthermore, AI-powered security tools are being widely adopted, with 62% of organizations already utilizing them and an additional 35% planning to integrate them into their systems.
The research highlights the key AI-driven capabilities that security professionals believe are crucial for safeguarding private 5G networks, including predictive threat intelligence, continuous, adaptive authentication, zero-trust enforcement, and self-healing AI-automated networks.
However, despite the investment in AI security solutions, organizations are facing challenges in securing their private 5G infrastructures. More than 90% of AI security users report difficulties in deploying the technology, citing high costs, concerns about false positives and negatives, and a lack of internal expertise as significant obstacles.
One alarming revelation from the report is the lack of dedicated CT security teams within organizations. Only 20% of companies have specialized personnel focused on securing communications networks, leaving the responsibility often to Chief Technology Officers (CTOs) or Chief Information Officers (CIOs) and potentially creating gaps in protection.
Jason Huang, CEO at CTOne, emphasized the need for specialized CT security capabilities as the use of private and public mobile networks increases among enterprises. He stressed the importance of broad visibility that aligns with security operations (SecOps) needs to effectively manage the expanding attack surface risk associated with new wireless applications.
Furthermore, the study found that security budgets allocated to private 5G networks may not adequately reflect their critical role in supporting essential services and handling sensitive data. On average, only 18% of security budgets are devoted to these infrastructures.
In addition, many organizations may unknowingly be exposing themselves to cyber and compliance risks by improperly utilizing AI in traffic monitoring and analysis. Less than half of respondents ensure compliance with GDPR, encrypt data in transit and at rest, enforce strict AI access controls, or utilize data anonymization techniques.
Rachel Jin, Chief Enterprise Platform Officer at Trend, warned about the varying levels of AI security and the potential risks associated with inadequate knowledge in this area. She highlighted the importance of proactive attack surface management in protecting private 5G networks, emphasizing the need for security leaders to combine AI-powered protection with in-depth technological understanding and cyber risk awareness to secure these critical environments effectively.