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Private 5G Networks Face Security Risks Amid AI Adoption
A rapid increase in private 5G network deployments across industries has raised concerns over security gaps stemming from a lack of communications technology (CT) expertise.
New research from Trend Micro and CTOne warns that organizations may be exposing these networks to cyber risks despite integrating AI security tools.
Private 5G networks are gaining traction in sectors such as energy, military, logistics, healthcare and manufacturing.
According to Trend Micro’s survey, all respondents indicated they either currently use (86%) or are evaluating (14%) private 5G deployment. AI-powered security solutions are also widely adopted, with 62% of organizations already using them and another 35% planning to do so.
The research highlights key AI-powered capabilities that security professionals deem essential for protecting private 5G networks:
- Predictive threat intelligence (58%)
- Continuous, adaptive authentication (52%)
- Zero-trust enforcement (47%)
- Self-healing AI-automated networks (41%)
Despite this investment, organizations face challenges in securing private 5G infrastructure.
Over 90% of AI security users report difficulties in deploying the technology. High costs (47%), false positive and negative concerns (44%) and a lack of internal expertise (37%) are cited as significant obstacles.
One critical issue highlighted in the report is the absence of dedicated CT security teams. Only 20% of organizations have specialized personnel for securing communications networks. Instead, responsibility often falls on CTOs (43%) or CIOs (32%), potentially leaving gaps in protection.
“As enterprise use of private and public mobile networks accelerates, we are seeing new challenges that demand specialized CT security capabilities,” explained Jason Huang, CEO at CTOne.
“Organizations need the ability to secure end-to-end combined broad visibility that fits with SecOps needs, enabling them to manage their enterprise attack surface risk as it expands to support new wireless applications.”
The research also reveals that security budgets may not reflect the critical nature of private 5G networks. On average, only 18% of security budgets are allocated to these infrastructures, despite their role in supporting essential services and handling sensitive data.
Additionally, many organizations may be inadvertently exposing themselves to cyber and compliance risks through improper AI use in traffic monitoring and analysis. Only around half of respondents ensure compliance with GDPR (54%), encrypt data in transit and at rest (51%), enforce strict AI access controls (50%) and/or use data anonymization techniques (44%).
“Not all AI security is created equal, and some organizations are putting themselves at risk due to lack of know-how,” said Rachel Jin, chief enterprise platform officer at Trend.
“Proactive attack surface management is crucial for private 5G networks, where any oversight can open the door to compromises. Security leaders must combine AI-powered protection with a deep understanding of technology and cyber risk to safeguard these critical environments.”
