Security vulnerabilities jeopardize private 5G networks amid AI boom
Trend Micro, one of the world's leading providers of cybersecurity solutions, has published a new joint study with CTOne. The study warns of a lack of communications technology (CT) expertise that could jeopardize private 5G networks despite the widespread adoption of artificial intelligence (AI)-powered security tools.
Private 5G networks are booming thanks to their use in critical industries such as energy and utilities, the military, logistics and healthcare. 100% of respondents to the trend study stated that they are either already using private 5G networks (86%) or are considering their use (14%).
IT and cybersecurity experts also seem to understand the potential benefits of AI-powered security in these environments: Here too, almost all of them stated that they either already use such tools for private 5G networks (62 percent) or plan to use them (35 percent).
Respondents consider the following AI-supported functions to be essential:
- Predictive threat intelligence (58 percent)
- Continuous, adaptive authentication (52 percent)
- Enforcement of Zero Trust (47 percent)
- Self-healing networks with AI automation (41 percent)
The lack of internal CT expertise is also reflected in the fact that only a fifth (20 percent) of global companies have a dedicated team to protect their communication networks. In many cases, responsibility for CT security lies with the CTO (43 percent) or the CIO (32 percent).
On average, less than a fifth (18 percent) of companies' security budgets are currently spent on private 5G networks, even though they support critical services and transport highly sensitive data.
Every second company protects data inadequately
Trend's study shows that companies are unknowingly exposing themselves to cyber and compliance risks if they do not secure the use of AI to monitor/analyze data traffic.
Specifically, only around half or fewer of those surveyed stated that they:
- ensure compliance with data protection regulations such as the GDPR (54 percent)
- Encrypt data at rest and in transit (51 percent)
- Establish strict access controls for AI models (50 percent)
- Use data anonymization techniques (44 percent)
"Not all AI security is created equal, and some organizations are putting themselves at risk due to a lack of expertise," said Rachel Jin, Chief Enterprise Platform Officer at Trend. "Proactively managing the attack surface is critical for private 5G networks, as any lapse in attention can open the door to compromise. Security leaders must combine AI-powered protection with a comprehensive understanding of technology and cyber risk to protect these critical environments."
5G and AI: security must grow with it
"Organizations see great operational value in private 5G networks, often as part of AI projects," reports Jim Frey, Principal Analyst, Networking for ESG. "However, they need to ensure that their Security Operations Center (SOC) is prepared to monitor and protect this new communications technology. Cybersecurity vendors that can employ proactive risk management, attack path prediction and other proactive measures will be able to protect private 5G and AI architectures."
Jason Huang, CEO of CTOne: "As organizations increase their use of private and public networks, new challenges arise that require specialized CT security capabilities," explains Jason Huang, CEO of CTOne. "Organizations need to ensure end-to-end security combined with comprehensive visibility that aligns with SecOps requirements. This allows them to manage the attack risk of the IT surface as it continues to expand and support new wireless applications."
