University networks are prime targets for hackers. By exploiting a vulnerable device with outdated firmware or weak passwords, bad actors can move laterally through the network to other high-value devices, stealing student records, financial credentials and other confidential or high-value information.
Research institutions, in particular, generate and store highly valuable data—such as scientific discoveries, medical research, engineering designs, proprietary formulas and blueprints—that are prime targets for cybercriminals seeking financial gain or engaging in malicious intent.
While stolen data is certainly one of the major consequences of a data breach, another overlooked consequence is network disruption. Network downtime negatively affects everything from day-to-day administrative operations to online learning uptime, degrading a university’s bottom line and reputation.
Consider, for example, dorms and resident halls, which are one of the largest revenue sources for most universities. And if occupancy rates are not 100%, universities lose revenue.
Network uptime and reliable connectivity are critical factors in student satisfaction. If students cannot connect to the internet to complete assignments, play video games or stream movies because of network performance and security concerns, they may leave the dorms or even the institution.
For universities, protecting their networks is tantamount to protecting their bottom line. They need a campus-wide zero-trust security framework that secures every port and access point by default and bakes identity-based access into the network infrastructure itself. Without this, implementing such a security framework can be quite challenging.
Zero-trust readiness: Why most universities struggle
Currently, most universities have basic security measures in place, such as firewalls, anti-virus endpoint protection, intrusion detection systems, encryption and multifactor authentication. However, these protections are mere table stakes.
The security readiness gap for higher education becomes more evident with the adoption of advanced capabilities such as complex AI-driven threat detection, data loss prevention and zero trust security solutions. These advanced capabilities, especially zero-trust, are harder to implement due to varied interpretations.
A general survey of higher education organizations would reveal that almost all have a zero-trust strategy in place, but few have deployed it at scale across their entire network environment. Many IT teams have attempted to overlay a zero-trust framework on top of their legacy network’s architecture, resulting in compatibility challenges and security gaps.
The Gartner report, “Predicts 2025: Scaling Zero-Trust Technology and Resilience,” found that complexity, integration issues, resistance and vendor limitations will cause 30% of organizations to abandon their zero-trust initiatives by 2028.
Other obstacles that prevent universities from successfully implementing zero-trust initiatives include legacy infrastructure, never designed for dynamic access control or micro-segmentation, which are key elements of zero-trust.
IT teams will also try agent-based solutions like zero-trust network access (ZTNA); however, these do not account for unmanaged IoT or OT devices. Administrative mistakes, like misconfigurations and policy sprawl, likewise impede success.
Additional barriers to achieving campus-wide zero-trust are IT skills and labor shortages. Many networking teams lack budget or manpower for extensive zero-trust projects, focusing mainly on uptime.
What is campus zero-trust?
Within the zero-trust framework, there is strict authentication, continuous verification and isolation of users and devices, regardless of their origin on the network. These rules treat every access attempt as potentially malicious, thus preventing internal and external threats.
Unfortunately, these principles were initially designed to reinforce environments where remote access, IoT/OT devices and sophisticated AI threats did not exist.
Because cybercriminals often target known vulnerabilities, they attack devices and then move laterally within a university’s network. Within a campus zero-trust framework, universities can minimize the blast radius of an attack by restricting the movement of hackers and associated malware and threats.
A combination of host-based isolation that comes out of the box, and a deny-all policy that prevents communications without explicit permission is required.
This enables IT to create policy groups that can flexibly be based on identity and not necessarily network constructs like VLANs. Only this form of micro-segmentation provides very fine-grained controls that are consistent with zero trust principles.
In other words, should a device become compromised, the attacker cannot move to other higher-value devices. This new fine-grained segmentation enables universities to prolong the shelf life of their assets, benefiting their bottom line.
Ideally, universities should explore alternatives where campus zero-trust features are built directly into the network architecture. This approach would remove legacy vulnerabilities and the need for IT teams to constantly layer add-on security services on top of the network.
Of course, many universities’ IT teams cannot accomplish this level of implementation on their own, which is why some choose to deploy campus zero-trust via a network-as-a-service model and purpose-built network architecture.
When done properly, this emerging network architecture will not require VLANs, manual software configurations or allow for open Ethernet ports. It should include built-in segmentation, per-device isolation, traffic inspection and consistent policy enforcement.
Built-in rather than bolted-on
Universities should not have to retrofit advanced capabilities onto legacy networks simply to resolve outdated vulnerabilities. Instead, networks must be purpose-built with zero-trust in mind—where continuous visibility, identity enforcement and segmentation are inherent to the architecture.
In this model, granular authentication and micro-segmentation to prevent lateral movement aren’t afterthoughts but essential capabilities that scale policy enforcement and threat detection without relying on manual oversight.
Such an approach will safeguard the university network from disruption, ultimately protecting (and potentially improving) one’s bottom line and reputation.
