Higher Education - IoT Network Segmentation and Protection

Challenge

Preventing lateral movement attacks within large, decentralized campus networks.

Segmentation implementation challenges

of higher education institutions report difficulties in implementing effective network segmentation

Budget limitations

of universities cite budget constraints as a significant barrier to adopting network segmentation

Lateral movement exposure

of universities experienced lateral movement attacks in 2024

Solution

Cylera enhances IoT device security for higher education institutions by facilitating network segmentation and accelerating the adoption of zero trust frameworks.

University students in a robotics lab working with IoT-connected devices, securely monitored and protected on the campus network using Cylera’s cybersecurity platform.

Enhanced Network Security, Reduced IoT Cyber Risk for Higher Education Institutions

"Adopting Cylera's solutions has greatly improved our IoT device security. By facilitating strong network segmentation, minimizing lateral movement, and speeding up zero trust framework adoption, we've been able to safeguard our campus network more efficiently and better secure our sensitive research, staff, and student data."

IT Director

Large Research University

Enhance higher education IoT device network security and swiftly neutralize malware and other cyber threats

University IT administrators in a server room reviewing IoT device network activity, ensuring real-time monitoring and segmentation for cybersecurity with Cylera’s platform

Detailed Device Profiling Network Segmentation And Protection

Detailed Device Profiling

Cylera swiftly identifies and profiles all IoT devices connected to the campus network, capturing detailed information such as device model, manufacturer, operating system, and network traffic patterns. This granular data is essential for creating effective network segmentation policies tailored to the unique needs of higher education institutions.

Automated Policy Generation

Leveraging machine learning and behavioral analysis, Cylera automatically generates network segmentation security policies tailored to each IoT device's risk level and function within the campus network. This approach minimizes the risk of human error and ensures that security measures can adapt to diverse, dynamic higher education IoT environments.

University IT analyst reviewing IoT device network segmentation policies automatically generated by the Cylera platform and designed to prevent cyber attack lateral movement on networks and enhance cybersecurity in higher education environments.

Clinical Awareness Network Segmentation And Protection

A smart keycard being used on a campus security access control system, an IoT device that is secured using Cylera’s automated network segmentation policies and integrations with firewall and NAC solutions.

Segmentation Policy Creation Update Network Segmentation And Protection

Threat Containment

Cylera sends the network segmentation policies it generates for IoT devices on campus networks to popular firewall and network access control (NAC) solutions used by university IT teams via integrations. These firewall and NAC solutions can then use the security policies generated by Cylera to effectively isolate and contain IoT device threats on campus networks.

Continuous Monitoring and Adaptation

Cylera constantly monitors the network behavior and communications of IoT devices on campus, creating new IoT device network policies or adjusting existing ones as necessary. This approach ensures that the network segmentation policies Cylera develops for higher education institutions remain effective and current as the network changes.