What are the best network security architectures to protect against malware?

2 Network segmentation

Network segmentation is the practice of dividing your network into smaller, isolated sections based on functions, roles, or security levels. This can reduce the attack surface and the impact of malware by limiting its access and spread. For example, you can separate your sensitive data from your public-facing services, or your internal network from your guest network. Network segmentation can also improve performance, availability, and manageability of your network. You can implement network segmentation using VLANs, subnets, firewalls, or SDN.

4 Cloud security

Cloud security is the protection of data and applications that are hosted or accessed through the cloud. Cloud computing offers many benefits, such as scalability, flexibility, and cost-efficiency, but also introduces new challenges and risks for network security. Malware can compromise cloud services, data breaches can occur, and unauthorized access can be granted. Cloud security requires a combination of measures, such as choosing a reputable cloud provider, configuring cloud settings and permissions, encrypting data in transit and at rest, and using cloud security tools and services.

5 Zero trust security

Zero trust security is a network security model that assumes that no entity, whether inside or outside the network, is trustworthy by default. It requires strict verification and validation of every request, connection, and transaction before granting access or permission. Zero trust security can prevent malware from exploiting trust relationships or credentials that are often assumed in traditional network security models. Zero trust security can be implemented using technologies such as multifactor authentication, microsegmentation, encryption, and continuous monitoring.

6 Artificial intelligence

Artificial intelligence is the use of machine learning and data analysis to automate and enhance network security functions. Artificial intelligence can help detect and respond to malware by analyzing large volumes of network data, identifying patterns and anomalies, and learning from previous incidents. Artificial intelligence can also help optimize and improve network security performance, efficiency, and resilience. Some of the applications of artificial intelligence in network security are anomaly detection, threat intelligence, behavior analysis, and incident response.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?