DNS servers, like any other server, are vulnerable to all network-based attacks. TCP/UDP/ICMP floods, for example, can cause a large amount of network traffic to the DNS servers, rendering the service unavailable to other network users by saturating the network link to the DNS servers. Attackers can also exploit a specific vulnerability in the DNS server software or host operating system to either circumvent control measures and create rogue entries in the DNS database or crash the DNS server.

NetworkFort caters to this challenge by not storing or distributing information relating to the IP addresses. It does not let the resolver’s operator link queries to identities. Besides this, it encrypts the email data (content) and any attachments and transports them securely, hence ensuring security.

NetworkFort uses AI and ML to counter DNS attacks. The detection of these attacks (DNS) can be achieved using two types of analysis, i.e., payload and traffic analysis.

In payload analysis, the payload packets traveling over the network are analyzed for any malicious code. If positively identified, the tunnel creation can be prevented, leading to security.

On the other hand, the second method is traffic analysis. In this approach, the entire traffic is taken into account. Here, the number of requests, history, and other statistics are used to differentiate between normal and malicious traffic. The normal DNS behavior is taught to the ML model, and for any incoming traffic not matching the set baseline, an alert for the anomaly is generated as it may be an attack.