Noah K. Bamfo Proposes AI Overhaul for DNSSEC in Global Network Security

By Benson Michael

Noah K. Bamfo, a leading Network Solution Architect and Senior Engineer, is calling for a major rethinking of DNS security architecture one that embraces artificial intelligence and machine learning to overcome the inherent performance limitations of DNSSEC.

Despite being essential for internet functionality, the Domain Name System (DNS) has long been vulnerable to various attacks. While DNS Security Extensions (DNSSEC) were introduced to mitigate these issues by authenticating DNS responses, Bamfo’s extensive fieldwork has revealed critical flaws.

“DNSSEC works, but not without cost,” Bamfo explains. “In high-throughput or bandwidth-sensitive environments, its signature verification and key management slow everything down. We need more than secure responses we need smarter systems.”

Bamfo has spent over nine years fortifying networks across Africa and the U.S., leading major DNS-layer security projects in critical institutions. One such project was for the Social Security and National Insurance Trust (SSNIT), where he adopted Cisco Umbrella a cloud-delivered security platform that uses AI models from Cisco Talos to detect and block malicious domains in real time.

By using AI rather than relying solely on DNSSEC’s cryptographic methods, Bamfo reports that his team achieved faster response times and significantly improved network latency. “AI models were able to interpret DNS query behaviors and spot threats proactively, something DNSSEC is too rigid to do,” he noted.

He brings similar innovation to other critical infrastructures. During politically sensitive periods, he secured the operations of a nation’s Electoral Commission using Fortinet firewalls combined with DNS anomaly detection and global threat intelligence feeds. At the National Banking College, Bamfo enforced DNSSEC policies alongside AI-driven analytics through Sophos cloud tools, successfully stopping data exfiltration methods like DNS tunneling and beaconing.

Bamfo’s vision is supported by emerging academic findings. Advanced machine learning techniques such as Capsule Networks, Multi-Task Learning, and Ant Colony Optimization are proving effective at bolstering DNS security in environments using encrypted protocols like DNS-over-HTTPS (DoH). These AI models enable real-time threat detection while preserving privacy and minimizing processing loads.

“The shift is clear,” Bamfo says. “We’re moving from static defense to predictive intelligence. DNSSEC laid the groundwork, but AI gives us the foresight we need to stay ahead of threats.”

However, he acknowledges that the road ahead is not without hurdles. AI-based DNS solutions must maintain user privacy, handle encryption, and perform efficiently in constrained environments like IoT devices or edge networks.

“But these challenges are solvable,” Bamfo affirms. “With adaptive architectures and the right learning models, we can reduce reliance on brute-force cryptography and move toward intelligent threat screening.”

For enterprises aiming to modernize their cybersecurity infrastructure, Bamfo’s work signals a new frontier in DNS protection one that doesn’t discard DNSSEC but reimagines its role in a smarter, AI-driven era.