Enhancing Secure Digital Infrastructure through Intruder Detection and Mitigation Using Cryptographic Hash-Based Malware Signatures: A Contribution to SDG 9.

The high rates of spreading digital technologies have been followed by the increased number of advanced cyber threats, and malware and intruder attacks have proved to be the serious threats to the critical infrastructure, essential services, and company information. The threat is highlighted by this increasing threat landscape, and it requires stable and secure digital infrastructures that will identify and counter such nefarious activities effectively. The purpose of the study is to improve the digital protection system by creating an intruder-detection system based on the concept of the malware signature using cryptographic hashes, namely, the Schla-256 algorithm. A quantitative methodology of simulation was thus used where malware samples have been used in open-source repositories like the virus share. The system was programmed by the Python computer language and run in Cisco Packet Tracer to consider the performance measures of detection rate, latency, CPU consumption, and false positive characters. The main findings include a high detection rate of 98.5 %, low latency (15 ms) and low numbers of false alarms, which are more rendering than traditional decision support systems in terms of efficiency and accuracy. The findings indicate that hash-based detection is an excellent method to enhance cybersecurity resilience at a low computational cost. The study under consideration directly supports the idea of Sustainable Development Goal 9 (SDG 9) or fostering the creation of reliable, secure, and innovative digital infrastructure. The study helps the industrialize as well as innovate by ensuring that they are able to trust in the digital ecosystems that are prerequisite to inclusive and sustainable development by enhancing cybersecurity building.