Nature-inspired swarm optimization paradigms for securing semantic web frameworks against DDoS attacks: a computational approach.

Abstract

The Semantic Web has transformed the way data is represented, shared, and integrated across multiple domains. However, as its size and interconnectedness continue to grow, it becomes increasingly exposed to cyber threats. Securing the Semantic Web is therefore a critical challenge, as traditional security methods often fail to protect the highly interlinked data, ontologies, and network structures on which it relies. This paper proposes a novel, nature-inspired cybersecurity approach that uses swarm optimization algorithm to improve the resilience of Semantic Web. These algorithms, modeled on the collective behavior of insects, can efficiently allocate limited security resources to detect and mitigate potential threats in real time. By applying a distributed and adaptive defense mechanism based on swarm optimization, Semantic Web nodes can autonomously respond to evolving attack patterns, reducing vulnerabilities and strengthening overall system security. The results demonstrate a significant improvement in the network's robustness against various attack scenarios, including those targeting ontologies and data relationships. The proposed nature-inspired strategy enables secure and reliable information exchange across distributed systems while adapting dynamically to new cyber threats.