Firefly Optimization-Based Model for Cloud Security Enhancement
Venkata Sai Sandeep Velaga · 2025
Cloud computing has dramatically changed the digital space with its on-demand scalable services, yet it poses a new wave of security risks, including data loss, unauthorized access, and implanted attacks on virtual machines. In response to new types of challenges posed by introducing intelligent solutions based on several intelligent techniques, including bio-inspired optimization algorithms, researchers have looked into a number of bio-inspired optimization algorithms. The Firefly Algorithm (FA), utilizes the bioluminescent signalling behaviour of fireflies as a model for addressing complex optimization issues in cloud security. This chapter seeks to create a synopsis of Firefly Optimization and its application to cloud security methods. In this chapter, the basic principles of the Firefly Algorithm will be synthesized to outline the rationale for studying new algorithms that can optimize security issues. The contextual advantages to using the Firefly Algorithm in solving high-dimensional optimization problems will be addressed, in addition to detail studies where Firefly Algorithm (FA) were specifically utilized for tasks like Feature Selection, Intrusion Detection Systems (IDSs), and Better Resource Allocation in cloud systems. By conducting a survey of the more recent literature, we demonstrate where FA has led to improved efficiency and accuracy regarding security mechanisms used in cloud systems. The discussion chapter will close with a summary of some of the key themes, advantages, disadvantages, and suggestions for future avenues of research on cloud systems with optimization- driven security.