Using LLMs as Incident Prevention Copilots in Cloud Infrastructure
Sai Prasad Veluru, Mohan Krishna Manchala · International Journal of AI BigData Computational and Management Studies · 2024
Incident prevention has become very critical in modern, complex, changing cloud environments. Conventional security systems may struggle to fit the speed & scale of modern infrastructure, which leaves companies more vulnerable to human mistake, overlooked threats & also incorrect settings. Specifically Large Language Models (LLMs), AI is beginning to revolutionize cybersecurity. With their ability to understand natural language, scan logs, evaluate settings & also spot patterns, large language models which help to anticipate, interpret & also prevent security issues are becoming more valuable allies in the ongoing effort to forecast, analyze & avoid security concerns. Acting as smart assistants, LLMs may see potential issues before they become more serious, provide actual time repair suggestions, and enable developer, security team & cloud operations communication. These models increase visibility & more responsiveness by combining automated policy verification, anomaly detection & also threat modeling among any other approaches. Initial findings reveal instruments including custom fine-tuned LLMs embedded into CI/CD systems like OpenAI's Codex, Google's Sec- PaLM.One notable example is to a financial services organization that included a big language model into its deployment process, therefore significantly lowering their incident rates by spotting dangerous infrastructure changes before they were put into use. This incident, among any others, emphasizes the great benefit LLMs can offer not just as proactive partners in protecting their cloud systems but also as reactive aid after breaches. Integration of LLMs into the cloud security process has clear benefits even if accuracy, bias, and explainability remain challenges. Using AI to improve human expertise might help companies move from reactive crisis management to a proactive defensive culture. The growing role of LLMs in cloud security, the technical approaches enabling their effectiveness, and the structure for their effective incorporation into incident prevention strategies are investigated in this paper