AI-Driven Security Mechanisms In IOT Cloud Solutions

Abstract

Artificial Intelligence (AI)-driven cloud security has emerged as a revolutionary approach to tackle the increasing complexity of cyber threats within cloud computing. This research investigates the incorporation of AI and Machine Learning (ML) methods to improve the capabilities of cloud-based security solutions in terms of threat detection, prevention, and response. The paper highlights the primary factors contributing to the adoption of AI-driven cloud security, such as the rapid growth of cloud-based data and applications, the rising occurrence of advanced persistent threats, and the necessity for real-time, adaptive security measures. It analyzes how AI and ML algorithms can process extensive volumes of security-related data, detect anomalies, and recognize new threats with higher precision and speed compared to traditional security methods. The study also examines the different capabilities of AI-driven security. Additionally, it looks into the challenges that come with the deployment of AI-enhanced cloud security. The study's findings offer significant knowledge for cloud service providers, security experts, and decision-makers aiming to harness AI and ML to bolster their cloud security initiatives. The Internet of Things (IoTs) has become a focal point of interest. It encompasses the connectivity of numerous devices and their integration with humans. IoTs necessitates a cloud computing framework to manage its data exchange and processing, while at the same time, it relies on AI to evaluate the data housed in cloud infrastructure and make prompt and accurate intelligent decisions. These interconnected IoTs devices utilize unique identifiers and embedded sensors within each device to communicate with one another and share information using the internet and cloud-based network infrastructure. We exist in the age of big data, where the need for applying AI/ML has become essential for the swift and precise processing and analysis of the gathered cloud-based big data. Nevertheless, despite the growing influence of AI in enhancing traditional cybersecurity measures, both cloud vulnerabilities and the networking of IoTs devices remain significant risks. In addition to the security challenges associated with cloud and IoTs devices, hackers are also leveraging AI, which continues to pose a threat to the cybersecurity landscape.