Volume 15, No 1, 2018
AI Strategies For Real-Time Security In Cloud Architecture
Sailesh Oduri
Abstract
In the evolving landscape of cloud computing, real-time security has become a critical concern due to the increasing sophistication of cyber threats. Artificial Intelligence (AI) has emerged as a transformative force in enhancing cloud security by providing dynamic, adaptive, and proactive measures. This article explores the application of AI strategies to bolster real-time security in cloud architecture. It examines how AI-driven anomaly detection systems can identify and mitigate unusual patterns and behaviors, thereby preventing potential breaches. Additionally, the integration of predictive analytics and threat intelligence platforms is discussed, highlighting their role in forecasting and neutralizing emerging threats before they manifest. Automated response systems, powered by AI, are reviewed for their capability to swiftly address security incidents, minimizing damage and downtime. The use of behavioral analytics to monitor and analyze user behavior is also addressed, focusing on its effectiveness in detecting insider threats and compromised accounts. Through case studies of successful AI implementations in cloud security, the article illustrates the practical benefits and challenges associated with these technologies. Despite the advancements, the integration of AI in cloud security is not without limitations, including technical challenges and ethical considerations. The article concludes with a look at future directions in AI research for cloud security, offering insights into emerging technologies and their potential to further enhance real-time protection. Overall, AI represents a pivotal advancement in the quest for robust and responsive cloud security solutions.
Pages: 287-297
Keywords: Artificial Intelligence, Cloud Security, Real-Time Threat Detection, Anomaly Detection, Automated Response Systems.