AI-driven security for next-generation data centers: Conceptualizing autonomous threat detection and response in cloud-connected environments

Sunday Adeola Oladosu 1, *, Adebimpe Bolatito Ige 2, Christian Chukwuemeka Ike 3, Peter Adeyemo Adepoju 4, Olukunle Oladipupo Amoo 5 and Adeoye Idowu Afolabi 6

1 Independent Researcher, Texas, USA.
2 Independent Researcher, Canada.
3 Globacom Nigeria Limited.
4 Independent Researcher, Lagos, Nigeria.
5 Amstek Nigeria Limited.
6 CISCO, Nigeria.
 
Review Article
GSC Advanced Research and Reviews, 2023, 15(02), 162–172.
Article DOI: 10.30574/gscarr.2023.15.2.0136
Publication history: 
Received on 27 March 2023; revised on 09 May 2023; accepted on 12 May 2023
 
Abstract: 
The dynamic evolution of next-generation data centers, driven by cloud-native and hybrid architectures, has necessitated a paradigm shift in cybersecurity. Traditional security models, designed for static and on-premise environments, struggle to address the complexities of cloud-connected infrastructures and the rapidly evolving threat landscape. Emerging challenges, such as advanced persistent threats (APTs), ransomware, and insider attacks, demand sophisticated and adaptive security solutions. In this context, artificial intelligence (AI) emerges as a transformative technology capable of redefining threat detection and response mechanisms. This review explores the conceptualization of AI-driven security for next-generation data centers, focusing on autonomous threat detection and response. By leveraging AI and machine learning (ML), security systems can achieve real-time anomaly detection, advanced behavior analysis, and predictive risk assessment. These capabilities enhance the accuracy and speed of identifying malicious activities while reducing false positives. Additionally, autonomous response mechanisms, such as self-healing networks and adaptive security policies, enable rapid containment and mitigation of threats, minimizing potential damages. The review also discusses the integration of AI with existing Security Operations Centers (SOCs), highlighting its potential to augment human decision-making and automate repetitive tasks. Furthermore, it examines the role of advanced encryption, identity management, and compliance tools in fortifying security frameworks. Future trends, including the impact of 5G and edge computing, are explored, emphasizing their implications for real-time applications and IoT security. This study underscores the importance of proactive, AI-driven strategies in securing next-generation data centers, ensuring scalability, resilience, and robust protection in an increasingly interconnected digital landscape. By bridging the gap between cloud-native and on-premise environments, AI-powered security frameworks offer a promising path toward achieving autonomous, adaptive, and future-proof cybersecurity.
 
Keywords: 
AI-Driven; Threat detection; Cloud-connected environments; Next-generation
 
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