AI-Driven Cybersecurity Systems for Modern Digital Infrastructure using Cloud Computing and Enterprise Risk Management
DOI:
https://doi.org/10.15662/IJEETR.2025.0706049Keywords:
artificial intelligence, cybersecurity, cloud computing, enterprise risk management, machine learning, threat detection, anomaly detection, cyber risk, cloud security, digital infrastructure, automated incident response, security analyticsAbstract
Artificial intelligence (AI) has become an important component of modern cybersecurity as organizations increasingly depend on cloud computing, distributed applications, Internet of Things devices, remote work environments, and interconnected enterprise networks. Traditional cybersecurity mechanisms based exclusively on predefined rules and signatures are often insufficient for identifying sophisticated, rapidly evolving, and previously unknown threats. AI-driven cybersecurity systems address these limitations by applying machine learning, deep learning, natural language processing, behavioral analytics, and automated response mechanisms to detect anomalies, identify malicious activities, predict emerging risks, and support security decision-making. Cloud computing further enables organizations to deploy scalable security capabilities across geographically distributed infrastructure while providing centralized monitoring, elastic computational resources, and access to large volumes of security data. However, cloud-based environments also introduce challenges involving data privacy, identity management, misconfiguration, third-party dependencies, model security, and regulatory compliance. Enterprise risk management provides a strategic framework for integrating these technical capabilities with organizational objectives, risk appetite, governance, and business continuity requirements. This essay examines the role of AI-driven cybersecurity systems in protecting modern digital infrastructure through cloud computing and enterprise risk management. It discusses the integration of intelligent threat detection, predictive analytics, automated incident response, cloud security controls, and risk-based decision-making. The study argues that effective cybersecurity requires a coordinated combination of AI capabilities, cloud-native security architecture, human oversight, and enterprise-wide risk governance
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