2024· International Journal of Artificial Intelligence, Data Science and Machine Learning· 0 citations
TL;DR
The proposed maturity model comprising Fragmented, Instrumented, Correlated, Automated, Automated, and Adaptive stages provides organizations with a practical roadmap for assessing current capabilities and systematically advancing toward intelligent, self-optimizing security operations.
Abstract
Modern enterprises increasingly struggle to manage cloud security architecture, infrastructure resilience, SIEM operations, and regulatory compliance as isolated disciplines, resulting in operational inefficiencies, increased cyber risk, and costly audit processes. This paper presents a comprehensive five-level maturity model that unifies these traditionally disconnected domains into a cohesive framework for enterprise cybersecurity transformation. The proposed maturity model comprising Fragmented, Instrumented, Correlated, Automated, and Adaptive stages provides organizations with a practical roadmap for assessing current capabilities and systematically advancing toward intelligent, self-optimizing security operations. Unlike conventional reference architectures that assume green field deployments, the framework addresses the realities of heterogeneous enterprise environments spanning multi-cloud platforms, storage infrastructures, backup systems, security information and event management (SIEM) solutions, and compliance programs. The study further introduces diagnostic decision flows, capability maps, maturity transition guidance, and comparative operational metrics demonstrating improvements in incident detection, containment, backup resilience, compliance coverage, and automation maturity. By emphasizing the convergence of cloud infrastructure, cybersecurity operations, data protection, and governance through automation and cross-functional collaboration, the proposed framework enables organizations to reduce operational complexity, strengthen cyber resilience, accelerate regulatory compliance, and establish adaptive security capabilities suitable for modern cloud-native enterprises.
The growing dependence of governments, financial institutions, healthcare organizations, energy providers, transportation networks, and communication systems on “cloud-native” platforms has made it more important than ever that these digital services be delivered continuously and securely. Cloud-native architectures offer scalability, flexibility, and quick deployment using microservices, containers, orchestration, and DevSecOps practices, but they also present complex cybersecurity, operational, and supply chain threats to the country’s critical infrastructure and economic well-being. The existing research focuses on cloud resilience, artificial intelligence for IT operations (AIOps), cybersecurity or governance individually, causing approaches to be disjointed and suboptimal for critical service continuity during large-scale cyber incidents. In this research, the authors introduce the AI-powered Integrated Cyber-Economic Resilience (AICER) Framework, which is a conceptual framework that integrates cloud-native infrastructure, cybersecurity intelligence, AI-assisted operational analytics, secure software delivery, economic impact assessment, and governance into a comprehensive decision-support architecture. The framework is formulated on the basis of Design Science Research Methodology (DSRM) and supported by an integrative literature review encompassing the most recent literature, international cybersecurity standards, and cloud computing best practices. The proposed framework does not introduce new performance metrics but rather builds on existing metrics, such as Service Level Objectives (SLOs), availability and reliability metrics, Mean Time Between Failures (MTBF), Mean Time to Recovery (MTTR), DORA software delivery metrics, Common Vulnerability Scoring System (CVSS), Exploit Prediction Scoring System (EPSS), Software Levels for Supply Chain Security (SLSA), and NIST Cybersecurity Framework (CSF 2.0) and NIST AI Risk Management Framework (AI RMF). The framework also takes economic impact into account to inform decisions on recovery for nationally significant services. The proposed architecture provides a vision for a policy-aware and AI-driven approach to enhancing cyber resilience, bolstering critical infrastructure, and fortifying continuity of essential digital services. The study provides a strong foundation for further prototype implementation, experimental validation, and deployment in public and private critical sectors.
Unknown authors· American Journal of Innovati...· 0 citations
The Adaptive Risk-Driven DevSecOps Framework (ARDDSF) is proposed, a layered framework for securing multi-cloud enterprise systems in the era of agentic artificial intelligence that bridges DevSecOps automation, AI-assisted security analysis, Zero Trust policy enforcement, and multi-cloud governance.
Nitin Bodade· International Journal of Inn...· 0 citations
Saudi enterprises are rapidly adopting cloud technologies to advance digital government, artificial intelligence, financial services, industrial modernization, and data-intensive operations. While this migration strengthens operational capabilities, it also disperses identity, data, workloads, and dependencies across complex hybrid and multi-cloud environments. The main challenge goes beyond intrusion prevention to include the preservation of vital services, containment of damage, restoration of trustworthy operations, and organizational learning from disruptions. This review critically synthesizes research published between 2020 and 2025 on cloud security and cyber resilience, with a specific focus on enterprise infrastructure in Saudi Arabia. A structured integrative review was conducted, encompassing peer-reviewed literature in cybersecurity, cloud computing, zero trust, ransomware, industrial control, and risk governance, and supplemented by the Saudi National Cybersecurity Authority's Cloud Cybersecurity Controls. The synthesis identifies five interdependent capabilities: governance and shared-responsibility assurance; identity-centred zero trust; data and workload protection; telemetry-driven detection and automated response; and recovery engineering supported by tested backups, service continuity, and supplier resilience. Evidence demonstrates that isolated security products are insufficient for resilience when asset ownership, cloud configuration, privileged access, recovery objectives, and third-party liability are fragmented. Accordingly, this paper proposes a Saudi Enterprise Cloud Cyber-Resilience Framework which integrates compliance alignment, architectural controls, operational preparedness, and continuous learning through a six-stage lifecycle: govern, anticipate, withstand, detect, recover, and adapt. The review delivers a practical control-to-outcome model and a staged implementation roadmap for enterprises pursuing secure cloud transformation while assuring compliance, service availability, and organizational confidence.
Munir Ahmed Mohammed· Global academic journal of e...· 0 citations
Large-scale data center migration within Saudi critical infrastructure is not a conventional relocation of servers and applications. It is a time-bounded transformation of trust boundaries, routing domains, identity dependencies, recovery mechanisms, and operational accountability. During coexistence, legacy and target environments remain interconnected, which expands the attack surface precisely when configuration volume, change velocity, and service uncertainty are highest. This review examines how cyber resilience can be engineered into migration programmes through secure IP fabric segmentation, evidence-led threat containment, and continuity controls aligned with Saudi Vision 2030. An integrative review of peer-reviewed studies, standards, and regulatory documents published from 2020 to 2025 was undertaken. Evidence was synthesised around five analytical themes: migration risk, EVPN-VXLAN segmentation, zero-trust enforcement, containment and recovery, and governance. The review finds that resilient migration depends less on a single security product than on coordinated design decisions. These include separating management, replication, user, backup, security, and operational-technology flows; replacing inherited network trust with identity- and workload-aware policy; constraining migration corridors; maintaining cryptographically protected recovery copies; and releasing each migration wave only after observable technical and business evidence has been obtained. A reference operating model is proposed in which dual-running environments are governed through explicit security zones, continuous telemetry, policy-as-code, tested rollback, and service-level recovery objectives. The principal contribution is a practical review framework that treats migration as a sequence of reversible resilience decisions rather than a one-time cutover.
Zakiuddin Mohammed· Veredas do Direito· 0 citations
The methodology addresses log correlation, alert triage, incident classification and cross-functional escalation protocols and produces measurable improvements in mean time to detect (MTTD) and mean time to respond (MTTR) while reducing alert fatigue and redundant infrastructure costs.
Oladele Adekunle Awonusi· Computer Science & IT Re...· 0 citations
In recent years, organizations have increasingly migrated enterprise systems to cloud platforms, significantly transforming how operational and financial processes are managed. With the adoption of modern solutions such as SAP S/4HANA, new security challenges emerge, particularly in areas such as access control, identity governance, and monitoring of privileged activities. This article aims to analyze the main security challenges in SAP cloud environments and propose a risk-based approach that integrates governance, access control, and continuous monitoring. The methodology is based on conceptual review and analysis of market practices aligned with international security frameworks. The results indicate that implementing structured governance models enhances organizational resilience against cyber threats while ensuring compliance with global standards. It is concluded that security in SAP cloud environments is essential for protecting critical systems and ensuring business continuity.