TL;DR
This paper presents the cloud computing security risk assessment (CCSRA) framework, which addresses this gap by constraining cloud consumer involvement to asset definition and importance criteria, delegating threat and vulnerability evaluation to the CSP through attack tree analysis, and combining both inputs into a reproducible quantitative risk score within an ISO/IEC 27005-aligned process.
The study demonstrates that the key factors to achieving effective cloud security are continuous monitoring, robust governance policies, employee awareness training, and high-level cybersecurity frameworks.
The results indicate that MPC can support privacy-preserving collaborative vulnerability assessment in a simplified proof-of-concept setting, but that scalability and protocol choice remain important limitations for larger deployments.
A taxonomy that classifies security controls for SaaS platforms by the degree to which they are observable to the tenant is introduced, giving tenants a shared language for procurement, contractual negotiations, and continuous assurance, and gives providers a roadmap for increasing visibility into their controls.
Results from a controlled testbed evaluation demonstrate that implementing this model substantially reduces the exposure window available to attackers — eliminating credential exposure and unplanned security-related downtime — and supports a smooth, transparent, and secure transition to cloud infrastructure.
This paper presents a hybrid edge–cloud framework for resilient cybersecurity monitoring and organizational security assessment, intentionally technology-agnostic so that it can be extended with different sensors, endpoint sources, security controls, analytical models, and security-operations integrations.
This paper proposes a conceptual framework for distributed, AI-assisted risk assessment designed to address the gap between conventional vulnerability management and distributed systems, and outlines key open challenges— data, robustness, performance, consistency, explainability, and evaluation.
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