This paper reviews over 120 security publications from 2008 to 2025, focusing on how these isolation boundaries can be breached, and introduces a quantitative scoring framework called ADPO, which rates defenses from 0 to 3 based on their Accuracy, Deployment ease, Performance impact, and Operational overhead.
Abstract
In cloud computing, different users share the same physical hardware, which creates serious security risks. To protect data, cloud systems rely on virtual machines and containers to keep users isolated. This paper reviews over 120 security publications from 2008 to 2025, focusing on how these isolation boundaries can be breached. We examine threats like virtual machine escape, virtual machine hopping, CPU cache side-channels, container breakouts, vulnerable container images, and distributed denial of service (DDoS) attacks. We evaluate these security threats and their defenses using three key research questions. To compare different defense systems, we introduce a quantitative scoring framework called ADPO, which rates defenses from 0 to 3 based on their Accuracy, Deployment ease, Performance impact, and Operational overhead. We also map the impact of these attacks onto a 1-to-5 severity scale for Confidentiality, Integrity, and Availability. Finally, we highlight the trade-offs between security and system performance, and we outline open challenges like building low-overhead intrusion detection and creating realistic test datasets.
This work presents the first large-scale, systematic analysis of default security weaknesses across cloud providers and reveals substantial variation in default security postures, high-light the need for increased transparency and standardization in default cloud security practices.
It is concluded that securing serverless environments requires a paradigm shift from network-level protection to granular application logic validation and continuous observability, essential for maintaining data integrity in decentralized cloud-native environments.
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