Enhancing public cloud resilience: an analytical review of detection and mitigation strategies against economic denial of sustainability attacks

Sahar Saeed, Zubaidi Maytham and Zainal, Anazida Binti and Ghaleb, Fuad A. and Al-rimy, Bander Ali Saleh (2025) Enhancing public cloud resilience: an analytical review of detection and mitigation strategies against economic denial of sustainability attacks. Discover Internet of Things, 5 (1). ISSN 2730-7239

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Abstract

Cloud computing (CC) delivers computing resources as utilities, akin to services like electricity or water. However, security concerns—particularly Distributed Denial of Service (DDoS) and its economically targeted variant, Economic Denial of Sustainability (EDoS)—pose significant threats to its adoption. EDoS attacks exploit the pay-per-use and auto-scaling features of CC platforms to incur financial damage by triggering unnecessary resource consumption. While existing studies have proposed various countermeasures, comprehensive, comparative analysis remains limited. This review systematically examines 69 key articles addressing EDoS-specific or joint DDoS–EDoS threats. Beyond merely cataloguing these methods, this review provides a novel analytical synthesis by categorizing defense strategies into detection, prevention, mitigation, and hybrid models, and critically evaluating them against factors such as scalability, computational overhead, and false-positive rates. Importantly, this study introduces a service-model-aware framework, distinguishing which solutions are most effective for Infrastructure as a Service (IaaS) versus Software as a Service (SaaS) environments. By mapping techniques to operational contexts, the review reveals methodological gaps, highlights practical deployment challenges, and proposes priorities for future research and cloud-specific security design. Articles Highlights: • Provides a systematic review of EDoS attacks in cloud computing to understand current issues and limitations. • Classifies EDoS defences into four strategic categories to guide future research on key gaps. • Suggests future EDoS research focusing on AI, blockchain, and economic impacts to enhance defence effectiveness.

Item Type:	Article
Identification Number:	10.1007/s43926-025-00183-9
Dates:	Date Event 8 July 2025 Accepted 22 July 2025 Published Online
Uncontrolled Keywords:	Cloud computing, Distributed denial of service, Economic denial of sustainability, Graphical turing test, Machine learning
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions:	Architecture, Built Environment, Computing and Engineering > Computer Science
Depositing User:	Gemma Tonks
Date Deposited:	06 Aug 2025 14:55
Last Modified:	06 Aug 2025 14:55
URI:	https://www.open-access.bcu.ac.uk/id/eprint/16582

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