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Evaluating the efficacy of cloud workload protection platforms in hybrid and multicloud environments Cover

Evaluating the efficacy of cloud workload protection platforms in hybrid and multicloud environments

Open Access
|Feb 2026

Figures & Tables

Figure 1:

The proposed approach of CWPP with dynamic threat intelligence and adaptive policy enforcement. CSPM, cloud security posture management; CWPP, cloud workload protection platforms.
The proposed approach of CWPP with dynamic threat intelligence and adaptive policy enforcement. CSPM, cloud security posture management; CWPP, cloud workload protection platforms.

Figure 2:

Attack volume rate detected at a particular time stamp. DDoS, distributed denial of service.
Attack volume rate detected at a particular time stamp. DDoS, distributed denial of service.

Figure 3:

L7 attack volume.
L7 attack volume.

Figure 4:

L3/L4 attack volume.
L3/L4 attack volume.

Figure 5:

Network layer attack distribution.
Network layer attack distribution.

Figure 6:

Mitigated traffic source. DDoS, distributed denial of service.
Mitigated traffic source. DDoS, distributed denial of service.

Comparison of proposed CWPP with existing research approaches

MetricExisting CWPP-A [24]Existing CWPP-B [25]Proposed CWPP framework
Threat detection accuracy (%)82.486.194.7
False positive rate (%)9.57.83.2
Average response time (ms)620480310
Policy adaptation time (ms)750540320
CPU utilization (%)423833
Memory utilization (%)484436

Comparative table: Traditional CWPP vs AI-enhanced CWPP vs proposed CWPP

FeatureTraditional CWPPsAI-enhanced CWPPsProposed CWPP framework
Deployment modelStatic, single-cloudHybrid/multicloud (limited support)Fully hybrid and multicloud optimized
Threat intelligenceStatic signatures, manual updatesSome support for dynamic feedsReal-time dynamic threat feeds + ML-based anomaly detection
Policy enforcementRule-based, manually triggeredSemi-automatedFully adaptive, real-time policy enforcement
Cryptographic integrationAES/RSA-based (general)Not typically integratedECC-based HE for secure key management
Automation levelMinimalModerateHigh automation with minimal manual intervention
Integration with legacy systemsPoorModerateSeamless integration supported
Scalability (multicloud)LimitedModerateHighly scalable with data-aware orchestration
False positive managementHighImproved with MLReduced significantly via contextual intelligence
Test environmentSimulated (CloudSim or similar)Mostly testbed or emulatedReal-time deployment on AWS and SSD Nodes
Evaluation metrics usedLimited (qualitative or basic)Some quantitative analysisComprehensive (detection accuracy, response time, etc.)

j_ijssis-2026-0012_tab_003

TermExplanation
CWPPCloud Workload Protection Platform; secures workloads, such as VMs, containers, and serverless functions across any cloud.
CSPMCloud Security Posture Management; identifies misconfigurations and compliance issues in cloud infrastructure.
Cloud WorkloadsApplications, services, or processes running on cloud infrastructure, often distributed across locations.
OrchestrationAutomated coordination and management of cloud resources, services, and workloads for efficiency and scalability.
Hybrid cloudA mix of on-premise infrastructure and public/private cloud services, working together seamlessly.
MulticloudUse of multiple cloud service providers to avoid vendor lock-in and enhance flexibility and reliability.
MultitenantA single cloud environment serving multiple customers (tenants) with shared infrastructure but isolated data.
Single-tenantA dedicated cloud environment for one customer, offering better control and data isolation.
Zero trustA security model where no entity is trusted by default, requiring continuous verification of identity and access.
Language: English
Submitted on: Feb 25, 2025
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Published on: Feb 20, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2026 R. Prithviraj, R. Saminathan, R. Manishankar, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.