Adaptive Event‐Driven Key Management for Securing Cloud Data Against Key Exposure

ABSTRACT Ensuring data confidentiality and integrity in dynamic cloud storage environments is a growing challenge, particularly in the face of key exposure threats. Traditional key management schemes, which rely on periodic updates, introduce significant vulnerabilities due to long windows of exposure between key rotations. Also, it often requires high computational overhead from re‐encrypting entire datasets during key updates and frequently depends on third‐party auditors for integrity verification, which can compromise privacy. However, a major research gap remains in developing a scalable, efficient, and auditor‐free key management protocol that can adapt in real time to evolving cloud access patterns. In this paper, we propose a novel Dynamic Event‐Driven Key Regeneration System that leverages Elliptic Curve Diffie‐Hellman (ECDH) for secure key exchange and Advanced Encryption Standard—Galois/Counter Mode (AES‐GCM) for combined encryption and integrity verification. Unlike conventional time‐ or session‐based strategies, the proposed design uses statistically adaptive thresholding derived from real‐time file access patterns to enable on‐demand key regeneration and selective re‐encryption, drastically reducing computational overhead. By re‐encrypting only affected files, the system is optimized for large‐scale, multi‐tenant cloud environments. Furthermore, the proposed approach eliminates the need for external auditors, as integrity verification is performed internally via cryptographic mechanisms, ensuring both privacy and security. Experimental results show that the proposed system achieves an average key generation time of 2.3 ms, encryption latency of just 0.21 s for 100 MB files, and key regeneration times as low as 0.0012–0.0350 s, outperforming existing approaches by up to 80% in computational efficiency. The system scales efficiently in multi‐tenant environments, maintaining low overhead with up to 100 users and providing near‐linear performance even with 1000 concurrent encryption operations. These results demonstrate that the proposed adaptive, event‐driven system offers enhanced protection against key exposure while maintaining low overhead, making it a viable and secure solution for modern cloud infrastructures.

Authors

Institutions

Publication Details

Journal
Concurrency and Computation Practice and Experience
Published
2025-10-02
DOI
https://doi.org/10.1002/cpe.70329
Primary Topic
Cloud Data Security Solutions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adaptive Event‐Driven Key Management for Securing Cloud Data Against Key Exposure

Kriti Bhushan, Atul Kumar Singh
Concurrency and Computation Practice and Experience
Cloud Data Security Solutions
article

Adaptive Event‐Driven Key Management for Securing Cloud Data Against Key Exposure

Kriti Bhushan, Atul Kumar Singh
article en

Abstract

ABSTRACT Ensuring data confidentiality and integrity in dynamic cloud storage environments is a growing challenge, particularly in the face of key exposure threats. Traditional key management schemes, which rely on periodic updates, introduce significant vulnerabilities due to long windows of exposure between key rotations. Also, it often requires high computational overhead from re‐encrypting entire datasets during key updates and frequently depends on third‐party auditors for integrity verification, which can compromise privacy. However, a major research gap remains in developing a scalable, efficient, and auditor‐free key management protocol that can adapt in real time to evolving cloud access patterns. In this paper, we propose a novel Dynamic Event‐Driven Key Regeneration System that leverages Elliptic Curve Diffie‐Hellman (ECDH) for secure key exchange and Advanced Encryption Standard—Galois/Counter Mode (AES‐GCM) for combined encryption and integrity verification. Unlike conventional time‐ or session‐based strategies, the proposed design uses statistically adaptive thresholding derived from real‐time file access patterns to enable on‐demand key regeneration and selective re‐encryption, drastically reducing computational overhead. By re‐encrypting only affected files, the system is optimized for large‐scale, multi‐tenant cloud environments. Furthermore, the proposed approach eliminates the need for external auditors, as integrity verification is performed internally via cryptographic mechanisms, ensuring both privacy and security. Experimental results show that the proposed system achieves an average key generation time of 2.3 ms, encryption latency of just 0.21 s for 100 MB files, and key regeneration times as low as 0.0012–0.0350 s, outperforming existing approaches by up to 80% in computational efficiency. The system scales efficiently in multi‐tenant environments, maintaining low overhead with up to 100 users and providing near‐linear performance even with 1000 concurrent encryption operations. These results demonstrate that the proposed adaptive, event‐driven system offers enhanced protection against key exposure while maintaining low overhead, making it a viable and secure solution for modern cloud infrastructures.

Concurrency and Computation Practice and ExperienceVol. 37(25-26)
National Institute of Technology Kurukshetra (IN)
Openalex Percentile: Top 60%
Cloud Data Security Solutions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.