Lightweight Traceable Data Circulation Encryption Scheme for Edge Computing

ABSTRACT With the increasing demand for secure and efficient data circulation in edge computing environments, ensuring data privacy, integrity, and traceability has become a critical challenge. In such decentralized and untrusted settings, traditional encryption schemes often suffer from key management complexity, single points of failure, and high computational costs. To address these issues, this paper proposes a lightweight and traceable data circulation encryption (LTP‐CLE) scheme tailored for edge computing scenarios. The scheme leverages certificateless encryption to eliminate the dependency on a trusted key generation center (KGC), and integrates a proxy re‐encryption mechanism and a digital signature scheme using a unified key structure. This unified design not only enhances security and traceability but also reduces key management overhead. Furthermore, the scheme minimizes the use of expensive cryptographic operations, such as bilinear pairings and scalar multiplications, thereby improving computational efficiency. Security analysis in the random oracle model demonstrates the scheme's resistance to collision attacks, ciphertext indistinguishability, and signature forgery. Experimental evaluations show that the LTP‐CLE scheme outperforms existing methods in both computational and communication efficiency, making it well‐suited for practical deployment in data‐centric edge computing applications such as IoT‐based healthcare monitoring, industrial control, and smart city infrastructure.

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Publication Details

Journal
Concurrency and Computation Practice and Experience
Published
2025-09-25
DOI
https://doi.org/10.1002/cpe.70294
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
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article

Lightweight Traceable Data Circulation Encryption Scheme for Edge Computing

Miao Li, Hanlin Tang, Tao Zhang, Changgen Peng et al.
Concurrency and Computation Practice and Experience
Cryptography and Data Security
article

Lightweight Traceable Data Circulation Encryption Scheme for Edge Computing

Miao Li, Hanlin Tang, Tao Zhang, Changgen Peng, Hai Liu, Jin Niu, Chuanda Cai
article en

Abstract

ABSTRACT With the increasing demand for secure and efficient data circulation in edge computing environments, ensuring data privacy, integrity, and traceability has become a critical challenge. In such decentralized and untrusted settings, traditional encryption schemes often suffer from key management complexity, single points of failure, and high computational costs. To address these issues, this paper proposes a lightweight and traceable data circulation encryption (LTP‐CLE) scheme tailored for edge computing scenarios. The scheme leverages certificateless encryption to eliminate the dependency on a trusted key generation center (KGC), and integrates a proxy re‐encryption mechanism and a digital signature scheme using a unified key structure. This unified design not only enhances security and traceability but also reduces key management overhead. Furthermore, the scheme minimizes the use of expensive cryptographic operations, such as bilinear pairings and scalar multiplications, thereby improving computational efficiency. Security analysis in the random oracle model demonstrates the scheme's resistance to collision attacks, ciphertext indistinguishability, and signature forgery. Experimental evaluations show that the LTP‐CLE scheme outperforms existing methods in both computational and communication efficiency, making it well‐suited for practical deployment in data‐centric edge computing applications such as IoT‐based healthcare monitoring, industrial control, and smart city infrastructure.

Concurrency and Computation Practice and ExperienceVol. 37(23-24)
Guizhou University (CN), Changzhou Vocational Institute of Light Industry (CN), Guizhou Aerospace Power Science & Tech (China) (CN)
Openalex Percentile: Top 86%
Cryptography and Data Security
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Lightweight Traceable Data Circulation Encryption Scheme for Edge Computing — Miao Li, Hanlin Tang, et al. · Concurrency and Computation Practice and Experience (2025) | TGRS Research Map | TGRS