CD-KLM: A Secure Storage Architecture for Agricultural Big Data
Year: 2026
Type: preprint
Abstract: With the development of smart agriculture, agricultural big data typically exhibit characteristics such as long-term accumulation and multi-source heterogeneity, which place higher demands on secure storage and sustained decryptability in long-running environments. To address this issue, this paper proposes CD-KLM, a secure storage architecture for Hadoop-based agricultural big data platforms. Specifically, we adopt a client-driven, server-lightweight-collaborative design, in which the reading and decryption capabilities of historical files are independently controlled by the client, while the server only issues collaborative salt values to authenticated clients during new-file creation. On this basis, a dynamic working-key derivation mechanism is designed based on HKDF and file-related contextual information, so that working keys no longer need to be persistently stored over the long term, thereby reducing the risk of malicious data decryption caused by prolonged exposure of critical key material. Meanwhile, threshold-based key recovery is unified at the root-key level, enabling the system to restore its overall decryption capability even when critical keys are damaged or lost. Experimental results in a Hadoop distributed environment show that, while ensuring key recoverability and continuous decryptability, the proposed architecture imposes only a low impact on system throughput, making it suitable for long-running secure storage scenarios for agricultural big data.
Source: Preprints.org
Authors: Bochun Cao, Hanbing Deng, Yuncheng Zhou, Teng Miao
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W7213553318