Журнал «Труды Института системного анализа Российской академии наук» - M. Maalla "Enhancing Blockchain-Based Access Control Using Probabilistic Filters"

Attribute-Based Access Control (ABAC) in blockchain environments faces challenges in token management, including privacy, storage efficiency, and token lifecycle handling. Storing tokens on-chain compromises privacy and increases costs. This paper introduces a token management system using probabilistic filters, comparing Bloom and Cuckoo filters for efficient token storage and verification. Experiments on the Ethereum testnet show that Cuckoo filters deliver superior performance, with configurable false positive rates as low as 9.54×10-7 and support for lifecycle operations like deletion. The system achieves a 99.8% success rate for basic operations while ensuring efficient gas consumption. Under high load, it handles up to 80 operations per minute with minimal performance degradation. These results demonstrate that probabilistic filters, especially Cuckoo filters, provide an efficient and scalable solution for managing tokens in blockchain-based access control systems.

Полная версия статьи в формате pdf.

PP. 73-82.

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