Fast and Efficient UserID Lookup in Distributed Authentication: A Probabilistic Approach Using Bloom Filters
DOI:
https://doi.org/10.47941/ijce.2124Keywords:
Distributed Systems, User Authentication, Latency Reduction, Probabilistic Data Structures, Cloud ComputingAbstract
Purpose: User authentication in distributed systems presents unique challenges due to the decentralized nature of these environments and the potential for high-volume login attempts. This paper proposes an efficient method for UserID existence checking during the login process using Bloom filters, a space-efficient probabilistic data structure. Our approach aims to reduce authentication latency and minimize network traffic while maintaining a high level of security.
Methodology: We present a novel system architecture that incorporates Bloom filters at strategic points within the distributed system to perform rapid preliminary checks on UserID existence. This method allows for quick rejection of non-existent UserIDs without querying the main user database, significantly reducing the load on central authentication servers. The paper details the implementation of Bloom filters optimized for UserID storage and lookup, including considerations for filter size, hash function selection, and false positive rate management. We also describe the integration of this method into a typical authentication workflow, highlighting the points at which Bloom filter checks are performed and how they interact with existing security measures.
Findings: To evaluate the effectiveness of our approach, we conducted extensive experiments simulating various scales of distributed systems and login attempt patterns. Our results demonstrate that the Bloom filter-based UserID existence checking method reduces authentication latency by an average of 37% compared to traditional database lookup methods. Additionally, we observed a 42% decrease in network traffic related to authentication processes, indicating improved scalability for large-scale distributed systems. The paper also discusses the trade-offs inherent in using probabilistic data structures for security-critical operations, addressing potential vulnerabilities and proposing mitigation strategies. We conclude by outlining future research directions, including adaptive Bloom filter sizing and the potential application of this method to other aspects of distributed system security.
Unique Contribution to Theory, Policy and Practice: This research contributes to the field of distributed systems security by providing a practical, efficient, and scalable solution for UserID existence checking, potentially improving the performance and user experience of large-scale authentication systems.
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Copyright (c) 2024 Purshotam S Yadav
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