Abstract
The security of the dynamic heterogeneous redundancy (DHR) architecture relies on the heterogeneity of its executors, which also defines the vulnerability of the mimic system. In order to select executors with reliable and significant dissimilarity as service executors, we propose a DHR executor selection algorithm based on historical credibility and dissimilarity clustering (HCDC), which adds two metrics of executor historical credibility and dissimilarity. First, to maximize the difference between heterogeneous executor pools, clustering is performed based on the dissimilarity of the executor. Second, the executor with the highest historical credibility is selected from the heterogeneous executor pool as the candidate pool. The historical credibility is dynamically updated by the negative feedback control based on the results of the multi-mode adjudicator. Finally, the dynamic scheduling algorithm selects the executors from the candidate pool to form the set of service executors. The simulation results demonstrate that, in comparison to existing methods, the algorithm reduces the attack success rate and average failure rate while increasing system reliability.
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Acknowledgements
This work was supported by National Natural Science Foundation of China (Grant Nos. 62076139, 621762-64), Natural Science Foundation of Jiangsu Province (Higher Education Institutions) (Grant Nos. BK20170900, 19KJB520046, 20KJA520001), Innovative and Entrepreneurial Talents Projects of Jiangsu Province, Jiangsu Planned Projects for Postdoctoral Research Funds (Grant No. 2019K024), Six Talent Peak Projects in Jiangsu Province (Grant No. JY02), Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant Nos. KYCX19_0921, KYCX19_0906), Open Research Project of Zhejiang Lab (Grant No. 2021KF0AB05), and NUPT DingShan Scholar Project and NUPTSF (Grant No. NY219132).
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Shao, S., Ji, Y., Zhang, W. et al. A DHR executor selection algorithm based on historical credibility and dissimilarity clustering. Sci. China Inf. Sci. 66, 212304 (2023). https://doi.org/10.1007/s11432-022-3635-2
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DOI: https://doi.org/10.1007/s11432-022-3635-2