Abstract In this digital world, information evolves from several sources like social media, e-commerce sites, and mobile networks, etc., in large volumes for processing. The sensitiveness in the form of rules extracted from different resources entails that privacy-preserving is a significant research issue to be cared for. In this context, it is imperative to impose confidentiality on sensitive rule data during its processing. Optimization algorithms play a vital role in the reduction of ghost rules and lost rules in association rule hiding. This paper proposes a novel Hybrid optimization algorithm that acquires the characteristics of the above-said algorithms for association rule hiding and it has been shown that it produces better results in less time. Further, the newly introduced concepts on the lost rule generation and recovery are seen to produce almost 99% of lost rules with a reduction in side effect factors from 24–5%.

中文翻译：

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使用混合优化算法提高关联规则隐藏的性能

摘要在这个数字世界中，信息从社交媒体，电子商务站点和移动网络等多种来源中大量发展而来，以进行处理。从不同资源中提取的规则形式的敏感性意味着，隐私保护是需要关注的重要研究问题。在这种情况下，必须在敏感规则数据的处理过程中对其进行保密。优化算法在减少关联规则隐藏中的重影规则和丢失规则方面起着至关重要的作用。提出了一种新颖的混合优化算法，该算法获得了上述关联规则隐藏算法的特点，并证明了在较短的时间内产生较好的结果。进一步，