Data splitting preserves privacy by partitioning data into various fragments to be stored remotely and shared. It supports most data operations because data can be stored in clear as opposed to methods that rely on cryptography. However, majority of existing data splitting techniques do not consider data already in the multi-cloud. This leads to unnecessary use of resources to re-split data into fragments. This work proposes a data splitting framework that leverages on existing data in the multi-cloud. It improves data splitting mechanisms by reducing the number of splitting operations and resulting fragments. Therefore, decreasing the number of storage locations a data owner manages. Broadcasts queries locate third-party data fragments to avoid costly operations when splitting data. This work examines considerations for the use of third-party fragments and application to existing data splitting techniques. The proposed framework was also applied to an existing data splitting mechanism to complement its capabilities.

翻译：数据分解通过将数据分解成各种碎片以远程储存和共享来维护隐私,它支持大多数数据操作,因为数据可以清晰地储存,而不是使用加密方法;然而,大多数现有数据分解技术并不考虑多层中的数据,这导致不必要地使用资源将数据分解成碎片;这项工作提议了一个数据分解框架,利用多层中的现有数据;它通过减少分解操作和由此产生的碎片来改进数据分解机制;因此,减少数据所有人管理的储存地点的数量;广播查询如何找到第三方数据碎片,以避免在数据分解时花费昂贵的操作;这项工作审查了第三方碎片的使用考虑和对现有数据分解技术的应用;拟议框架还适用于现有数据分解机制,以补充其能力。