DEDUCT: A Secure Deduplication of Textual Data in Cloud Environments

DEDUCT: A Secure Deduplication of Textual Data in Cloud Environments

Blog Article

The exponential growth of textual data in Vision-and-Language Navigation tasks poses significant challenges for data management in large-scale storage systems.Data deduplication has emerged as a practical strategy for data reduction in large-scale storage systems; however, it has also raised security concerns.This paper introduces DEDUCT, an innovative data deduplication method for textual data.

DEDUCT employs a hybrid approach that combines cloud-side and client-side deduplication mechanisms to achieve high compression rates while maintaining data security.DEDUCT’s click here lightweight preprocessing and client-side deduplication make it suitable for resource-constrained devices like IoT devices.It has also been designed to resist side-channel attacks.

Experimental evaluations on the Touchdown life extension blueberry extract dataset, consisting of human-written navigation instructions for routes, demonstrate the effectiveness of DEDUCT.It achieves compression rates of nearly 66%, significantly reducing storage requirements while preserving the confidentiality of textual data.This substantial reduction in storage demands can lead to significant cost savings and improved efficiency in large-scale data management systems.