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Data Deletion Scheme Based on Bloom Filter.

EasyChair Preprint no. 9295

5 pagesDate: November 10, 2022


One of the most alluring features of cloud computing is the ability to provide users limitless storage space. Users can therefore send their data to a cloud server, considerably reducing the need for local storage. However, because data ownership and management are separated in cloud storage, customers lose we cannot control the outgoing data, which presents numerous security and privacy issues. The issue of verifiable outsourced data erasure, this is significant yet has received little attention in business and academia, is the subject of this essay. The efficient fine-grained outsourced deletion of data  we suggest is based on Bloom filter and produce storage and deletion results that are both publicly and privately verifiable.

Keyphrases: AWS Lambda, AWS S3, Bloom Filter.

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Atla Naveen and Kokkonda Shiva and V Lavanya},
  title = {Data Deletion Scheme Based on Bloom Filter.},
  howpublished = {EasyChair Preprint no. 9295},

  year = {EasyChair, 2022}}
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