CDGeB: Cloud Data Geolocation Benchmark

Adi Offer, Aviram Zilberman, Asaf Shabtai, Yuval Elovici, Rami Puzis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Cloud computing has revolutionized data processing and management, offering flexible and scalable infrastructure for the distribution of content, computing power, and services across the globe. Dynamic, flexible, and transparent reallocation of resources increases cloud-based services' use and effectiveness. As rates of cloud adoption soar, privacy regulations, and geopolitical security introduce new challenges, which include the assessment, validation, and enforcement of data geolocation. However, currently, there is no standardized benchmark for this research domain. Therefore, this paper presents a novel dataset of measurements specifically designed to evaluate cloud data geolocation algorithms. In addition to its beneficial role in evaluating data geolocation algorithms, our dataset can be used for other data geolocation subtopics.

Original languageEnglish
Title of host publicationCCSW 2023 - Proceedings of the 2023 Cloud Computing Security Workshop
PublisherAssociation for Computing Machinery, Inc
Pages69-74
Number of pages6
ISBN (Electronic)9798400702594
DOIs
StatePublished - 26 Nov 2023
Event14th Anniversary Cloud Computing Security Workshop, CCSW 2023 - Copenhagen, Denmark
Duration: 26 Nov 2023 → …

Publication series

NameCCSW 2023 - Proceedings of the 2023 Cloud Computing Security Workshop

Conference

Conference14th Anniversary Cloud Computing Security Workshop, CCSW 2023
Country/TerritoryDenmark
CityCopenhagen
Period26/11/23 → …

Keywords

  • cloud
  • data geolocation
  • geolocation

ASJC Scopus subject areas

  • Computer Networks and Communications

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