SecLoc: Securing location-sensitive storage in the cloud

Jingwei Li, Anna Squicciarini, Dan Lin, Shuang Liang, Chunfu Jia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Cloud computing offers a wide array of storage services. While enjoying the benefits of flexibility, scalability and reliability brought by the cloud storage, cloud users also face the risk of losing control of their own data, in partly because they do not know where their data is actually stored. This raises a number of security and privacy concerns regarding one's sensitive data such as health records. For example, according to Canadian laws, data related to personal identifiable information must be stored within Canada. Nevertheless, in contrast to the urgent demands, privacy requirements regarding to cloud storage locations have not been well investigated in the current cloud computing market, fostering security and privacy concerns among potential adopters. Aiming at addressing this emerging critical issue, we propose a novel secure location-sensitive storage framework, called SecLoc, which offers protection for cloud users' data following the storage location restrictions, with minimum management overhead to existing cloud storage services. We conduct security analysis, complexity analysis and experimental evaluation on the proposed SecLoc system. Our results demonstrate both effectiveness and efficiency of our mechanism.

Original languageEnglish (US)
Title of host publicationSACMAT 2015 - Proceedings of the 20th ACM Symposium on Access Control Models and Technologies
PublisherAssociation for Computing Machinery
Pages51-61
Number of pages11
ISBN (Electronic)9781450335560
DOIs
StatePublished - Jun 1 2015
Event20th ACM Symposium on Access Control Models and Technologies, SACMAT 2015 - Vienna, Austria
Duration: Jun 1 2015Jun 3 2015

Publication series

NameProceedings of ACM Symposium on Access Control Models and Technologies, SACMAT
Volume2015-June

Other

Other20th ACM Symposium on Access Control Models and Technologies, SACMAT 2015
CountryAustria
CityVienna
Period6/1/156/3/15

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality
  • Information Systems

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  • Cite this

    Li, J., Squicciarini, A., Lin, D., Liang, S., & Jia, C. (2015). SecLoc: Securing location-sensitive storage in the cloud. In SACMAT 2015 - Proceedings of the 20th ACM Symposium on Access Control Models and Technologies (pp. 51-61). (Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT; Vol. 2015-June). Association for Computing Machinery. https://doi.org/10.1145/2752952.2752965