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IoT Expunge: Implementing Verifiable Retention of IoT Data

Authors :
Panwar, Nisha
Sharma, Shantanu
Gupta, Peeyush
Ghosh, Dhrubajyoti
Mehrotra, Sharad
Venkatasubramanian, Nalini
Publication Year :
2020

Abstract

The growing deployment of Internet of Things (IoT) systems aims to ease the daily life of end-users by providing several value-added services. However, IoT systems may capture and store sensitive, personal data about individuals in the cloud, thereby jeopardizing user-privacy. Emerging legislation, such as California's CalOPPA and GDPR in Europe, support strong privacy laws to protect an individual's data in the cloud. One such law relates to strict enforcement of data retention policies. This paper proposes a framework, entitled IoT Expunge that allows sensor data providers to store the data in cloud platforms that will ensure enforcement of retention policies. Additionally, the cloud provider produces verifiable proofs of its adherence to the retention policies. Experimental results on a real-world smart building testbed show that IoT Expunge imposes minimal overheads to the user to verify the data against data retention policies.<br />Comment: This paper has been accepted in 10th ACM Conference on Data and Application Security and Privacy (CODASPY), 2020

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2003.04969
Document Type :
Working Paper
Full Text :
https://doi.org/10.1145/3374664.3375737