Revisiting Compressive Sensing based Encryption Schemes for IoT

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Compressive sensing (CS) is regarded as one of the promising solutions for IoT data encryption as it achieves simultaneous sampling, compression, and encryption. Theoretical work in the literature has proved that CS provides computational secrecy. It also provides asymptotic perfect secrecy for Gaussian sensing matrix with constraints on input signal. In this paper, we design an attack decoding algorithm based on block compressed sensing decoding algorithm to perform ciphertext-only attack on real-life time series IoT data. It shows that it is possible to retrieve vital information in the plaintext under some conditions. Furthermore, it is also applied to a State-of-the Art CS-based encryption scheme for smart grid, and the power profile is reconstructed using ciphertext-only attack. Additionally, the statistical analysis of Gaussian and Binomial measurements is conducted to investigate the randomness provided by them.

Original languageEnglish
Title of host publication2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Proceedings
Number of pages6
Publication year2020
Article number9120785
ISBN (Electronic)9781728131061
Publication statusPublished - 2020
EventIEEE Wireless Communications and Networking Conference 2020 - Internet (Virtual Conference)
Duration: 25 May 202028 May 2020


ConferenceIEEE Wireless Communications and Networking Conference 2020
LocationInternet (Virtual Conference)

    Research areas

  • IoT, compressed sensing, computational secrecy, encryption, time series data

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