Aarhus Universitets segl

Qi Zhang

Energy Concealment based Compressive Sensing Encryption for Perfect Secrecy for IoT

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Standard

Energy Concealment based Compressive Sensing Encryption for Perfect Secrecy for IoT. / Kuldeep, Gajraj; Zhang, Qi.
GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020. IEEE, 2020. 9322181.

Publikation: Bidrag til bog/antologi/rapport/proceedingKonferencebidrag i proceedingsForskningpeer review

Harvard

Kuldeep, G & Zhang, Q 2020, Energy Concealment based Compressive Sensing Encryption for Perfect Secrecy for IoT. i GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020., 9322181, IEEE, 2020 IEEE Global Communications Conference, Taipei, Taiwan, 07/12/2020. https://doi.org/10.1109/GLOBECOM42002.2020.9322181

APA

Kuldeep, G., & Zhang, Q. (2020). Energy Concealment based Compressive Sensing Encryption for Perfect Secrecy for IoT. I GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020 [9322181] IEEE. https://doi.org/10.1109/GLOBECOM42002.2020.9322181

CBE

Kuldeep G, Zhang Q. 2020. Energy Concealment based Compressive Sensing Encryption for Perfect Secrecy for IoT. I GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020. IEEE. Article 9322181. https://doi.org/10.1109/GLOBECOM42002.2020.9322181

MLA

Vancouver

Kuldeep G, Zhang Q. Energy Concealment based Compressive Sensing Encryption for Perfect Secrecy for IoT. I GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020. IEEE. 2020. 9322181 doi: 10.1109/GLOBECOM42002.2020.9322181

Author

Kuldeep, Gajraj ; Zhang, Qi. / Energy Concealment based Compressive Sensing Encryption for Perfect Secrecy for IoT. GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020. IEEE, 2020.

Bibtex

@inproceedings{b9cb83272ff946dab733e8b8dff483e5,
title = "Energy Concealment based Compressive Sensing Encryption for Perfect Secrecy for IoT",
abstract = "Recent study has shown that compressive sensing (CS) based computationally secure scheme using Gaussian or Binomial sensing matrix in resource-constrained IoT devices is vulnerable to ciphertext-only attack. Although the CS-based perfectly secure scheme has no such vulnerabilities, the practical realization of the perfectly secure scheme is challenging, because it requires an additional secure channel to transmit the measurement norm. In this paper, we devise a practical realization of a perfectly secure scheme by concealing energy in which the requirement of an additional secure channel is removed. Since the generation of Gaussian sensing matrices is not feasible in resource-constrained IoT devices, approximate Gaussian sensing matrices are generated using linear feedback shift registers. We also demonstrate the implementation feasibility of the proposed perfectly secure scheme in practice without additional complexity. Furthermore, the security analysis of the proposed scheme is performed and compared with the state-of-the-art compressive sensing based energy obfuscation scheme.",
author = "Gajraj Kuldeep and Qi Zhang",
year = "2020",
doi = "10.1109/GLOBECOM42002.2020.9322181",
language = "English",
booktitle = "GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020",
publisher = "IEEE",
note = "2020 IEEE Global Communications Conference, Globecom ; Conference date: 07-12-2020 Through 11-12-2020",
url = "https://globecom2020.ieee-globecom.org/",

}

RIS

TY - GEN

T1 - Energy Concealment based Compressive Sensing Encryption for Perfect Secrecy for IoT

AU - Kuldeep, Gajraj

AU - Zhang, Qi

PY - 2020

Y1 - 2020

N2 - Recent study has shown that compressive sensing (CS) based computationally secure scheme using Gaussian or Binomial sensing matrix in resource-constrained IoT devices is vulnerable to ciphertext-only attack. Although the CS-based perfectly secure scheme has no such vulnerabilities, the practical realization of the perfectly secure scheme is challenging, because it requires an additional secure channel to transmit the measurement norm. In this paper, we devise a practical realization of a perfectly secure scheme by concealing energy in which the requirement of an additional secure channel is removed. Since the generation of Gaussian sensing matrices is not feasible in resource-constrained IoT devices, approximate Gaussian sensing matrices are generated using linear feedback shift registers. We also demonstrate the implementation feasibility of the proposed perfectly secure scheme in practice without additional complexity. Furthermore, the security analysis of the proposed scheme is performed and compared with the state-of-the-art compressive sensing based energy obfuscation scheme.

AB - Recent study has shown that compressive sensing (CS) based computationally secure scheme using Gaussian or Binomial sensing matrix in resource-constrained IoT devices is vulnerable to ciphertext-only attack. Although the CS-based perfectly secure scheme has no such vulnerabilities, the practical realization of the perfectly secure scheme is challenging, because it requires an additional secure channel to transmit the measurement norm. In this paper, we devise a practical realization of a perfectly secure scheme by concealing energy in which the requirement of an additional secure channel is removed. Since the generation of Gaussian sensing matrices is not feasible in resource-constrained IoT devices, approximate Gaussian sensing matrices are generated using linear feedback shift registers. We also demonstrate the implementation feasibility of the proposed perfectly secure scheme in practice without additional complexity. Furthermore, the security analysis of the proposed scheme is performed and compared with the state-of-the-art compressive sensing based energy obfuscation scheme.

UR - https://ieeexplore.ieee.org/document/9322181

U2 - 10.1109/GLOBECOM42002.2020.9322181

DO - 10.1109/GLOBECOM42002.2020.9322181

M3 - Article in proceedings

BT - GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Taipei, Taiwan, 2020

PB - IEEE

T2 - 2020 IEEE Global Communications Conference

Y2 - 7 December 2020 through 11 December 2020

ER -