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Compressive Sensing based Multi-class Privacy-preserving Cloud Computing

Publikation: Bidrag til bog/antologi/rapport/proceeding › Konferencebidrag i proceedings › Forskning › peer review

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In this paper, we design the multi-class privacy-preserving cloud computing scheme (MPCC) leveraging compressive sensing for compact sensor data representation and secrecy for data encryption. The proposed scheme achieves two-class secrecy, one for superuser who can retrieve the exact sensor data, and the other for semi-authorized user who is only able to obtain the statistical data such as mean, variance, etc. MPCC scheme allows computationally expensive sparse signal recovery to be performed at cloud without compromising the confidentiality of data to the cloud service providers. In this way, it mitigates the issues in data transmission, energy and storage caused by massive IoT sensor data as well as the increasing concerns about IoT data privacy in cloud computing. Compared with the state-of-the-art schemes, we show that MPCC scheme not only has lower computational complexity at the IoT sensor device and data consumer, but also is proved to be secure against ciphertext-only attack.
OriginalsprogEngelsk
Titel2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings
Antal sider6
ForlagIEEE
Udgivelsesår2020
Artikelnummer9348093
ISBN (Elektronisk)9781728182988
DOI
StatusUdgivet - 2020
Begivenhed2020 IEEE Global Communications Conference - Taipei, Taiwan + Online (Hybrid), Taipei, Taiwan
Varighed: 7 dec. 2020 → 11 dec. 2020
https://globecom2020.ieee-globecom.org/

Konference

Konference2020 IEEE Global Communications Conference
LokationTaipei, Taiwan + Online (Hybrid)
LandTaiwan
ByTaipei
Periode07/12/2020 → 11/12/2020
Internetadresse

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