Secure Data Encryption for Cloud-Based Human Care Services

Joint Authors

Kim, Howon
Park, Taehwan
Seo, Hwajeong
Lee, Sokjoon

Source

Journal of Sensors

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-08-06

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Civil Engineering

Abstract EN

Sensor network services utilize sensor data from low-end IoT devices of the types widely deployed over long distances.

After the collection of sensor data, the data is delivered to the cloud server, which processes it to extract useful information.

Given that the data may contain sensitive and private information, it should be encrypted and exchanged through the network to ensure integrity and confidentiality.

Under these circumstances, a cloud server should provide high-speed data encryption without a loss of availability.

In this paper, we propose efficient parallel implementations of Simeck family block ciphers on modern 64-bit Intel processors.

In order to accelerate the performance, an adaptive encryption technique is also exploited for load balancing of the resulting big data.

Finally, the proposed implementations achieved 3.5 cycles/byte and 4.6 cycles/byte for Simeck32/64 and Simeck64/128 encryption, respectively.

American Psychological Association (APA)

Park, Taehwan& Seo, Hwajeong& Lee, Sokjoon& Kim, Howon. 2018. Secure Data Encryption for Cloud-Based Human Care Services. Journal of Sensors،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1201848

Modern Language Association (MLA)

Park, Taehwan…[et al.]. Secure Data Encryption for Cloud-Based Human Care Services. Journal of Sensors No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1201848

American Medical Association (AMA)

Park, Taehwan& Seo, Hwajeong& Lee, Sokjoon& Kim, Howon. Secure Data Encryption for Cloud-Based Human Care Services. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1201848

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1201848