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Novel implementation of memristive systems for data encryption and obfuscation


Du, N; Manjunath, N; Shuai, Y; Bürger, D; Skorupa, I; Schüffny, R; Mayr, C; Basov, D; Di Ventra, M; Schmidt, O; Schmidt, H (2014). Novel implementation of memristive systems for data encryption and obfuscation. Journal of Applied Physics, 115:124501.

Abstract

With the rise of big data handling, new solutions are required to drive cryptographic algorithms for maintaining data security. Here, we exploit the nonvolatile, nonlinear resistance change in BiFeO3 memristors [Shuai et al., J. Appl. Phys. 109, 124117 (2011)] by applying a voltage for the generation of second and higher harmonics and develop a new memristor-based encoding system from it to encrypt and obfuscate data. It is found that a BiFeO3 memristor in high and low resistance state can be used to generate two clearly distinguishable sets of second and higher harmonics as recently predicted theoretically [Cohen et al., Appl. Phys. Lett. 100, 133109 (2012)]. The computed autocorrelation of encrypted data using higher harmonics generated by a BiFeO3 memristor shows that the encoded data distribute randomly.

Abstract

With the rise of big data handling, new solutions are required to drive cryptographic algorithms for maintaining data security. Here, we exploit the nonvolatile, nonlinear resistance change in BiFeO3 memristors [Shuai et al., J. Appl. Phys. 109, 124117 (2011)] by applying a voltage for the generation of second and higher harmonics and develop a new memristor-based encoding system from it to encrypt and obfuscate data. It is found that a BiFeO3 memristor in high and low resistance state can be used to generate two clearly distinguishable sets of second and higher harmonics as recently predicted theoretically [Cohen et al., Appl. Phys. Lett. 100, 133109 (2012)]. The computed autocorrelation of encrypted data using higher harmonics generated by a BiFeO3 memristor shows that the encoded data distribute randomly.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2014
Deposited On:24 Feb 2015 16:30
Last Modified:08 Dec 2017 11:36
Publisher:American Institute of Physics
Series Name:Journal of Applied Physics
ISSN:0021-8979
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1063/1.4869262

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