NDLI: Security analysis of neural cryptography implementation

Content Provider	IEEE Xplore Digital Library
Author	Allam, A.M. Abbas, H.M. El-Kharashi, M.W.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. & Syst. Eng., Ain Shams Univ., Cairo, Egypt (Allam, A.M.; El-Kharashi, M.W.) \|\| Fac. of Media Eng. & Technol., German Univ. in Cairo, Cairo, Egypt (Abbas, H.M.)
Abstract	Neural cryptography is a recent approach that aims to solve the key exchange problem with non classical computing through neural networks training on the same input patterns. Recently, there is a great interest in the cryptographic community to study the security of implementations of cryptographic protocols. Timing analysis and power analysis are the most known and successful mechanisms to obtain information about the protocols secret parameters without the need to solve a hard problem. Some parts of the circuits needed for the protocol are implemented and synthesized in VHDL. HSPICE simulator is used to measure the power consumption with different inputs. In this paper, the information leakage through the learning process is investigated. It is also shown how this information can be used to reduce the complexity of the genetic attack, a neural cryptography known attack strategy. To overcome these vulnerabilities some solutions are proposed to make the neural key exchange protocol immune against this simple power analysis attack. In addition, Trojan insertion attacks are introduced.
Starting Page	195
Ending Page	199
File Size	206029
Page Count	5
File Format	PDF
ISBN	9781479915019
ISSN	21545952
DOI	10.1109/PACRIM.2013.6625473
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cryptography Protocols Vectors Power demand Training Complexity theory Ring oscillators
Content Type	Text
Resource Type	Article

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