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Investigation of Sample Sizes and Correlation in Multi-Cluster Feature Distributions for an Efficient Encryption System

Papoutsis, Evangelos and Howells, Gareth and Hopkins, Andrew B.T. and McDonald-Maier, Klaus D. (2008) Investigation of Sample Sizes and Correlation in Multi-Cluster Feature Distributions for an Efficient Encryption System. In: Keymeulen, Didier and Arslan, Tughrul and Seuss, Martin and Stoica, Adrian and Erdogan, Ahmet T. and Merodio, David, eds. 2008 NASA/ESA Conference on Adaptive Hardware and Systems. IEEE, pp. 409-415. ISBN 978-0-7695-3166-3. (doi:10.1109/AHS.2008.32) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/AHS.2008.32

Abstract

This paper investigates some practical aspects of the employment of measurable features derived from characteristics of given integrated electronic circuits for the generation of encryption keys pertaining to the circuits, a technique termed ICmetrics. Specifically the paper addresses difficulties introduced by features exhibiting highly diverse distributions, potentially containing many distinct clusters associated with each of the given circuits. For such feature distributions, it is crucial to detect the precise number of clusters associated with each given circuit and the paper discusses the consequentially crucial importance of selecting the appropriate number of samples in order to correctly detect and identify the number of clusters. Moreover, the phenomenon of correlation in multi-cluster features is analyzed and methods of how to successively detect it are presented.

Item Type: Book section
DOI/Identification number: 10.1109/AHS.2008.32
Uncontrolled keywords: feature extraction; correlation; cryptography; distance measurement; security; detection algorithms; decorrelation
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: J. Harries
Date Deposited: 21 Apr 2009 08:50 UTC
Last Modified: 17 Sep 2019 14:50 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/15488 (The current URI for this page, for reference purposes)
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