Further Hidden Markov model cryptanalysis

Green, PJ; Noad, R; Smart, NP

Further Hidden Markov model cryptanalysis

Green, PJ

Noad, R Smart, NP

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science, 2005, 3659 pp. 61 - 74
Issue Date:: 2005-11-07

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Field	Value	Language
dc.contributor.author	Green, PJ https://orcid.org/0000-0002-4367-4756	en_US
dc.contributor.author	Noad, R	en_US
dc.contributor.author	Smart, NP	en_US
dc.date.issued	2005-11-07	en_US
dc.identifier.citation	Lecture Notes in Computer Science, 2005, 3659 pp. 61 - 74	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16070
dc.description.abstract	We extend the model of Karlof and Wagner for modelling side channel attacks via Input Driven Hidden Markov Models (IDHMM) to the case where not every state corresponds to a single observable symbol. This allows us to examine algorithms where errors in measurements can occur between sub-operations, e.g. there may be an error probability of distinguishing an add (A) versus a double (D) for an elliptic curve system. The prior work of Karlof and Wagner would assume the error was between distinguishing an add-double (AD) versus a double (D). Our model also allows the modelling of unknown values, where one is unable to determine whether a given observable is add or double, and is the first model to allow one to analyse incomplete traces. Hence, our extension allows a more realistic modelling of real side channel attacks. In addition we look at additional heuristic approaches to combine multiple traces together so as to deduce further information. © International Association for Cryptologic Research 2005.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Further Hidden Markov model cryptanalysis	en_US
dc.type	Conference Proceeding
utslib.citation.volume	3659	en_US
utslib.for	0104 Statistics	en_US
dc.location.activity	Edinburgh, UK	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	3659	en_US

Abstract:

We extend the model of Karlof and Wagner for modelling side channel attacks via Input Driven Hidden Markov Models (IDHMM) to the case where not every state corresponds to a single observable symbol. This allows us to examine algorithms where errors in measurements can occur between sub-operations, e.g. there may be an error probability of distinguishing an add (A) versus a double (D) for an elliptic curve system. The prior work of Karlof and Wagner would assume the error was between distinguishing an add-double (AD) versus a double (D). Our model also allows the modelling of unknown values, where one is unable to determine whether a given observable is add or double, and is the first model to allow one to analyse incomplete traces. Hence, our extension allows a more realistic modelling of real side channel attacks. In addition we look at additional heuristic approaches to combine multiple traces together so as to deduce further information. © International Association for Cryptologic Research 2005.

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http://hdl.handle.net/10453/16070