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dc.contributor.authorOu, Changhaien_US
dc.contributor.authorLam, Siew-Keien_US
dc.contributor.authorJiang, Guiyuanen_US
dc.identifier.citationOu, C., Lam, S. & Jiang, G. (2020). The science of guessing in collision-optimized divide-and-conquer attacks. IEEE Transactions On Computer-Aided Design of Integrated Circuits and Systems, 40(6), 1039-1051.
dc.description.abstractRecovering keys ranked in very deep candidate space efficiently is a very important but challenging issue in side-channel attacks (SCAs). State-of-the-art collision-optimized divide-and-conquer attacks (CODCAs) extract collision information from a collision attack to optimize the key recovery of a divide-and-conquer attack, and transform the very huge guessing space to a much smaller collision space. However, the inefficient collision detection makes them time consuming. The very limited collisions exploited and large performance difference between the collision attack and the divide-and-conquer attack in CODCAs also prevent their application in much larger spaces. In this article, we propose a Minkowski distance enhanced collision attack (MDCA) with performance closer to template attack (TA) compared to traditional correlation-enhanced collision attack (CECA), thus making the optimization more practical and meaningful. Next, we build a more advanced CODCA named full-collision chain (FCC) from TA and MDCA to exploit all collisions. Moreover, to minimize the thresholds while guaranteeing a high success probability of key recovery, we propose a fault-tolerant scheme to optimize FCC. The full key is divided into several big 'blocks,' on which a fault-tolerant vector (FTV) is exploited to flexibly adjust its chain space. Finally, guessing theory is exploited to optimize thresholds determination and search order of subkeys. Experimental results show that FCC notably outperforms the existing CODCAs.en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.relation.ispartofIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systemsen_US
dc.rights© 2020 IEEE. All rights reserved.en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleThe science of guessing in collision-optimized divide-and-conquer attacksen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.contributor.researchHardware & Embedded Systems Lab (HESL)en_US
dc.subject.keywordsCollision Attacken_US
dc.subject.keywordsDivide and Conqueren_US
dc.description.acknowledgementThis work was supported in part by the National Research Foundation Singapore Under Its Campus for Research Excellence and Technological Enterprise Programme with the Technical University of Munich at TUMCREATE.en_US
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