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Towards a software approach to mitigate correlation power analysis

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dc.contributor.author Frieslaar, I
dc.contributor.author Irwin, B
dc.date.accessioned 2017-01-17T08:59:22Z
dc.date.available 2017-01-17T08:59:22Z
dc.date.issued 2016-07
dc.identifier.citation Frieslaar, I. and Irwin, B. 2016. Towards a software approach to mitigate correlation power analysis. Proceedings of the 13th International Joint Conference on e-Business and Telecommunications, 26-28 July 2016, Lisbon, Portugal. en_US
dc.identifier.isbn 978-989-758-196-0
dc.identifier.uri http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=ATREeXCX/YI=&t=1
dc.identifier.uri http://hdl.handle.net/10204/8912
dc.description Proceedings of the 13th International Joint Conference on e-Business and Telecommunications, 26-28 July 2016, Lisbon, Portugal, pp 403-410. en_US
dc.description.abstract In this research we present a novel implementation for a software countermeasure to mitigate Correlation Power Analysis (CPA). This countermeasure combines pseudo controlled-random dummy code and a task scheduler using multi threads to form dynamic power traces which hides the occurrence of critical operations of the AES-128 algorithm. This work investigates the use of a task scheduler to generate noise at specific areas in the AES-128 algorithm to mitigate the CPA attack. The dynamic power traces have shown to be an effective contermeasure, as it obscures the CPA into predicting the incorrect secret key. Furthermore, the countermeasure is tested on an ATmega and an ATxmega microcontroller. The basic side channel analysis attack resistance has been increased and in both scenarios the countermeasure has reduced the correlation accuracy and forced the CPA to predict the incorect key. The correlation accuracy has decreased from 97.6% to 53.6% on the ATmega microntroller and from 82% to 51.4% on the ATxmega microcontroller. en_US
dc.language.iso en en_US
dc.publisher SCITEPRESS Digital Library en_US
dc.relation.ispartofseries Workflow;17576
dc.subject Software Countermeasure en_US
dc.subject Task Scheduler en_US
dc.subject Correlation Power Analysis en_US
dc.subject CPA en_US
dc.subject Data engineering en_US
dc.title Towards a software approach to mitigate correlation power analysis en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Frieslaar, I., & Irwin, B. (2016). Towards a software approach to mitigate correlation power analysis. SCITEPRESS Digital Library. http://hdl.handle.net/10204/8912 en_ZA
dc.identifier.chicagocitation Frieslaar, I, and B Irwin. "Towards a software approach to mitigate correlation power analysis." (2016): http://hdl.handle.net/10204/8912 en_ZA
dc.identifier.vancouvercitation Frieslaar I, Irwin B, Towards a software approach to mitigate correlation power analysis; SCITEPRESS Digital Library; 2016. http://hdl.handle.net/10204/8912 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Frieslaar, I AU - Irwin, B AB - In this research we present a novel implementation for a software countermeasure to mitigate Correlation Power Analysis (CPA). This countermeasure combines pseudo controlled-random dummy code and a task scheduler using multi threads to form dynamic power traces which hides the occurrence of critical operations of the AES-128 algorithm. This work investigates the use of a task scheduler to generate noise at specific areas in the AES-128 algorithm to mitigate the CPA attack. The dynamic power traces have shown to be an effective contermeasure, as it obscures the CPA into predicting the incorrect secret key. Furthermore, the countermeasure is tested on an ATmega and an ATxmega microcontroller. The basic side channel analysis attack resistance has been increased and in both scenarios the countermeasure has reduced the correlation accuracy and forced the CPA to predict the incorect key. The correlation accuracy has decreased from 97.6% to 53.6% on the ATmega microntroller and from 82% to 51.4% on the ATxmega microcontroller. DA - 2016-07 DB - ResearchSpace DP - CSIR KW - Software Countermeasure KW - Task Scheduler KW - Correlation Power Analysis KW - CPA KW - Data engineering LK - https://researchspace.csir.co.za PY - 2016 SM - 978-989-758-196-0 T1 - Towards a software approach to mitigate correlation power analysis TI - Towards a software approach to mitigate correlation power analysis UR - http://hdl.handle.net/10204/8912 ER - en_ZA


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