Matches in SemOpenAlex for { <https://semopenalex.org/work/W3144936410> ?p ?o ?g. }
Showing items 1 to 93 of
93
with 100 items per page.
- W3144936410 startingPage "179" @default.
- W3144936410 abstract "Various Artificial Intelligence (AI) techniques are combined with classic side-channel methods to improve the efficiency of attacks. Among them, Genetic-Algorithms-based Correlation Power Analysis (GA-CPA) is proposed to launch attacks on hardware cryptosystems to extract the secret key efficiently. However, the convergence efficiency of GA-CPA is unsatisfactory due to two problems: the randomly generated initial population generally have low fitness, and the mutation operation in each iteration hardly produces high-quality individuals because of the confusion and diffusion characteristics of S-boxes. In this paper, we propose an analysis framework of GA-CPA which focuses on solving these two problems. First, we explore the list of candidate key bytes which is the result of Correlation Power Analysis (CPA) on a limited number of power traces, so that the population can be initialized with high quality candidates. Second, we improve the mutation operation by guiding the candidate key to mutate in a higher-fitness direction instead of randomly. Third, we make full use of the fitness calculation method and combine it with key enumeration algorithms to further improve the efficiency of key recovery. Simulation experimental results show that our method reduces the number of traces by 33.3% and 43.9% compared to CPA with key enumeration and GA-CPA respectively when the success rate is fixed to 90%. Real experiments performed on SAKURA-G confirm that the number of traces required in our method is much less than the numbers of traces required in CPA and GA-CPA. Besides, we adjust our method to deal with DPA contest v1 dataset, and achieve a better result of 40.76 traces than the winning proposal of 42.42 traces. The computation cost of our proposal is nearly 16.7% of the winner." @default.
- W3144936410 created "2021-04-13" @default.
- W3144936410 creator A5017195907 @default.
- W3144936410 creator A5048770374 @default.
- W3144936410 creator A5061860143 @default.
- W3144936410 creator A5064276936 @default.
- W3144936410 creator A5079565555 @default.
- W3144936410 date "2021-01-01" @default.
- W3144936410 modified "2023-09-26" @default.
- W3144936410 title "Efficient Framework for Genetic-Algorithm-Based Correlation Power Analysis." @default.
- W3144936410 hasPublicationYear "2021" @default.
- W3144936410 type Work @default.
- W3144936410 sameAs 3144936410 @default.
- W3144936410 citedByCount "0" @default.
- W3144936410 crossrefType "posted-content" @default.
- W3144936410 hasAuthorship W3144936410A5017195907 @default.
- W3144936410 hasAuthorship W3144936410A5048770374 @default.
- W3144936410 hasAuthorship W3144936410A5061860143 @default.
- W3144936410 hasAuthorship W3144936410A5064276936 @default.
- W3144936410 hasAuthorship W3144936410A5079565555 @default.
- W3144936410 hasConcept C104317684 @default.
- W3144936410 hasConcept C111919701 @default.
- W3144936410 hasConcept C11413529 @default.
- W3144936410 hasConcept C117220453 @default.
- W3144936410 hasConcept C118615104 @default.
- W3144936410 hasConcept C119857082 @default.
- W3144936410 hasConcept C144024400 @default.
- W3144936410 hasConcept C149923435 @default.
- W3144936410 hasConcept C156340839 @default.
- W3144936410 hasConcept C178489894 @default.
- W3144936410 hasConcept C185592680 @default.
- W3144936410 hasConcept C2524010 @default.
- W3144936410 hasConcept C26517878 @default.
- W3144936410 hasConcept C2908647359 @default.
- W3144936410 hasConcept C33923547 @default.
- W3144936410 hasConcept C38652104 @default.
- W3144936410 hasConcept C41008148 @default.
- W3144936410 hasConcept C43364308 @default.
- W3144936410 hasConcept C501734568 @default.
- W3144936410 hasConcept C55493867 @default.
- W3144936410 hasConcept C6295992 @default.
- W3144936410 hasConcept C8880873 @default.
- W3144936410 hasConceptScore W3144936410C104317684 @default.
- W3144936410 hasConceptScore W3144936410C111919701 @default.
- W3144936410 hasConceptScore W3144936410C11413529 @default.
- W3144936410 hasConceptScore W3144936410C117220453 @default.
- W3144936410 hasConceptScore W3144936410C118615104 @default.
- W3144936410 hasConceptScore W3144936410C119857082 @default.
- W3144936410 hasConceptScore W3144936410C144024400 @default.
- W3144936410 hasConceptScore W3144936410C149923435 @default.
- W3144936410 hasConceptScore W3144936410C156340839 @default.
- W3144936410 hasConceptScore W3144936410C178489894 @default.
- W3144936410 hasConceptScore W3144936410C185592680 @default.
- W3144936410 hasConceptScore W3144936410C2524010 @default.
- W3144936410 hasConceptScore W3144936410C26517878 @default.
- W3144936410 hasConceptScore W3144936410C2908647359 @default.
- W3144936410 hasConceptScore W3144936410C33923547 @default.
- W3144936410 hasConceptScore W3144936410C38652104 @default.
- W3144936410 hasConceptScore W3144936410C41008148 @default.
- W3144936410 hasConceptScore W3144936410C43364308 @default.
- W3144936410 hasConceptScore W3144936410C501734568 @default.
- W3144936410 hasConceptScore W3144936410C55493867 @default.
- W3144936410 hasConceptScore W3144936410C6295992 @default.
- W3144936410 hasConceptScore W3144936410C8880873 @default.
- W3144936410 hasLocation W31449364101 @default.
- W3144936410 hasOpenAccess W3144936410 @default.
- W3144936410 hasPrimaryLocation W31449364101 @default.
- W3144936410 hasRelatedWork W150807089 @default.
- W3144936410 hasRelatedWork W2053245640 @default.
- W3144936410 hasRelatedWork W2056896847 @default.
- W3144936410 hasRelatedWork W2084253837 @default.
- W3144936410 hasRelatedWork W2097485911 @default.
- W3144936410 hasRelatedWork W2181936060 @default.
- W3144936410 hasRelatedWork W2340721073 @default.
- W3144936410 hasRelatedWork W2408429201 @default.
- W3144936410 hasRelatedWork W2471644006 @default.
- W3144936410 hasRelatedWork W2548533766 @default.
- W3144936410 hasRelatedWork W2603200202 @default.
- W3144936410 hasRelatedWork W2733485676 @default.
- W3144936410 hasRelatedWork W2762942147 @default.
- W3144936410 hasRelatedWork W2791620471 @default.
- W3144936410 hasRelatedWork W3025905513 @default.
- W3144936410 hasRelatedWork W3090510908 @default.
- W3144936410 hasRelatedWork W3102142622 @default.
- W3144936410 hasRelatedWork W3161792922 @default.
- W3144936410 hasRelatedWork W3199665208 @default.
- W3144936410 hasRelatedWork W47249848 @default.
- W3144936410 hasVolume "2021" @default.
- W3144936410 isParatext "false" @default.
- W3144936410 isRetracted "false" @default.
- W3144936410 magId "3144936410" @default.
- W3144936410 workType "article" @default.