Artificial intelligence applied to the identification of Block Ciphers under CBC Mode

Repositório Institucional da Produção Científica da Marinha do Brasil (RI-MB)

Use este identificador para citar ou linkar para este item: https://www.repositorio.mar.mil.br/handle/ripcmb/846594

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Campo DC	Valor	Idioma
dc.contributor.advisor	Xexéo, José Antonio Moreira	pt_BR
dc.contributor.advisor	Torres, Renato Hidaka	pt_BR
dc.contributor.author	Rocha, Bruno dos Santos	-
dc.date.accessioned	2024-01-29T17:42:01Z	-
dc.date.available	2024-01-29T17:42:01Z	-
dc.date.issued	2023	-
dc.identifier.uri	https://www.repositorio.mar.mil.br/handle/ripcmb/846594	-
dc.description	This research introduces a novel methodology for identifying symmetric cryptosystems operating in Cipher Block Chaining (CBC) mode based solely on encrypted texts. The approach combines statistical tests from NIST STS with machine learning algorithms, analyzing DES, 3DES, Blowfish, Camellia, and AES. The experimental results demonstrate an 84% identification rate for multiclass identification using random keys and initialization vectors. These findings are valuable in the field of information security and aid in minimizing cryptanalytic efforts.	pt_BR
dc.language.iso	en	pt_BR
dc.publisher	International Journal of Computer Applications	pt_BR
dc.rights	openAccess	pt_BR
dc.subject	Criptografia	pt_BR
dc.subject	Inteligência artificial	pt_BR
dc.subject	Modo CBC	pt_BR
dc.title	Artificial intelligence applied to the identification of Block Ciphers under CBC Mode	pt_BR
dc.type	article	pt_BR
dc.subject.dgpm	Segurança da informação	pt_BR
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