Fast Software AES Encryption View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2010

AUTHORS

Dag Arne Osvik , Joppe W. Bos , Deian Stefan , David Canright

ABSTRACT

This paper presents new software speed records for AES-128 encryption for architectures at both ends of the performance spectrum. On the one side we target the low-end 8-bit AVR microcontrollers and 32-bit ARM microprocessors, while on the other side of the spectrum we consider the high-performing Cell broadband engine and NVIDIA graphics processing units (GPUs). Platform specific techniques are detailed, explaining how the software speed records on these architectures are obtained. Additionally, this paper presents the first AES decryption implementation for GPU architectures. More... »

PAGES

75-93

References to SciGraph publications

  • 2002. The Design of Rijndael, AES — The Advanced Encryption Standard in NONE
  • 2008. New AES Software Speed Records in PROGRESS IN CRYPTOLOGY - INDOCRYPT 2008
  • 2008. Boosting AES Performance on a Tiny Processor Core in TOPICS IN CRYPTOLOGY – CT-RSA 2008
  • 2004. Strong Authentication for RFID Systems Using the AES Algorithm in CRYPTOGRAPHIC HARDWARE AND EMBEDDED SYSTEMS - CHES 2004
  • 2006-05-17. A fast new DES implementation in software in FAST SOFTWARE ENCRYPTION
  • 2009. Faster and Timing-Attack Resistant AES-GCM in CRYPTOGRAPHIC HARDWARE AND EMBEDDED SYSTEMS - CHES 2009
  • 2009. Distinguisher and Related-Key Attack on the Full AES-256 in ADVANCES IN CRYPTOLOGY - CRYPTO 2009
  • 2007. Symmetric Key Cryptography on Modern Graphics Hardware in ADVANCES IN CRYPTOLOGY – ASIACRYPT 2007
  • 2009. Related-Key Cryptanalysis of the Full AES-192 and AES-256 in ADVANCES IN CRYPTOLOGY – ASIACRYPT 2009
  • Book

    TITLE

    Fast Software Encryption

    ISBN

    978-3-642-13857-7
    978-3-642-13858-4

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-13858-4_5

    DOI

    http://dx.doi.org/10.1007/978-3-642-13858-4_5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1046316812


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