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Cryptanalysis of ForkAES

  • Subhadeep Banik
  • Jannis Bossert
  • Amit Jana
  • Eik List
  • Stefan Lucks
  • Willi Meier
  • Mostafizar Rahman
  • Dhiman Saha
  • Yu SasakiEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11464)

Abstract

Forkciphers are a new kind of primitive proposed recently by Andreeva et al. for efficient encryption and authentication of small messages. They fork the middle state of a cipher and encrypt it twice under two smaller independent permutations. Thus, forkciphers produce two output blocks in one primitive call.

Andreeva et al. proposed ForkAES, a tweakable AES-based forkcipher that splits the state after five out of ten rounds. While their authenticated encrypted schemes were accompanied by proofs, the security discussion for ForkAES was not provided, and founded on existing results on the AES and KIASU-BC. Forkciphers provide a unique interface called reconstruction queries that use one ciphertext block as input and compute the respective other ciphertext block. Thus, they deserve a careful security analysis.

This work fosters the understanding of the security of ForkAES with three contributions: (1) We observe that security in reconstruction queries differs strongly from the existing results on the AES. This allows to attack nine out of ten rounds with differential, impossible-differential and yoyo attacks. (2) We observe that some forkcipher modes may lack the interface of reconstruction queries, so that attackers must use encryption queries. We show that nine rounds can still be attacked with rectangle and impossible-differential attacks. (3) We present forgery attacks on the AE modes proposed by Andreeva et al. with nine-round ForkAES.

Keywords

Symmetric-key cryptography Cryptanalysis Tweakable block cipher Impossible differential Boomerang Yoyo AE 

Notes

Acknowledgments.

Parts of this work have been initiated during the group sessions of the 8th Asian Workshop on Symmetric Cryptography (ASK 2018) held at the Indian Statistical Institute in Kolkata. We would also like to thank the anonymous reviewers and the designers of ForkAES for their helpful comments. Subhadeep Banik is supported by the Ambizione Grant PZ00P2_179921, awarded by the Swiss National Science Foundation.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Subhadeep Banik
    • 1
  • Jannis Bossert
    • 2
  • Amit Jana
    • 3
  • Eik List
    • 2
  • Stefan Lucks
    • 2
  • Willi Meier
    • 4
  • Mostafizar Rahman
    • 3
  • Dhiman Saha
    • 5
  • Yu Sasaki
    • 6
    Email author
  1. 1.EPFLLausanneSwitzerland
  2. 2.Bauhaus-Universität WeimarWeimarGermany
  3. 3.CSRU, Indian Statistical InstituteKolkataIndia
  4. 4.FHNWWindischSwitzerland
  5. 5.IIT BhilaiRaipurIndia
  6. 6.NTT Secure Platform LaboratoriesTokyoJapan

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