On the Multi-output Filtering Model and Its Applications

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10194)

Abstract

In this paper, we propose a novel technique, called multi-output filtering model, to study the non-randomness property of a cryptographic algorithm such as message authentication codes and block ciphers. A multi-output filtering model consists of a linear feedback shift register and a multi-output filtering function. Our contribution in this paper is twofold. First, we propose an attack technique under IND-CPA using the multi-output filtering model. By introducing a distinguishing function, we theoretically determine the success rate of this attack. In particular, we construct a distinguishing function based on the distribution of the linear complexity of component sequences, and apply it on studying \({\textsf {TUAK}}\)’s \(f_1\) algorithm, \( {\textsf {AES} }\), \( {\textsf {KASUMI} }\), \( {\textsf {PRESENT} }\) and PRINTcipher. We demonstrate that the success rate of the attack on \( {\textsf {KASUMI} }\) and \( {\textsf {PRESENT} }\) is non-negligible, but \(f_1\) and \( {\textsf {AES} }\) are resistant to this attack. Second, we study the distribution of the cryptographic properties of component functions of a random primitive in the multi-output filtering model. Our experiments show some non-randomness in the distribution of algebraic degree and nonlinearity for \( {\textsf {KASUMI} }\).

Keywords

Randomness Distinguishing attack TUAK Linear complexity 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Teng Wu
    • 1
  • Yin Tan
    • 1
  • Kalikinkar Mandal
    • 1
  • Guang Gong
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of WaterlooWaterlooCanada

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