Welcome to the resource topic for 2014/542
Title:
On the Multi-output Filtering Model and Its Applications
Authors: Guang Gong, Kalikinkar Mandal, Yin Tan, Teng Wu
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 (LFSR) 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 \T's f_1 algorithm, \AES, \Kasumi and \Present. We demonstrate that the success rate of the attack on \Kasumi and \Present is non-negligible, but f_1 and \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 \Kasumi.
ePrint: https://eprint.iacr.org/2014/542
See all topics related to this paper.
Feel free to post resources that are related to this paper below.
Example resources include: implementations, explanation materials, talks, slides, links to previous discussions on other websites.
For more information, see the rules for Resource Topics .