M. Eugenia Pazo-Robles
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
M. Eugenia Pazo-Robles has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Amparo Fúster-Sabater
Instituto de Tecnologías Físicas y de la Información, C.S.I.C.
3 shared publications - Pino Caballero-Gil
Universidad de La Laguna
3 shared publications - Amparo Fúster-Sabater
Instituto de Tecnologías Físicas y de la Información, Consejo Superior de Investigaciones Científicas, Madrid, Spain
1 shared publication
Latest Publications
- Open Access
Security Analysis of the Symmetric Cryptosystem TinyJambu
Symmetric cryptography provides the best examples of cryptosystems to be applied in lightweight environments (e.g., IoT). A representative example is the cryptosystem TinyJambu, one of the ten finalists in the NIST Lightweight Cryptography Standardization Project. It is an authentication encryption with associated data scheme that is extremely lightweight and fast. In this work, we analyze the security of TinyJambu from two distinct and non-symmetric points of view: (1) the improvement of the best cryptanalytical attack found in the literature and (2) a randomness analysis of the generated sequences. Concerning item (1), we launched a differential forgery attack with probability 2−65.9487, which was improved considerably compared with previous numerical results. Concerning item (2), we analyzed the degree of randomness of the TinyJambu keystream sequences with a complete and powerful battery of statistical tests. This non-symmetric study shows the weakness of TinyJambu against cryptanalytic attacks as well as the strength of TinyJambu against statistical analysis.
Open AccessSecurity Analysis of the Symmetric Cryptosystem TinyJambu
Symmetric cryptography provides the best examples of cryptosystems to be applied in lightweight environments (e.g., IoT). A representative example is the cryptosystem TinyJambu, one of the ten finalists in the NIST Lightweight Cryptography Standardization Project. It is an authentication encryption with associated data scheme that is extremely lightweight and fast. In this work, we analyze the security of TinyJambu from two distinct and non-symmetric points of view: (1) the improvement of the best cryptanalytical attack found in the literature and (2) a randomness analysis of the generated sequences. Concerning item (1), we launched a differential forgery attack with probability 2−65.9487, which was improved considerably compared with previous numerical results. Concerning item (2), we analyzed the degree of randomness of the TinyJambu keystream sequences with a complete and powerful battery of statistical tests. This non-symmetric study shows the weakness of TinyJambu against cryptanalytic attacks as well as the strength of TinyJambu against statistical analysis.
- Open Access
Using Linear Difference Equations to Model Nonlinear Cryptographic Sequences
A new class of linear sequence generators based on cellular automata is here introduced in order to model several nonlinear keystream generators with practical applications in symmetric cryptography. The output sequences are written as solutions of linear difference equations, and three basic properties (period, linear complexity and number of different output sequences) are analyzed.
Open AccessUsing Linear Difference Equations to Model Nonlinear Cryptographic Sequences
A new class of linear sequence generators based on cellular automata is here introduced in order to model several nonlinear keystream generators with practical applications in symmetric cryptography. The output sequences are written as solutions of linear difference equations, and three basic properties (period, linear complexity and number of different output sequences) are analyzed.
- 1 April 2010
- Published by Elsevier in Neural Networks
- Vol. 23 (3) , 461-464
A simple linearization of the self-shrinking generator by means of cellular automata
- 1 April 2010
- Published by Elsevier in Neural Networks
- Vol. 23 (3) , 461-464
A simple linearization of the self-shrinking generator by means of cellular automata