Improved guess-and-determine and distinguishing attacks on SNOW-V
In this paper, we investigate the security of SNOW-V, demonstrating two guess-and-determine (GnD) attacks against the full version with complexities 2384 and 2378, respectively, and one distinguishing attack against a reduced variant with complexity 2303. Our GnD attacks use enumeration with recursion to explore valid guessing paths, and try to truncate as many invalid guessing paths as possible at early stages of the recursion by carefully designing the order of guessing. In our first GnD attack, we guess three 128-bit state variables, determine the remaining four according to four consecutive keystream words. We finally use the next three keystream words to verify the correct guess. The second GnD attack is similar but exploits one more keystream word as side information helping to truncate more guessing paths. Our distinguishing attack targets a reduced variant where 32-bit adders are replaced with exclusive-OR operations. The samples can be collected from short keystream sequences under different (key, IV) pairs. These attacks do not threaten SNOW-V, but provide more in-depth details for understanding its security and give new ideas for cryptanalysis of other ciphers.
Vectorized linear approximations for attacks on SNOW 3G 📺
SNOW 3G is a stream cipher designed in 2006 by ETSI/SAGE, serving in 3GPP as one of the standard algorithms for data confidentiality and integrity protection. It is also included in the 4G LTE standard. In this paper we derive vectorized linear approximations of the finite state machine in SNOW3G. In particular,we show one 24-bit approximation with a bias around 2−37 and one byte-oriented approximation with a bias around 2−40. We then use the approximations to launch attacks on SNOW 3G. The first approximation is used in a distinguishing attack resulting in an expected complexity of 2172 and the second one can be used in a standard fast correlation attack resulting in key recovery in an expected complexity of 2177. If the key length in SNOW 3G would be increased to 256 bits, the results show that there are then academic attacks on such a version faster than the exhaustive key search.
Spectral analysis of ZUC-256 📺
In this paper we develop a number of generic techniques and algorithms in spectral analysis of large linear approximations for use in cryptanalysis. We apply the developed tools for cryptanalysis of ZUC-256 and give a distinguishing attack with complexity around 2236. Although the attack is only 220 times faster than exhaustive key search, the result indicates that ZUC-256 does not provide a source with full 256-bit entropy in the generated keystream, which would be expected from a 256-bit key. To the best of our knowledge, this is the first known academic attack on full ZUC-256 with a computational complexity that is below exhaustive key search.
New Circuit Minimization Techniques for Smaller and Faster AES SBoxes 📺
In this paper we consider various methods and techniques to find the smallest circuit realizing a given linear transformation on n input signals and m output signals, with a constraint of a maximum depth, maxD, of the circuit. Additional requirements may include that input signals can arrive to the circuit with different delays, and output signals may be requested to be ready at a different depth. We apply these methods and also improve previous results in order to find hardware circuits for forward, inverse, and combined AES SBoxes, and for each of them we provide the fastest and smallest combinatorial circuits. Additionally, we propose a novel technique with “floating multiplexers” to minimize the circuit for the combined SBox, where we have two different linear matrices (forward and inverse) combined with multiplexers. The resulting AES SBox solutions are the fastest and smallest to our knowledge.
A new SNOW stream cipher called SNOW-V 📺
In this paper we are proposing a new member in the SNOW family of stream ciphers, called SNOW-V. The motivation is to meet an industry demand of very high speed encryption in a virtualized environment, something that can be expected to be relevant in a future 5G mobile communication system. We are revising the SNOW 3G architecture to be competitive in such a pure software environment, making use of both existing acceleration instructions for the AES encryption round function as well as the ability of modern CPUs to handle large vectors of integers (e.g. SIMD instructions). We have kept the general design from SNOW 3G, in terms of linear feedback shift register (LFSR) and Finite State Machine (FSM), but both entities are updated to better align with vectorized implementations. The LFSR part is new and operates 8 times the speed of the FSM. We have furthermore increased the total state size by using 128-bit registers in the FSM, we use the full AES encryption round function in the FSM update, and, finally, the initialization phase includes a masking with key bits at its end. The result is an algorithm generally much faster than AES-256 and with expected security not worse than AES-256.