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Register a new userQuantum collision finding for homomorphic hash functions
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Added by
Julio Jos\\'e Moyano-Fern\\'andez
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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Hash functions are a basic cryptographic primitive. Certain hash functions try to prove security against collision and preimage attacks by reductions to known hard problems. These hash functions usually have some additional properties that allow for that reduction. Hash functions which are additive or multiplicative are vulnerable to a quantum attack using the hidden subgroup problem algorithm for quantum computers. Using a quantum oracle to the hash, we can reconstruct the kernel of the hash function, which is enough to find collisions and second preimages. When the hash functions are additive with respect to the group operation in an Abelian group, there is always an efficient implementation of this attack. We present concrete attack examples to provable hash functions, including a preimage attack to $oplus$-linear hash functions and for certain multiplicative homomorphic hash schemes.
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A $k$-collision for a compressing hash function $H$ is a set of $k$ distinct inputs that all map to the same output. In this work, we show that for any constant $k$, $Thetaleft(N^{frac{1}{2}(1-frac{1}{2^k-1})}right)$ quantum queries are both necessary and sufficient to achieve a $k$-collision with constant probability. This improves on both the best prior upper bound (Hosoyamada et al., ASIACRYPT 2017) and provides the first non-trivial lower bound, completely resolving the problem.
In this paper, we specify a class of mathematical problems, which we refer to as Function Density Problems (FDPs, in short), and point out novel connections of FDPs to the following two cryptographic topics; theoretical security evaluations of keyless hash functions (such as SHA-1), and constructions of provably secure pseudorandom generators (PRGs) with some enhanced security property introduced by Dubrov and Ishai [STOC 2006]. Our argument aims at proposing new theoretical frameworks for these topics (especially for the former) based on FDPs, rather than providing some concrete and practical results on the topics. We also give some examples of mathematical discussions on FDPs, which would be of independent interest from mathematical viewpoints. Finally, we discuss possible directions of future research on other cryptographic applications of FDPs and on mathematical studies on FDPs themselves.
Wireless Body Sensor Network (WBSN) is a developing technology with constraints in energy consumption, coverage radius, communication reliability. Also, communications between nodes contain very sensitive personal information in which sometimes due to the presence of hostile environments, there are a wide range of security risks. As such, designing authenticated key agreement (AKA) protocols is an important challenge in these networks. Recently, Li et al. proposed a lightweight scheme using the hash and XOR functions which is much more efficient compared with similar schemes based on elliptic curve. However, the investigations revealed that the claim concerning the unlinkability between the sessions of a sensor node is NOT true. The present paper considers the security issues of the scheme proposed by Li et al. and some of its new extensions in order to propose a new AKA scheme with anonymity and unlinkability of the sensor node sessions. The results of theoretical analysis compared with similar schemes indicate that the proposed scheme reduces average energy consumption and average computation time by 61 percent while reduces the average communication cost by 41 percent. Further, it has been shown by formal and informal analysis that, Besides the two anonymity and unlinkability features, the other main features of the security in the proposed scheme are comparable and similar to the recent similar schemes.
Many commonly used public key cryptosystems will become insecure once a scalable quantum computer is built. New cryptographic schemes that can guarantee protection against attacks with quantum computers, so-called post-quantum algorithms, have emerged in recent decades. One of the most promising candidates for a post-quantum signature scheme is SPHINCS$^+$, which is based on cryptographic hash functions. In this contribution, we analyze the use of the new Russian standardized hash function, known as Streebog, for the implementation of the SPHINCS$^+$ signature scheme. We provide a performance comparison with SHA-256-based instantiation and give benchmarks for various sets of parameters.
As the application of deep learning continues to grow, so does the amount of data used to make predictions. While traditionally, big-data deep learning was constrained by computing performance and off-chip memory bandwidth, a new constraint has emerged: privacy. One solution is homomorphic encryption (HE). Applying HE to the client-cloud model allows cloud services to perform inference directly on the clients encrypted data. While HE can meet privacy constraints, it introduces enormous computational challenges and remains impractically slow in current systems. This paper introduces Cheetah, a set of algorithmic and hardware optimizations for HE DNN inference to achieve plaintext DNN inference speeds. Cheetah proposes HE-parameter tuning optimization and operator scheduling optimizations, which together deliver 79x speedup over the state-of-the-art. However, this still falls short of plaintext inference speeds by almost four orders of magnitude. To bridge the remaining performance gap, Cheetah further proposes an accelerator architecture that, when combined with the algorithmic optimizations, approaches plaintext DNN inference speeds. We evaluate several common neural network models (e.g., ResNet50, VGG16, and AlexNet) and show that plaintext-level HE inference for each is feasible with a custom accelerator consuming 30W and 545mm^2.
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