Popping “R-propping”: breaking hardness assumptions for matrix groups over F_{2^8}

A recent series of works (Hecht, IACR ePrint, 2020–2021) propose to build post-quantum public-key encapsulation, digital signatures, group key agreement and oblivious transfer from R-propped variants of the Symmetrical Decomposition and Discrete Logarithm problems for matrix groups over $\mathbb{F}_{2^8}$. We break all four proposals by presenting a linearisation attack on the Symmetrical Decomposition platform, a forgery attack on the signature scheme, and a demonstration of the insecurity of the instances of the Discrete Logarithm Problem used for signatures, group key agreement and oblivious transfer, showing that none of the schemes provides adequate security

Revisiting the Expected Cost of Solving uSVP and Applications to LWE

Abstract: Reducing the Learning with Errors problem (LWE) to the Unique-SVP problem and then applying lattice reduction is a commonly relied-upon strategy for estimating the cost of solving LWE-based constructions. In the literature, two different conditions are formulated under which this strategy is successful. One, widely used, going back to Gama & Nguyen\u27s work on predicting lattice reduction (Eurocrypt 2008) and the other recently outlined by Alkim et al. (USENIX 2016). Since these two estimates predict significantly different costs for solving LWE parameter sets from the literature, we revisit the Unique-SVP strategy. We present empirical evidence from lattice-reduction experiments exhibiting a behaviour in line with the latter estimate. However, we also observe that in some situations lattice-reduction behaves somewhat better than expected from Alkim et al.\u27s work and explain this behaviour under standard assumptions. Finally, we show that the security estimates of some LWE-based constructions from the literature need to be revised and give refined expected solving costs

Implementing Grover oracles for quantum key search on AES and LowMC

Grover\u27s search algorithm gives a quantum attack against block ciphers by searching for a key that matches a small number of plaintext-ciphertext pairs. This attack uses $O(\sqrt{N})$ calls to the cipher to search a key space of size $N$. Previous work in the specific case of AES derived the full gate cost by analyzing quantum circuits for the cipher, but focused on minimizing the number of qubits. In contrast, we study the cost of quantum key search attacks under a depth restriction and introduce techniques that reduce the oracle depth, even if it requires more qubits. As cases in point, we design quantum circuits for the block ciphers AES and LowMC. Our circuits give a lower overall attack cost in both the gate count and depth-times-width cost models. In NIST\u27s post-quantum cryptography standardization process, security categories are defined based on the concrete cost of quantum key search against AES. We present new, lower cost estimates for each category, so our work has immediate implications for the security assessment of post-quantum cryptography. As part of this work, we release Q# implementations of the full Grover oracle for AES-128, -192, -256 and for the three LowMC instantiations used in Picnic, including unit tests and code to reproduce our quantum resource estimates. To the best of our knowledge, these are the first two such full implementations and automatic resource estimations. This is a revised version that corrects the estimates for AES to account for some issues in Q# that made the original estimates inaccurate. We did not revise the estimates for LowMC, so the resource counts are likely lower than possible

Quantum Lattice Enumeration in Limited Depth

In 2018, Aono et al. (ASIACRYPT 2018) proposed to use quantum backtracking algorithms (Montanaro, TOC 2018; Ambainis and Kokainis, STOC 2017) to speedup lattice point enumeration. Quantum lattice sieving algorithms had already been proposed (Laarhoven et al., PQCRYPTO 2013), being shown to provide an asymptotic speedup over classical counterparts, but also to lose competitivity at relevant dimensions to cryptography if practical considerations on quantum computer architecture were taken into account (Albrecht et al., ASIACRYPT 2020). Aono et al.’s work argued that quantum walk speedups can be applied to lattice enumeration, achieving at least a quadratic asymptotic speedup à la Grover search while not requiring exponential amounts of quantum accessible classical memory, as it is the case for sieving. In this work, we explore how to lower bound the cost of using Aono et al.’s techniques on lattice enumeration with extreme cylinder pruning assuming a limit to the maximum depth that a quantum computation can achieve without decohering, with the objective of better understanding the practical applicability of quantum backtracking in lattice cryptanalysis

Adversarial Correctness and Privacy for Probabilistic Data Structures

We study the security of Probabilistic Data Structures (PDS) for handling Approximate Membership Queries (AMQ); prominent examples of AMQ-PDS are Bloom and Cuckoo filters. AMQ-PDS are increasingly being deployed in environments where adversaries can gain benefit from carefully selecting inputs, for example to increase the false positive rate of an AMQ-PDS. They are also being used in settings where the inputs are sensitive and should remain private in the face of adversaries who can access an AMQ-PDS through an API or who can learn its internal state by compromising the system running the AMQ-PDS. We develop simulation-based security definitions that speak to correctness and privacy of AMQ-PDS. Our definitions are general and apply to a broad range of adversarial settings. We use our defi- nitions to analyse the behaviour of both Bloom filters and insertion- only Cuckoo filters. We show that these AMQ-PDS can be provably protected through replacement or composition of hash functions with keyed pseudorandom functions in their construction. We also examine the practical impact on storage size and computation of providing secure instances of Bloom and insertion-only Cuckoo filters

Implementing RLWE-based Schemes Using an RSA Co-Processor

We repurpose existing RSA/ECC co-processors for (ideal) lattice-based cryptography by exploiting the availability of fast long integer multiplication. Such co-processors are deployed in smart cards in passports and identity cards, secured microcontrollers and hardware security modules (HSM). In particular, we demonstrate an implementation of a variant of the Module-LWE-based Kyber Key Encapsulation Mechanism (KEM) that is tailored for high performance on a commercially available smart card chip (SLE 78). To benefit from the RSA/ECC co-processor we use Kronecker substitution in combination with schoolbook and Karatsuba polynomial multiplication. Moreover, we speed-up symmetric operations in our Kyber variant using the AES co-processor to implement a PRNG and a SHA-256 co-processor to realise hash functions. This allows us to execute CCA-secure Kyber768 key generation in 79.6 ms, encapsulation in 102.4 ms and decapsulation in 132.7 ms

Optimization for SPHINCS+ using Intel Secure Hash Algorithm Extensions

SPHINCS+ was selected as a candidate digital signature scheme for standardization by the NIST Post-Quantum Cryptography Standardization Process. It offers security capabilities relying only on the security of cryptographic hash functions. However, it is less efficient than the lattice-based schemes. In this paper, we present an optimized software library for the SPHINCS+ signature scheme, which combines the Intel® Secure Hash Algorithm Extensions (SHA-NI) and AVX2 vector instructions. We obtain significant speed-up of SPHINCS+-128f-simple on both non-optimized (70%) and AVX2 reference implementations (8% -23%) offering 128-bit security