We propose a polynomial time quantum algorithm for solving the discrete logarithm problem (DLP) in matrices over finite group rings. The hardness of this problem was recently employed in the design of a key-exchange protocol proposed by D. Kahrobaei, C. Koupparis and V. Shpilrain [Groups Complex. Cryptol. 5 (2013), 97–115]. Our result implies that the Kahrobaei–Koupparis–Shpilrain protocol does not belong to the realm of post-quantum cryptography.
We propose a polynomial time quantum algorithm for solving the discrete logarithm problem (DLP) in matrices over finite group rings. The hardness of this problem was recently employed in the design of a key-exchange protocol proposed by D. Kahrobaei, C. Koupparis and V. Shpilrain [Groups Complex. Cryptol. 5 (2013), 97–115]. Our result implies that the Kahrobaei–Koupparis–Shpilrain protocol does not belong to the realm of post-quantum cryptography.
Abstract. We propose a polynomial time quantum algorithm for solving the discrete logarithm problem in matrices over finite group rings. The hardness of this problem was recently employed in the design of a key-exchange protocol proposed by D. Kahrobaei, C. Koupparis, and V. Shpilrain [4]. Our result implies that the Kahrobaei et al. protocol does not belong to the realm of post-quantum cryptography. Keywords and phrases: Group-based cryptography, semidirect product, matrix monoids, group-rings, Diffie-Hellman, key-exchange, discrete logarithm problem, quantum algorithms, post-quantum cryptography.
Simulation of Shor Algorithm for Discrete Logarithm Problems With Comprehensive Pairs of Modulo p and Order q
The discrete logarithm problem (DLP) over finite fields, commonly used in classical cryptography, has no known polynomial-time algorithm on classical computers. However, Shor has provided its polynomial-time algorithm on quantum computers. Nevertheless, there are only few examples simulating quantum circuits that operate on general pairs of modulopand orderq. In this paper, we constructed such quantum circuits and solved DLPs for all 1,860 possible pairs ofpandqup to 32 qubits using a quantum simulator with PRIMEHPC FX700. From this, we obtained and verified values of the success probabilities, which had previously been heuristically analyzed by [Ekerå, arXiv:1905.09084 (2019)]. As a result, the detailed waveform shape of the success probability of Shor's algorithm for solving the DLP, known as a periodic function of orderq, was clarified. Additionally, we generated 1,015 quantum circuits for larger pairs ofpandq, extrapolated the circuit sizes obtained, and compared them forp=2048bits between safeprime groups and Schnorr groups. While in classical cryptography, the cipher strength of safe-prime groups and Schnorr groups is the same ifpis equal, we quantitatively demonstrated how much the strength of the latter decreases to the bit length ofpin the former when using Shor's quantum algorithm. In particular, it was experimentally and theoretically shown that when a basic adder is used in the addition circuit, the cryptographic strength of a Schnorr group withp=2048bits under Shor's algorithm is almost equivalent to that of a safe-prime group withp=1024bits.
This thesis contains a collection of efficient quantum algorithms and classical pre- and post-processing algorithms for various number- and group-theoretical problems with concrete cryptanalytical applications. More specifically, the focus is on the integer factoring problem (IFP), the discrete logarithm problem (DLP), and the order-finding problem (OFP), and on certain important variations of these problems. It is for example explained how the OFP and complete IFP may be solved efficiently in a single run of a reduced version of Shor's algorithm for the OFP with very high success probability, as evidenced by a lower bound that is 1 − o(1), how the short DLP in groups of unknown order may be solved efficiently and with an advantage over Shor's algorithm for the DLP (that furthermore requires the order to be known), as evidenced by a lower bound on the single-run success probability that is 1 − o(1), how the RSA IFP may be solved efficiently and with an advantage over Shor's algorithm for the IFP, by reducing the RSA IFP to a short DLP, how the DLP may heuristically be solved efficiently, and with high success probability that is 1 − o(1), in a single run of a reduced version of Shor’s algorithm for the DLP that admits efficient implementation, how the DLP may be solved in groups of unknown order, such as Schnorr groups, by jointly solving an OFP and a DLP at lower overall cost but higher per-run cost compared to first solving the OFP and then the DLP, how tradeoffs — between the number of group operations that are evaluated quantumly and the number of runs that are required — may be achieved in all of the aforementioned algorithms, and how all of the aforementioned algorithms may be simulated efficiently classically, for arbitrary large cryptographically relevant problem instances, when the solution to the instance is known, enabling the number of runs required when performing tradeoffs to be tightly estimated. It is furthermore for example explained how Regev's recent quantum algorithm for the IFP may be extended to the DLP and OFP, yielding i) a reduction in the circuit size and depth by a factor compared to Shor for these problems when working in , for N an n-bit integer, at the expense of performing runs, and ii) slight improvements of Regev's orginal algorithm for the IFP, how the above algorithms may be simulated efficiently classically, for large special-form problem instances that are classically tractable, and that Regev’s post-processing, and the post-processing for our extensions, are robust to an arbitrarily large fraction < 1 of the runs being bad. The above has implications for cryptography based on the intractability of the IFP and DLP — including but not limited to for widely used schemes such as RSA, DSA and Diffie–Hellman. The algorithms in this thesis are all derived from, and make notable improvements to, the seminal works of Shor. Some of the contributions are joint works with other authors.
Solving the discrete logarithm problem (DLP) with quantum computers is a fundamental task with important implications. Beyond Shor's algorithm, many researchers have proposed alternative solutions in recent years. However, due to current hardware limitations, the scale of DLP instances that can be addressed by quantum computers remains insufficient. To overcome this limitation, we propose a distributed quantum discrete logarithm algorithm that reduces the required quantum register size for solving DLPs. Specifically, we design a distributed quantum algorithm to determine whether the solution is contained in a given set. Based on this procedure, our method solves DLPs by identifying the intersection of sets containing the solution. Compared with Shor's original algorithm, our approach reduces the register size and can improve the success probability, while requiring no quantum communication.
Abstract The semidirect discrete logarithm problem (SDLP) is the following analogue of the standard discrete logarithm problem in the semidirect product semigroup G⋊End(G) G⋊End(G) for a finite semigroupG. Given g∈G,σ∈End(G) g∈G,σ∈End(G) , and h=∏i=0t−1σi(g) h=∏i=0t-1σi(g) for some integert, the SDLP (G,σ) (G,σ) , forgandh, asks to determinet. As Shor’s algorithm crucially depends on commutativity, it is believed not to be applicable to the SDLP. For generic semigroups, the best known algorithm for the SDLP is based on Kuperberg’s subexponential time quantum algorithm. Still, the problem plays a central role in the security of certain proposed cryptosystems in the family ofsemidirect product key exchange. This includes a recently proposed signature protocol called SPDH-Sign. In this paper, we show that the SDLP is even easier in some important special cases. Specifically, for a finite groupG, we describe quantum algorithms for the SDLP in G⋊Aut(G) G⋊Aut(G) for the following two classes of instances: the first one is whenGis solvable and the second is whenGis a matrix group and a power of σ σ with a polynomially small exponent is an inner automorphism ofG. We further extend the results to groups composed of factors from these classes. A consequence is that SPDH-Sign and similar cryptosystems whose security assumption is based on the presumed hardness of the SDLP in the cases described above are insecure against quantum attacks. The quantum ingredients we rely on are not new: these are Shor’s factoring and discrete logarithm algorithms and well-known generalizations.
The discrete logarithm problem (DLP) is the basis for several cryptographic primitives. Since Shor’s work, it has been known that the DLP can be solved by combining a polynomial-size quantum circuit and a polynomial-time classical post-processing algorithm. The theoretical result corresponds the situation where a quantum device working with a medium number of qubits of very small errors can solve DLP. However, all the quantum devices that we can use have a limited number of noisy qubits, as of the noisy intermediate-scale quantum (NISQ) era. Thus, evaluating the instance size that the latest quantum device can solve, and give a future prediction of the size along the progress of quantum devices are emerging research topics. This paper contains two proposal to discuss the performance of quantum devices against DLP in the NISQ era. (1) A quantitative measure based on the success probability of the post-processing algorithm to determine whether an experiment on a quantum device (or a classical simulator) succeeded. (2) A procedure to modify bit strings observed from a Shor’s circuit to increase the success probability of a lattice-based post-processing algorithm. We conducted our experiments with theibm_kawasakidevice and discovered that the simplest circuit (7 qubits) from a 2-bit DLP instance achieves a sufficiently high success probability to proclaim the experiment successful. Experiments on another circuit from a slightly harder 2-bit DLP instance, on the other hand, did not succeed, and we determined that reducing the noise level by half is required to achieve a successful experiment. Finally, we give a near-term prediction based on required noise levels to solve some selected small DLP and integer factoring instances.