This work presents the first thorough exploration of how reset operations in cloud-based quantum computers could be exploited to run quantum circuits for free. This forms a new type of attack on the economics of cloud-based quantum computers. All major quantum computing companies today offer access to their hardware through some type of cloud-based service. Due to the noisy nature of quantum computers, a quantum circuit is run many times to collect the output statistics, and each run is called a shot. The fees users pay for access to the machines typically depend on the number of these shots of a quantum circuit that are executed. Per-shot pricing is a clean and straightforward approach as users are charged a small fee for each shot of their circuit. This work demonstrates that per-shot pricing can be exploited to get circuits to run for free when users abuse recently implemented mid-circuit qubit measurement and reset operations. Through evaluation on real, cloud-based quantum computers this work shows how multiple circuits can be executed together within a shot, by separating each user circuit by set of reset operations and submitting all the circuits, and reset operations, as one larger circuit. As a result, the user is charged per-shot pricing, even though inside each shot are multiple circuits. Total per-shot cost to run certain circuits could be reduced by up to $900$\% using methods proposed in this work, leading to significant financial losses to quantum computing companies. To address this novel finding, this work proposes a clear approach for how users should be charged for their execution, while maintaining the flexibility and usability of the mid-circuit measurement and reset~operations.
This work presents the first thorough exploration of how reset operations in cloud-based quantum computers could be exploited to run quantum circuits for free. This forms a new type of attack on the economics of cloud-based quantum computers. All major quantum computing companies today offer access to their hardware through some type of cloud-based service. Due to the noisy nature of quantum computers, a quantum circuit is run many times to collect the output statistics, and each run is called a shot. The fees users pay for access to the machines typically depend on the number of these shots of a quantum circuit that are executed. Per-shot pricing is a clean and straightforward approach as users are charged a small fee for each shot of their circuit. This work demonstrates that per-shot pricing can be exploited to get circuits to run for free when users abuse recently implemented mid-circuit qubit measurement and reset operations. Through evaluation on real, cloud-based quantum computers this work shows how multiple circuits can be executed together within a shot, by separating each user circuit by set of reset operations and submitting all the circuits, and reset operations, as one larger circuit. As a result, the user is charged per-shot pricing, even though inside each shot are multiple circuits. Total per-shot cost to run certain circuits could be reduced by up to 900% using methods proposed in this work, leading to significant financial losses to quantum computing companies. To address this novel finding, this work proposes a clear approach for how users should be charged for their execution, while maintaining the flexibility and usability of the mid-circuit measurement and reset~operations.
The development of quantum computers has been advancing rapidly in recent years. As quantum computers become more widely accessible, potentially malicious users could try to execute their code on the machines to leak information from other users, interfere with or manipulate the results of other users, or reverse engineer the underlying quantum computer architecture and its intellectual property. Among different security threats, previous work has demonstrated information leakage across the reset operations, and it then proposed a secure reset operation could be an enabling technology that allows the sharing of a quantum computer among different users or different quantum programs of the same user. In this study, we delve deeper into the reset attack, aiming to augment its efficacy and capabilities and the countermeasure to protect from this attack. First, we propose a set of new extended reset attacks that could be more stealthy by hiding the intention of the attacker's circuit. This work shows various concealing circuits and how attackers can retrieve information from the execution of a previous shot of a circuit, even if the concealing circuit is used between the reset operation (of the victim, after the shot of the circuit is executed) and the measurement (of the attacker). Second, based on the uncovered new possible attacks, this work proposes a set of heuristic checks that could be applied at transpile time to check for the existence of malicious circuits that try to steal information via the attack on the reset operation. Unlike run-time protection or added secure reset gates, this work proposes a complimentary, compile-time security solution to the attacks on reset operation.
Cloud-accessible quantum computing has made hardware comparison not only a physics benchmark but also a practical purchasing decision. Cost-aware comparison of quantum computers remains underexplored and is difficult to do under the heterogeneous billing models offered by various cloud-based quantum computing providers. This paper makes two main contributions to enable price-aware comparison of quantum computers. First, this work presents a cross-provider measurement study of quantum circuit execution fidelity spanning 14 cloud QPU access-path entries (12 distinct physical QPUs) across four cloud access paths: Amazon Web Services (AWS) cloud, IBM Quantum Runtime (IBM) cloud, IQM Resonance (IQM) cloud, and Oxford Quantum Circuits (OQC) cloud. Second, this work proposes and analyzes a cost-aware score, Quantum Fidelity-per-Cost (QFC), which combines Kullback--Leibler (KL) divergence from an ideal output distribution, shot count, and monetary cost into one possible metric under a documented billing model. The main empirical observation from this work is that cost-aware ranking can differ from purely fidelity-based evaluation of quantum computers, and that users may select different quantum computing backends when they consider price in their selection, as opposed to selection based on fidelity alone. This work shows that the ranking is stable under reweighting of the metric, and that a device's billing model, not its hardware, governs how its score scales with shot count. Reported QFC values change as new machines come online or as providers revise their prices.
The rapid expansion of cloud-based access to quantum computers has significantly democratized their usage, enabling a more diverse range of users to explore and utilize quantum computing technologies. However, this increased accessibility also introduces security and privacy concerns. Cloud-based access and sharing of quantum computers require secure means to isolate different users, such as through the use of reset operations. However, current reset operations, including direct thermalization and fast reset instructions, are vulnerable to information leakage due to imperfections in quantum computer operations. To counteract these vulnerabilities, our work proposes multiple implementations of the one-time pad (OTP) defense mechanism. These implementations, specifically random execution, dynamic circuit, and control gate, involve applying Pauli or control gates randomly before executing standard reset operations. We analyze and compare these implementations in detail, demonstrating their effectiveness in mitigating state leakage. This work offers innovative approaches to enhancing the security of reset operations and the safety of cloud-based quantum computers.
The ability for users to access quantum computers through the cloud has increased rapidly in recent years. Despite still being Noisy Intermediate-Scale Quantum (NISQ) machines, modern quantum computers are now being actively employed for research and by numerous startups. Quantum algorithms typically produce probabilistic results, necessitating repeated execution to produce the desired outcomes. In order for the execution to begin from the specified ground state each time and for the results of the prior execution not to interfere with the results of the subsequent execution, the reset mechanism must be performed between each iteration to effectively reset the qubits. However, due to noise and errors in quantum computers and specifically these reset mechanisms, a noisy reset operation may lead to systematic errors in the overall computation, as well as potential security and privacy vulnerabilities of information leakage. To counter this issue, we thoroughly examine the state leakage problem in quantum computing, and then propose a solution by employing the classical and quantum one-time pads before the reset mechanism to prevent the state leakage, which works by randomly applying simple gates for each execution of the circuit. In addition, this work explores conditions under which the classical one-time pad, which uses fewer resources, is sufficient to protect state leakage. Finally, we study the role of various errors in state leakage, by evaluating the degrees of leakage under different error levels of gate, measurement, and sampling errors. Our findings offer new perspectives on the design of reset mechanisms and secure quantum computing systems.
Context: Quantum computing is rapidly evolving, offering new opportunities for solving problems in optimization, cryptography, and simulation. However, the limited availability of quantum resources makes efficient utilization of quantum hardware a current challenge. Today’s paradigms often lead to under-utilization of qubits, increased costs, and execution delays, especially in the NISQ era. Objective: This work aims to improve the utilization of quantum hardware by introducing an execution model that integrates multiprogramming at circuit level with quantum shot-wise distribution in a single policy-driven pipeline. Methods: An architecture has been implemented that combines circuit scheduling and shot distribution techniques to aggregate multiple circuits and distribute their shots across heterogeneous QPUs. The approach was empirically validated on actual IBM Quantum devices using a diverse set of reference circuits. Results: The proposal achieved a reduction in cost of 95% and a reduction in tasks 92%. Moreover, the fidelity analysis of the results showed an increase in noise, with an average increase of approximately 20% using different statistical distances. Conclusions: This research provides a usable and extensible solution to increase the efficiency, cost effectiveness, and resilience of quantum workload execution in heterogeneous and dynamic cloud environments. These results obtained suggest that users should weigh the implications of fidelity versus cost (and time) savings based on the application requirements and their goals.
Security and reliability are primary concerns in any computing paradigm including quantum computing. Currently users can access quantum computers through a cloud based platform where they can run their programs on a suite of quantum computers. As the quantum computing ecosystem grows in popularity and utility it is reasonable to expect that more companies including untrusted or less trusted or unreliable vendors will begin offering quantum computers as hardware as a service at varied price or performance points. Since computing time on quantum hardware is expensive and the access queue could be long the users will be motivated to use the cheaper and readily available but unreliable or less trusted hardware. The less trusted vendors can tamper with the results providing a suboptimal solution to the user. In this paper we model this adversarial tampering and simulate its impact on a number of pure quantum and hybrid quantum classical workloads. To guarantee trustworthy computing for a mixture of trusted and untrusted hardware we propose distributing the total number of shots equally among the various hardware options. On average we note approx 30X and approx 1.5X improvement across the pure quantum workloads and a maximum improvement of approx 5X for hybrid classical algorithm in the chosen quality metrics. We also propose an intelligent run adaptive split heuristic leveraging temporal variation in hardware quality to users advantage allowing them to identify tampered or untrustworthy hardware at runtime and allocate more number of shots to the reliable hardware which results in a maximum improvement of approx 190X and approx 9X across the pure quantum workloads and an improvement of up to approx 2.5X for hybrid classical algorithm.