Researchers are today exploring models for cloud-based usage of quantum computers where multi-tenancy can be used to share quantum computer hard-ware among multiple users. Multi-tenancy has a promise of allowing better utilization of the quantum computer hardware, but also opens up the quantum computer to new types of security attacks. As this and other recent research shows, it is possible to perform a fault injection attack using crosstalk on quantum computers when a victim and attacker circuits are instantiated as co-tenants on the same quantum computer. To ensure such attacks do not happen, this paper proposes that new techniques should be developed to help catch malicious circuits before they are loaded onto quantum computer hardware. Following ideas from classical computers, a compile-time technique can be designed to scan quantum computer programs for mali-cious or suspicious code patterns before they are compiled into quantum circuits that run on a quantum computer. This paper presents ongoing work which demonstrates how crosstalk can affect Grover's algorithm, and then presents suggestions of how quantum programs could be analyzed to catch circuits that generate large amounts of crosstalk with malicious intent.
Researchers are today exploring models for cloud-based usage of quantum computers where multi-tenancy can be used to share quantum computer hard-ware among multiple users. Multi-tenancy has a promise of allowing better utilization of the quantum computer hardware, but also opens up the quantum computer to new types of security attacks. As this and other recent research shows, it is possible to perform a fault injection attack using crosstalk on quantum computers when a victim and attacker circuits are instantiated as co-tenants on the same quantum computer. To ensure such attacks do not happen, this paper proposes that new techniques should be developed to help catch malicious circuits before they are loaded onto quantum computer hardware. Following ideas from classical computers, a compile-time technique can be designed to scan quantum computer programs for mali-cious or suspicious code patterns before they are compiled into quantum circuits that run on a quantum computer. This paper presents ongoing work which demonstrates how crosstalk can affect Grover's algorithm, and then presents suggestions of how quantum programs could be analyzed to catch circuits that generate large amounts of crosstalk with malicious intent.
The development of quantum computers has been advancing rapidly in recent years. In addition to researchers and companies building bigger and bigger machines, these computers are already being actively connected to the internet and offered as cloud-based quantum computer services. 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, to interfere with or manipulate results of other users, or to reverse engineer the underlying quantum computer architecture and its intellectual property, for example. To analyze such new security threats to cloud-based quantum computers, this work first proposes and explores different types of quantum computer viruses. This work shows that quantum viruses can impact outcomes of Grover’s search algorithm or machine learning classification algorithms running on quantum computers, for example. The work then proposes a first of its kind quantum computer antivirus as a new means of protecting the expensive and fragile quantum computer hardware from quantum computer viruses. The antivirus can analyze quantum computer programs, also called circuits, and detect possibly malicious ones before they execute on quantum computer hardware. As a compile-time technique, it does not introduce any new overhead at run-time of the quantum computer.
Multi-tenancy schemes for quantum computing hardware are vulnerable to fault injection attacks through crosstalk effects. Research studies have experimentally demonstrated the change in output probabilities of victim circuits where the victim and the adversary share the same quantum hardware. To detect adversary circuits, this paper proposes compile time and simulation based protocols to scan quantum computer programs for malicious code patterns. In the compile time approach, with the help of databases of known malicious patterns, the number of gates and the repeating patterns in the code structures are tracked and validated for malicious intent. In the simulation based approach, Idle Tomography (IDT) using pyGSTi software framework is employed for crosstalk error rate extraction. Hamiltonian and Stochastic errors of relevant qubit pairs in accordance with the quantum hardware’s connectivity mapping are analyzed for the detection of unrecognized malicious adversary patterns. Both the protocols output metrics and error rates information that can be used as a "confidence ruler" over a concerned quantum hardware. These protocols safeguard honest quantum circuit parties from possible interference and resulting tampered computational outcomes brought about by adversary parties.
Abstract With the increasing demand for quantum hardware, shared and multi-tenant environments have been proposed to optimize resource utilization. However, the multi-tenancy paradigm in quantum computing inherently introduces security threats. This paper examines crosstalk-mediated attacks targeting three-qubit Grover’s search algorithm and explores two fundamental mitigation strategies: gate-based dynamical decoupling and the use of a buffer qubit. We evaluate the effectiveness of each method individually and in combination, finding that while both strategies offer some level of attack mitigation, their combined application yields the most significant performance improvement. Beyond security vulnerabilities, our work also has implications for unintentional circuit interference that can occur when multiple quantum circuits are executed in close proximity.
Real-time computers of the Noisy Intermediate Scale Quantum (NISQ) era undergo the undesirable coupling among qubits known as crosstalk. The negative effects of crosstalk errors can lead to degradation in the performance of various quantum circuits. In this paper, we present four crosstalk models that negatively affect the outcome of Grover’s search algorithm, Simon’s algorithm and the performance of the quantum teleportation protocol. The crosstalk models presented in this work are used as malicious circuits running alongside the victim circuits of the said quantum algorithms and protocol. This is possible in the shared cloud quantum computing environment which is right now offered by some of the industries. This work demonstrates the formation of some of the possible patterns as parts of the malicious circuits and their repetitions to inject crosstalk errors in the victim circuits. The analysis of the affected outputs for each pattern along with the corresponding diagrammatic representation is also done in this article along with the discussion on the degraded results for the used victim circuits other than the state-of-the-art works for the available ones. Moreover, this work highlights the need for proper counter-measures in order to detect and eliminate the malicious patterns that can harm the performance of a quantum circuit.
Quantum computing, while allowing for processing information exponentially faster than classical computing, is far from becoming a personal commodity. Indeed, because of cost and needs for ultra-cold temperature, shielded environment, and complex wiring for control, access to quantum computers is likely to be provided remotely, through quantum servers. Sharing quantum hardware between multiple users enables the efficient use of quantum resources, but makes some security threats possible. For instance, previous studies demonstrated that crosstalk between attacker and victim's qubits can be exploited to mount security attacks. In this work, we address the problem of securing user circuits submitted to quantum servers. We propose the Qubit Allocation for Inter-Circuit Crosstalk Countermeasure (QAICCC), which aims to maximize qubit usage, reduce inter-circuit crosstalk as well as intra-circuit noise. QAICCC performs (1) a crosstalk analysis of the targeted quantum processor to determine qubits involved in crosstalk with the largest intensity; (2) the allocation of qubits in the safest possible way; and (3) the application of existing techniques to further reduce crosstalk between circuits and noise in user circuits. The main contribution is the allocation algorithm, which aims to maximize qubit usage (including making unused qubits available for future usage) while minimizing the largest inter-circuit crosstalk error rate. Thus, QAICCC will support quantum computing adoption by securing the usage of quantum servers by a large number of actors.
Hardware crosstalk in multi-tenant superconducting quantum computers poses a severe security threat, allowing adversaries to induce targeted errors across tenant boundaries by injecting carefully engineered pulses. We present a simulation-based study of active crosstalk attacks at the pulse level, analyzing how adversarial control of pulse timing, shape, amplitude, and coupling can disrupt a victim's computation. Our framework models the time-dependent dynamics of a three-qubit system in the rotating frame, capturing both always-on couplings and injected drive pulses. We examine two attack strategies: attacker-first (pulse before victim operation) and victim-first (pulse after), and systematically identify the pulse and coupling configurations that cause the largest logical errors. Protocol-level experiments on quantum coin flip and XOR classification circuits show that some protocols are highly vulnerable to these attacks, while others remain robust. Based on these findings, we discuss practical methods for detection and mitigation to improve security in quantum cloud platforms.