Jul 2026· International Conference on Computer Communications and Networks· pp. 1-6· 0 citations· 20 references
Abstract
Cloud-based access to quantum hardware has become the dominant model for executing quantum workloads in the Noisy Intermediate-Scale Quantum (NISQ) era. However, the lack of transparency in multi-tenant quantum cloud platforms raises security and trust concerns, including the inability of users to verify which quantum processor executed their submitted circuits. In this paper, we propose a calibration data-based quantum device fingerprinting framework that enables verification of quantum cloud hardware without requiring circuit execution or additional measurement overhead. Our approach leverages historical calibration data published by the provider and employs a machine-learning classifier XGBoost to learn distinctive device-specific fingerprints. We evaluate the proposed framework on multiple generations of IBM quantum processors in binary and multi-class identification settings, and achieve 99.03% and 82.85% accuracy, respectively. These experimental results demonstrate that the proposed method achieves high device identification accuracy across heterogeneous hardware architectures while remaining robust to missing or evolving calibration data. Unlike prior fingerprinting techniques that rely on executing large numbers of quantum circuits, our static calibration-driven approach significantly reduces cost and runtime overhead, making it well suited for scalable and practical deployment in quantum cloud environments.
The framework provides a pragmatic, classifier-agnostic defense layer deployable on freely accessible cloud platforms (Google Colab) without specialized quantum hardware, and offers viable post-quantum hardening for security-critical applications.
Soha Rawas, Mohammed Al Saleh, A. D. Samala et al.· Applied Computing and Inform...· 0 citations
The transition to quantum-resistant cryptography is becoming increasingly urgent as advances in quantum computing threaten widely deployed public-key systems such as RSA and elliptic-curve cryptography. While the National Institute of Standards and Technology (NIST) has recently standardized several post-quantum cryptographic (PQC) algorithms, there remains limited empirical data on their practical performance and energy characteristics on commodity hardware. This paper presents a comprehensive microbenchmark study of NIST-selected PQC key encapsulation mechanisms (ML-KEM, HQC, BIKE, Classic McEliece) and digital signature algorithms (ML-DSA, Falcon, and SPHINCS +). Using the liboqs library on an AMD Zen 4 platform, we measure CPU cycles, artifact sizes, peak memory usage, and energy consumption across multiple NIST security levels. Energy measurements are obtained through AMD µProf power traces using an idle-subtracted methodology to estimate per-operation dynamic energy. Our results show that lattice-based schemes (ML-KEM and ML-DSA) consistently provide the best performance and energy efficiency, while code-based alternatives exhibit specialized trade-offs, including extremely expensive key generation for Classic McEliece and higher computational cost for HQC. Hash-based signatures such as SPHINCS + demonstrate significantly higher signing overhead but offer conservative security assumptions. These findings provide practical insight into the trade-offs between runtime, energy efficiency, and artifact sizes across PQC families, offering system architects and engineers concrete data for evaluating deployment strategies in quantum-safe systems.
Krish Jindal, Tyler Judd, S. Uludag· IEEE International Symposium...· 0 citations
Cloud-native infrastructures now form the backbone of modern digital systems, offeringscalability and flexible deployment, But they introduce new security challenges beyondtraditional cryptographic methods. The rise of quantum computing further threatens widelyused algorithms like RSA and ECC, which remain vulnerable to quantum attacks. Most postquantumsolutions focus narrowly on standalone primitives, overlooking the distributednature of cloud-native systems. To address this, Cloud-Aware Cryptographic CodeConstruction (CAC³) method, comprise of lattice-based routines designed for containerizedexecution environments is proposed. CAC³ ensures confidentiality and integrity underconcurrent workloads while supporting distributed key generation, context-aware parameterallocation, and orchestration compatibility. CAC³ integrates post-quantum primitives directlyinto the cloud-native execution context, facilitating scalable quantum-safe cloud services. Theworking prototype was developed locally and tested remotely on the cloud server of i2k2.com,simulating multi-tenant cryptography and communication among microservices. Tenant datais encrypted and verified at the destination via orchestrated channels. Performance ismeasured in terms of key generation, encryption, decryption, signing and verification timealong with distributed key generation latency under simulated multi-tenant workloads. Thiswork forms the core cryptographic layer for future expansion with composability, adaptiveauthentication and in-transit performance evaluation over orchestrated channels. The paperprovides a unified approach to securing cloud-native infrastructures in the quantum era.
K. Princey, T. Beena· THE SCIENTIFIC TEMPER· 0 citations
The recent introduction of Google’s Willow quantum chip has demonstrated remarkable computational capabilities, solving problems in microseconds that would take classical computers millions of years. As quantum computers advance toward cryptographic relevance, existing encryption algorithms become vulnerable to attacks that could break them within seconds or minutes, rendering current cryptographic protections ineffective. This necessitates the establishment of post-quantum cryptography (PQC) standards to secure systems in the quantum era. This study evaluates the performance of NIST-standardized PQC algorithms Kyber (512, 768, 1024) and Dilithium (2, 3, 5) on a Raspberry Pi 4 Model B, representing baseline IoT device capabilities. Using the Liboqs library, each algorithm was executed across 1000 iterations in a real-world wireless network environment connected to a router, accounting for practical network conditions such as packet loss, latency, and jitter to assess computational feasibility under resource-constrained conditions. Experimental results demonstrate the practical viability of PQC algorithms in IoT environments. Kyber-512 achieved encryption times of 58 μs and decryption times of 51 μs, while Dilithium-2 completed signature generation in 1.1 ms. These findings confirm that both Kyber and Dilithium algorithms offer efficient and rapid performance, making them suitable candidates for securing IoT devices against quantum threats.
Cemile Ince· Sakarya University Journal o...· 0 citations
This work presents an optimized software implementation providing 1 st -order side-channel protection, as well as the first efficiency-oriented 2 nd -order implementation, surpassing previous solutions in performance.
Juan Moreno-Cenizo, Eros Camacho-Ruiz, M. Martínez-Rodríguez et al.· International Conference on...· 0 citations
Distributed infrastructure schedulers traditionally optimise capacity, locality, and cost, but provide limited support for security posture and emerging quantum-classical workloads. As hybrid quantum-classical computing becomes increasingly practical and post-quantum security requirements begin to affect infrastructure deployment, schedulers must jointly reason about heterogeneous compute resources, security constraints, and quantum backend characteristics. We present SQUIRO, a framework for security-aware quantum-classical scheduling based on a platform-independent Unified Scheduling Model (USM) and a six-step Scheduler Design Methodology (SDM) that together enable the derivation of concrete schedulers for Kubernetes, high-performance computing (HPC), and federated environments. The framework combines multidimensional security posture enforcement through hard feasibility constraints with residual-risk optimisation, and introduces a circuit-aware quantum backend selector that accounts for coherence margin, calibration freshness, queue pressure, and hardware capabilities through a forward-compatible colocation hierarchy. Evaluation on synthetic Kubernetes clusters shows that the security model enforces complete compliance for regulated workloads by construction, while global optimisation reduces infrastructure cost by up to 51% and energy consumption by up to 63% compared with greedy placement in underloaded scenarios, without compromising admission priorities. Additional experiments characterise the solve-time growth of the current CP-SAT formulation and show that circuit-aware backend selection systematically diverges from naive error-rate ranking under coherence- and queue-limited conditions.
