arXiv AI

Quantum Cryptanalysis on IBM Quantum Hardware: Extending Even--Mansour Period Recovery from $N=4$ to $N=10$

arXiv:2607. 18340v1 Announce Type: cross Abstract: We report genuine-un-compiled, textbook-faithful-quantum cryptanalysis of symmetric-cipher structures executed on real IBM quantum hardware (ibm\_kingston, Heron generation).

arXiv AI
6d ago

Quantum Computing for Network Security Classification: Near-Term Classification and Long-Term Memory Efficiency

The paper investigates the role of quantum computing in network‑security classification through two experiments. First, it evaluates near‑term quantum‑kernel support vector machines on datasets such as KDD Cup 1999, CICIDS2017, and BoT‑IoT, finding that quantum kernels can match or sometimes improve classical baselines, though classical RBF kernels often remain stronger. Second, it explores long‑term memory efficiency using quantum oracle sketching (QOS), showing that quantum methods can achieve comparable accuracy with a smaller effective memory footprint than explicit storage, suggesting a potential advantage in memory‑efficient data access for streaming classification tasks.

By Yuqing Li, Poonam Bala Nehru, Yunpeng Zhang, Danindu Gammanpilage, Xin Jin, Zeguan Wu, Junyu Liu
arXiv AI
Aug 20

How Quantum Is the Advantage? A Fair, Calibration- and Noise-Aware Benchmark and Attribution Audit of Quantum Machine Learning for Network Intrusion Detection

The study evaluates quantum machine learning (QML) models for network intrusion detection against well-tuned classical baselines across four standard datasets, using a leakage-controlled protocol and noise simulation. It introduces a quantum-attribution audit to determine whether any performance gains are truly due to quantum effects. While most tuned classical models match or surpass QML, two quantum approaches— a quantum-kernel SVM and a small hybrid circuit—show statistically significant advantages on specific metrics and tasks.

By Syeda Anshrah Gillani, Mirza Samad Ahmed Baig, Shahid Munir Shah, Asher Ali, Hamzah Siddiqui
arXiv Machine Learning
Sep 29

Encryptability As a Coordinate Choice: Depth-One Homomorphic Federated Learning of Quantum Neural Networks

The paper demonstrates that by choosing unit‑quaternion coordinates, encrypted updates for variational quantum circuits become bilinear, allowing depth‑one homomorphic federated learning without bootstrapping. This coordinate choice reduces encrypted rotation updates to a single multiplicative level and federated averaging to zero levels, eliminating the previously prohibitive cost of one round per gate. Experiments across two cryptographic backends and up to 20 clients show negligible aggregation error and no measurable loss in utility, with hardware validation on a 156‑qubit processor achieving near‑optimal fidelity.

By Marcel Mordarski, Nathan Mani, Arshad Patel, William Knottenbelt, Roberto Bondesan
arXiv AI
Aug 18

A Bi-directional Multi-solution Scalable Grover Search Algorithm

arXiv:2404. 15616v2 Announce Type: replace-cross Abstract: Grover's search algorithms, including various Partial Grover Searches (PGS), suffer from scaling issues when multiple solutions are sought, as the number of iterations scales with the number of solutions or marked states, making implementation more computationally expensive.

By Debanjan Konar, Zain Hafeez, Vaneet Aggarwal
arXiv AI
Sep 24

A Non-Invasive Cloud-Based Migration Strategy for Post-Quantum Cybersecurity in Smart HVAC Systems: Architecture, Implementation, and Empirical Evaluation

The paper presents a non‑invasive, cloud‑based migration strategy that protects legacy smart HVAC controllers from quantum attacks without modifying the devices or vendor cloud. It introduces a Raspberry Pi 4B gateway that performs post‑quantum key encapsulation (ML‑KEM‑768) and authentication (ML‑DSA‑65) using AES‑256‑GCM, completing handshakes in 2.48 ms and sustaining 443 sessions per second. Extensive side‑channel testing shows no timing leakage or man‑in‑the‑middle vulnerabilities, and the architecture is vendor‑agnostic, becoming redundant once native PQC support is adopted.

By Mahedee Zaman Moon, Kaysarul Anas Apurba, Md Hasibul Hasan, Sk Md Mizanur Rahman