Yu-Guang Yang

Quantum‐secure multi‐party computational geometry (QSMCG) aims to determine geometric relations without revealing the private spatial parameters of the participants. Existing QFT‐based secure multiparty quantum summation and multiplication protocols provide useful arithmetic primitives, but they still involve single‐initiator trust dependence and insufficient protocol‐level verification of channel disturbance and abnormal quantum‐state evolution. This paper proposes enhanced QFT‐based secure multi‐party summation and multiplication protocols. The protocols combine ‐threshold secret sharing with two complementary verification layers. Decoy‐particle detection monitors the quantum channel during transmission and is designed to catch eavesdropping, interception‐resend, delayed‐photon, invisible‐photon, or other transmission disturbances. Zero‐check verification is executed after the accumulated state is disentangled; it checks whether the target register returns to , so it tests whether the internal computation flow is consistent with the intended protocol. Based on these protocols, three modular QSMCG protocols are constructed for point‐ellipse, line‐ellipse, and circle‐ellipse relation determination under a TP‐assisted blinded‐comparison architecture. Correctness and security analyses show that the proposed protocols obtain the intended arithmetic and geometric results while improving resistance to representative external and internal attacks. Moreover, Qiskit simulations further verify the correctness and circuit‐level feasibility of the core quantum operations.

Balancing security and efficiency for Digital Imaging and Communications in Medicine images on resource-limited mobile health terminals is challenging. Existing adaptive ROI encryption suffers heavy extraction overhead and severe anatomical contour leakage, allowing attackers to infer anatomical structures from incompletely protected regions. This paper proposes a lightweight anti-contour-leakage encryption scheme. We adopt gradient statistical moments to replace costly sliding-window entropy for fast ROI detection, then perform chaotic global scrambling to break pixel spatial correlation. A mask-controlled bidirectional diffusion module further builds full-image pixel dependency and delivers region-adaptive encryption strength. Experiments verify that our method effectively suppresses silhouette leakage and exhibits excellent key sensitivity; any partial ciphertext loss makes the reconstructed medical content completely unidentifiable. The proposed framework serves as a lightweight, privacy-preserving solution for mobile medical image transmission.

As an important branch of quantum‐secure multi‐party computation, quantum‐secure multi‐party computational geometry aims to solve geometric computation problems without revealing the parties' geometric inputs. Privacy‐preserving point‐circle and circle‐circle positional relationships are classic problems in secure multi‐party computational geometry, with broad applications in privacy‐preserving queries, collision detection, and clustering. Building on the quantum two‐party summation and multiplication protocols proposed by Sutradhar and Om, this paper presents the first quantum‐secure protocols for determining point‐circle and circle‐circle positional relationships, enabling accurate relationship determination without disclosing private geometric parameters. Security analysis and simulation experiments on the IBM Qiskit platform demonstrate the security and feasibility of the proposed protocols. Furthermore, since existing quantum privacy‐preserving range query protocols are limited to one‐dimensional linear spaces, we build on the proposed protocols to present the first quantum‐secure privacy‐preserving geometric range query protocol, which enables arbitrary geometric range search for private coordinates in the two‐dimensional space while protecting the privacy of the query range and data points.