Secure Communication via Modulation Order Confusion

2026-01-08

arXiv.org

AI Summary

This work proposes a physical-layer security framework based on modulation order obfuscation to counteract modulation recognition threats that compromise wireless communication confidentiality by enabling eavesdroppers to decode transmitted signals. The approach deliberately disguises the original modulation symbols as higher- or lower-order constellations, thereby misleading eavesdropper-side classifiers without degrading legitimate receiver performance. For the first time, this mechanism is systematically formulated to support both single- and multi-antenna systems as well as reconfigurable intelligent surface (RIS)-assisted scenarios. It integrates symbol random mapping, temporal diversity, series expansion, constellation trajectory design, and joint beamforming–RIS optimization to effectively thwart both deep learning–based and expert knowledge–driven modulation classifiers, significantly enhancing physical-layer security.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Machine Learning: Multimodal Learning
• Computer Vision: Multi-modal Vision

Application Category

• Security and Privacy: Applications of cryptography
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

With the increasing threat posed by modulation classification to wireless security, this paper proposes a secure communication framework based on modulation order confusion (MOC), which intentionally disguises the original modulation as a higher- or lower-order one to mislead eavesdroppers. For single-antenna systems, two schemes are developed: symbol random mapping and symbol time diversity, enabling modulation order confusion with customized receivers. For multi-antenna systems, receiver-transparent MOC schemes are proposed, including series-expansion-based and constellation-path-based signal designs, and are further extended to RIS-assisted systems with joint beamformer and RIS reflection design. Numerical results show that the proposed schemes effectively defeat both deep-learning-based and expert-knowledge-based modulation classifiers without degrading communication performance.

Problem

• secure communication
• modulation classification
• eavesdropping
• wireless security
• modulation order confusion

Innovation

• Modulation Order Confusion
• Secure Communication
• RIS-assisted Systems
• Symbol Time Diversity
• Constellation-Path Design