Zheng Zhouqiang, Song Haiyu, Zhang Wen-An, Fang Jinglong, Yu Li
IEEE Trans Cybern. 2025 Oct;55(10):4634-4646. doi: 10.1109/TCYB.2025.3589505.
This article presents a comprehensive theoretical framework for addressing the problem of secure fusion estimation in energy-constrained multisensor systems, specifically targeting hybrid attacks in multiple transmission levels. The lifespan of sensor nodes is constrained by the availability of energy supply, and all the sensors have the flexibility to choose between high-energy or low-energy levels for transmitting their measurements. Sensor data becomes vulnerable to malicious tampering when operating in a low-energy level, whereas the high-energy transmission level enables accurate data transmission. By introducing a set of Bernoulli random variables and ternary random variables, a novel measurement model is proposed to characterize scenarios involving both dual-energy transmission modes and hybrid attacks, including three statuses: safe, deception attacks, and Denial-of-Service attacks. Based on the innovation analysis approach, local secure estimators are designed to ensure that the estimation errors are minimized locally. Then, an optimal secure fusion algorithm is provided to generate the final estimated value by fusing all the local estimates. Additionally, the proposed secure fusion estimation algorithm's stability and steady-state properties are investigated. Finally, two simulation cases are conducted to provide the empirical evidence of the superior performance of the proposed approach.
本文提出了一个全面的理论框架，用于解决能量受限多传感器系统中的安全融合估计问题，特别针对多传输级别中的混合攻击。传感器节点的寿命受能量供应可用性的限制，并且所有传感器都可以灵活选择在高能量或低能量级别传输其测量值。当在低能量级别运行时，传感器数据容易受到恶意篡改，而高能量传输级别则能够实现准确的数据传输。通过引入一组伯努利随机变量和三元随机变量，提出了一种新颖的测量模型，以表征涉及双能量传输模式和混合攻击的场景，包括三种状态：安全、欺骗攻击和拒绝服务攻击。基于创新分析方法，设计了局部安全估计器，以确保局部估计误差最小化。然后，提供了一种最优安全融合算法，通过融合所有局部估计来生成最终估计值。此外，还研究了所提出的安全融合估计算法的稳定性和稳态特性。最后，进行了两个仿真案例，以提供所提方法具有卓越性能的经验证据。
