| Computer Technology |
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| Performance analysis of distributed detection under sensing data falsification attack |
Xiao-yan ZHENG( ),Hui-fang CHEN*(),Lei XIE |
| College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China |
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Abstract The performance of distributed detection in the presence of sensing data falsification (SDF) attack was studied for the security problem of distributed detection. A probabilistic inverse SDF attack model was defined to characterize the malicious behavior falsifying initial sensing data. Taking the detection probability, false-alarm probability and error probability as the performance metrics, closed-form performance expressions for consensus-based distributed detection with defined SDF attack model were derived, and the steady-state and transient-state performance of distributed detection under SDF attack was analyzed. Using the deflection coefficient as objective function, the blind condition was deduced, which is the attack strategy of malicious nodes to make distributed detection system invalid. Simulation results show that the system performance degradation is caused by the SDF attack and different attack parameters have effect on the performance of consensus-based distributed detection.
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Received: 17 March 2018
Published: 04 March 2019
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Corresponding Authors:
Hui-fang CHEN
E-mail: 21631151@zju.edu.cn;chenhf@zju.edu.cn
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感知数据错误化攻击下分布式检测的性能分析
针对分布式检测的安全问题，研究分布式检测中感知数据错误化（SDF）攻击及其对检测性能造成的影响. 定义一种概率型翻转攻击模型描述攻击者篡改初始感知数据的恶意行为. 以检测概率、虚警概率和错误概率为性能指标，推导在所提出的攻击模型下分布式系统检测性能的闭合表达式，进而分析SDF攻击下分布式检测系统的稳态性能和瞬态性能. 以偏移系数为目标函数，推导使分布式检测失效的盲化条件，即分布式系统无法检测出目标的真实状态时所对应的恶意节点攻击策略. 仿真结果表明：SDF攻击会恶化系统检测性能，且不同攻击参数会对检测性能造成不同程度的影响.
关键词：
分布式检测,
安全,
感知数据错误化（SDF）攻击,
一致性算法,
偏移系数
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