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基于深度生成模型的医院网络异常信息入侵检测算法

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为保障医院信息网络的安全管理,避免医疗信息泄露,提出了基于深度生成模型的医院网络异常信息入侵检测算法.采用二进制小波变换方法,多尺度分解医院网络运行数据,结合自适应软门限去噪系数提取有效数据.运用最优运输理论中的Wasserstein距离算法与MMD(Maximun Mean Discrepancy)距离算法,在深度生成模型中,对医院网络数据展开降维处理.向异常检测模型中输入降维后网络正常运行数据样本,并提取样本特征.利用深度学习策略中的Adam算法,生成异常信息判别函数,通过待测网络运行数据与正常网络运行数据的特征对比,实现医院网络异常信息入侵检测.实验结果表明,算法能实现对医院网络异常信息入侵的高效检测,精准检测多类型网络入侵行为,为医疗机构网络运行提供安全保障.
Based on Deep Generative Models,Hospital Network Abnormal Information Intrusion Detection Algorithm
In order to ensure the security management of the hospital information network and avoid medical information leakage,an intrusion detection algorithm for abnormal information in the hospital network based on deep generative model was proposed.Using binary wavelet transform method,multi-scale decomposition of hospital network operation data,combined with adaptive soft threshold denoising coefficient to extract effective data.The Wasserstein distance algorithm and MMD(Maximun Mean Discrepancy)distance algorithm in the optimal transportation theory are used to reduce the dimension of the hospital network data in the depth generative model,input the reduced dimension network normal operation data samples into the anomaly detection model,and extract the sample characteristics.Using the Adam algorithm in deep learning strategy,generate an anomaly information discrimination function,and compare the characteristics of the tested network operation data with the normal network operation data to achieve hospital network anomaly information intrusion detection.The experimental results show that the algorithm can achieve efficient detection of abnormal information intrusion in hospital networks,accurately detect multiple types of network intrusion behaviors,and provide security guarantees for the network operation of medical institutions.

binary wavelet transformdepth generative modelwasserstein distance algorithmmaximun mean discrepancy(MMD)distance algorithmhospital networkabnormal informationintrusion detection

吴风浪、李晓亮

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西安交通大学第一附属医院,西安 710061

二进制小波变换 深度生成模型 Wasserstein距离算法 MMD距离算法 医院网络 异常信息 入侵检测

陕西省重点研发计划基金资助项目

2022SF-388

2024

吉林大学学报(信息科学版)
吉林大学

吉林大学学报(信息科学版)

CSTPCD
影响因子：0.607
ISSN：1671-5896
年,卷(期)：2024.42(5)