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    • 基于大数据的网络信息安全认证仿真研究

    HE Hai-zhu,QIAO Shi-cheng

    Computer Simulation（2023）

    内蒙古民族大学

    Cited 0|Views6
    Abstract
    多种安全态势要素共同作用下会影响网络信息安全认证效果,为了增强网络信息认证的可靠性及精度,提出基于大数据的网络信息安全认证仿真研究.上述方法依据大数据分析方法提取网络信息特征属性,建立网络安全态势要素获取模型,提取网络安全态势要素,实现对安全态势要素的充分分析,降低其对网络信息安全认证的负面影响;采用频率水印嵌入算法构建网络信息的水印模型,依据傅立叶变换方法计算网络信息嵌入频率水印;最后依据嵌入水印完成网络信息的安全认证.实验结果表明,运用所提方法开展网络信息安全认证时,信息覆盖程度高、安全认证时间短以及认证效果好.
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    Key words
    Big data,Network information,Security authentication,Security situation element,Frequency water-mark embedding algorithm
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    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
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