基于ASSM算法的主动资产探测技术研究  

Research on Active Asset Detection Technology Based on ASSM Algorithm

作　　者：史明慧 SHI Minghui(CHN Energy Digital Intelligence Technology Development(Beijing)Co.,Ltd.,Beijing 100011)

机构地区：[1]国能数智科技开发(北京)有限公司,北京100011

出　　处：《软件》2024年第12期107-109,共3页Software

摘　　要：随着智能设备和物联网设备的普及,网络资产管理面临挑战。传统的资产探测方法依赖协议识别和指纹比对,难以应对设备种类和场景的变化。本文提出了一种基于资产语义相似度模型的主动资产探测方法,通过分析终端设备托管的Web服务信息,提取语义特征并建立资产语义数据库,从而提高设备类型的识别准确率。同时,该方法引入了深度学习中的注意力机制和卷积神经网络,进一步增强了特征提取和识别能力。与传统方法相比,该方法能够更好地适应设备的多样性和复杂性,特别适用于物联网环境。With the proliferation of smart devices and IoT devices,network asset management faces significant challenges.Traditional asset detection methods rely on protocol identification and fingerprint matching,which struggle to adapt to the diversity of devices and scenarios.This paper proposes an active asset detection method based on the Asset Semantic Similarity Model.By analyzing the web service information hosted by terminal devices,semantic features are extracted,and an asset semantic database is constructed to improve the accuracy of device type identification.At the same time,this method introduces attention mechanisms and convolutional neural networks from deep learning,further enhancing feature extraction and recognition capabilities.Compared with traditional methods,this approach better accommodates the diversity and complexity of devices,making it particularly suitable for IoT environments.

关 键 词：网络资产探测 资产语义相似度模型 主动探测 深度学习 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]