摘要
网络资产探测是指探测具有网络连接的硬件和软件,可以为企业、学校等网络资产全生命周期管理打下坚实的基础。结合资产标识、漏洞管理能够有效追溯每个资产的状态并及时弥补漏洞,避免造成经济损失。从网络资产探测相关技术角度出发,将相关技术分类为扫描识别技术、性能优化技术、隐蔽扫描技术和机器学习技术,先阐述当前技术面临的挑战,然后分析并总结各类技术的原理及其优缺点,最后对未来研究方向进行展望。
Network asset detection refers to the detection of hardware and software connected with network,which can lay a solid foundation for the full lifecycle management of network assets in enterprises,schools,etc.Combined with asset identification and vulnerability management,it can effectively trace the status of each asset and make up for vulnerabilities in time to avoid economic losses.From the perspective of technologies related to network asset detection,the technologies are classified as scanning technology,performance optimization technology,stealthy scanning technology and machine learning technology.Firstly,the challenges faced by current technologies are elaborated.Secondly,the principles,advantages and disadvantages of these technologies are analyzed.Finally,the future research directions are summarized.
作者
邵磊
余晓
吴剑章
Shao Lei;Yu Xiao;Wu Jianzhang(School of Cyber Science and Engineering,Southeast University,Nanjing 210096,China;School of Continuing Education,Southeast University,Nanjing 210096,China)
出处
《网络安全与数据治理》
2022年第11期3-9,35,共8页
CYBER SECURITY AND DATA GOVERNANCE
基金
中国高校产学研创新基金(2020ITA07007)。
关键词
网络资产探测
操作系统识别
流量分析
搜索引擎
机器学习
network asset detection
operating system identification
traffic analysis
search engine
machine learning
