| Title | A Network Asset Detection Scheme Based on Website Icon Intelligent Identification |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Hu, Guangjun, Li, Haiwei, Li, Kun, Wang, Rui |
| Conference Name | 2021 Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS) |
| Keywords | artificial intelligence, artificial intelligence security, Communications technology, composability, Computer science, cyber security, Cyberspace, detection, Human Behavior, Internet, Manuals, Metrics, network asset, pubcrawl, resilience, Resiliency, security, Training, website icon |
| Abstract | With the rapid development of the Internet and communication technologies, efficient management of cyberspace, safe monitoring and protection of various network assets can effectively improve the overall level of network security protection. Accurate, effective and comprehensive network asset detection is the prerequisite for effective network asset management, and it is also the basis for security monitoring and analysis. This paper proposed an artificial intelligence algorithm based scheme which accurately identify the website icon and help to determine the ownership of network assets. Through experiments based on data set collected from real network, the result demonstrate that the proposed scheme has higher accuracy and lower false alarm rate, and can effectively reduce the training cost. |
| DOI | 10.1109/ACCTCS52002.2021.00057 |
| Citation Key | hu_network_2021 |
A Network Asset Detection Scheme Based on Website Icon Intelligent Identification