A detection method of lost assets based on feature optimization and active-passive detection
Jingchen Yan, Chenxi Cai, Zhe Hua Du, Jianbin Li · 2022
With the development of Internet technology, various network attacks have emerged one after another, seriously affecting the security of many key infrastructures such as finance, energy, and transportation. Therefore, the importance of network asset management is self-evident. How to judge the security of assets and detect lost assets has become an important research topic. This paper proposes a method for detecting lost assets based on feature optimization and active-passive detection. Firstly, it achieves the classification of abnormal traffic by extracting important features of the traffic data. And then, it detects the network assets using the combined active and passive detection method. The experiments show that this method can effectively detect the lost assets in the network and effectively provide an analysis basis for threat analysis and emergency response.