基于主动探测的Web容器探测识别方法OA北大核心CSTPCD

As the Industrial Internet of Things rapidly evolves,enterprises are increasingly using a wide variety of web containers.However,this growing usage also magnifies the complexities associated with managing these assets,leading to a rise in network security risks and vulnerabilities.This trend not only highlights a shift in industrial practices but also underscores the urgent need for proactive measures to strengthen network security.In response to this complex challenge,this paper presents a cutting-edge approach for detecting and identifying web containers through proactive probing.During the detection phase,we meticulously construct web container probes,laying the groundwork for their central role in the identification process.During this stage,the probe leverages a payload-based identification method for web containers,achieving an exceptional level of accuracy by implementing advanced protocol decoding techniques.The integration of these innovative techniques not only enhances the precision of web container identification but also demonstrates our commitment to providing a comprehensive solution to the challenges posed by web container management.This pioneering methodology reflects the ongoing evolution of detection strategies and our dedication to pushing technological boundaries for an improved understanding of web containers.By seamlessly integrating these two advanced identification methods,we have successfully identified four different types of web containers.Importantly,we have made significant progress in precision and accurately differentiating between various versions of these web containers,with a total of ten versions correctly identified.This groundbreaking method is not only crucial for addressing the current complexities in web container asset management but also provides enterprises with a more effective means of network security defense.Through the use of this advanced proactive probing method,enterprises can better understand and manage their web container assets,reducing network security risks and ensuring system stability and security.Our contribution plays a pivotal role in the ongoing development of the Industrial Internet of Things and lays a strong foundation for future research and applications in network security.The innovative approach presented here serves as a catalyst for the positive advancement of the current Industrial Internet of Things landscape and lays a solid groundwork for future exploration and application in network security.