Biblio
Filters: Author is Ma, Yuanyuan [Clear All Filters]
.
2021. Building A Zero-trust Security Protection System in The Environment of The Power Internet of Things. 2021 2nd International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT). :557–560.
With the construction of power information network, the power grid has built a security protection system based on boundary protection. However, with the continuous advancement of the construction of the power Internet of Things, a large number of power Internet of Things terminals need to connect to the power information network through the public network, which have an impact on the existing security protection system of the power grid. This article analyzes the characteristics of the border protection model commonly used in network security protection. Aiming at the lack of security protection capabilities of this model, a zero-trust security architecture-based power Internet of Things network security protection model is proposed. Finally, this article analyzes and studies the application of zero trust in the power Internet of Things.
.
2021. Research on Key Node Method of Network Attack Graph Based on Power Information Physical System. 2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC)2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC). :48–51.
With the increasing scale of network, the scale of attack graph has been becoming larger and larger, and the number of nodes in attack graph is also increasing, which can not directly reflect the impact of nodes on the whole system. Therefore, in this paper, a method was proposed to determine the key nodes of network attack graph of power information physical system to solve the problem of uncertain emphasis of security protection of attack graph.
.
2019. Research on Mobile Application Local Denial of Service Vulnerability Detection Technology Based on Rule Matching. 2019 IEEE International Conference on Energy Internet (ICEI). :585–590.
Aiming at malicious application flooding in mobile application market, this paper proposed a method based on rule matching for mobile application local denial of service vulnerability detection. By combining the advantages of static detection and dynamic detection, static detection adopts smali abstract syntax tree as rule matching object. This static detection method has higher code coverage and better guarantees the integrity of mobile application information. The dynamic detection performs targeted hook verification on the static detection result, which improves the accuracy of the detection result and saves the test workload at the same time. This dynamic detection method has good scalability, can be upgraded with discovery and variants of the vulnerability. Through experiments, it is verified that the mobile application with this vulnerability can be accurately found in a large number of mobile applications, and the effectiveness of the system is verified.