Power communication network attack penetration testing system based on knowledge map

Wei Wang; Xuqiu Chen; Xin He; Kunhua Chen; Zhuojun Ying; Keyao Chun

doi:10.1117/12.2672765

16 March 2023 Power communication network attack penetration testing system based on knowledge map

Wei Wang, Xuqiu Chen, Xin He, Kunhua Chen, Zhuojun Ying, Keyao Chun

Proceedings Volume 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022); 125931H (2023) https://doi.org/10.1117/12.2672765
Event: 2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 2022, Guangzhou, China

Abstract

The power network's operation security contributes to the power grid's smooth operation. Aiming at the problem that each network node in the conventional power communication network attack penetration system is fragile, and the global network attack graph cannot be generated, which leads to the failure of the network attack penetration vulnerability test, this study introduces the knowledge map into it and designs a power communication network attack penetration test system. In hardware, the FPGA chips and RAM are designed. In terms of software, the software architecture of the test system is established to control the network attack penetration globally, and then the knowledge map is used to construct the communication network attack graph model and generate the network global attack graph, so as to realize the effective test of the electric power communication network attack penetration vulnerability. By using the method of system testing, it is verified that the number of vulnerabilities tested by the system is consistent with the actual situation, and it can be applied to real life.

Citation Download Citation

Wei Wang, Xuqiu Chen, Xin He, Kunhua Chen, Zhuojun Ying, and Keyao Chun "Power communication network attack penetration testing system based on knowledge map", Proc. SPIE 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 125931H (16 March 2023); https://doi.org/10.1117/12.2672765

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available