| Title | Intelligent Penetration and Attack Simulation System Based on Attack Chain |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Hao, Wei, Shen, Chuanbao, Yang, Xing, Wang, Chao |
| Conference Name | 2022 15th International Symposium on Computational Intelligence and Design (ISCID) |
| Date Published | dec |
| Keywords | artificial intelligence, composability, compositionality, Computational Intelligence, cryptography, Databases, decision making, Market research, Network security, penetration simulation system, Penetration Testing, Predictive models, pubcrawl, security, security assessment, Task Analysis, visualization, vulnerability assessment |
| Abstract | Vulnerability assessment is an important process for network security. However, most commonly used vulnerability assessment methods still rely on expert experience or rule-based automated scripts, which are difficult to meet the security requirements of increasingly complex network environment. In recent years, although scientists and engineers have made great progress on artificial intelligence in both theory and practice, it is a challenging to manufacture a mature high-quality intelligent products in the field of network security, especially in penetration testing based vulnerability assessment for enterprises. Therefore, in order to realize the intelligent penetration testing, Vul.AI with its rich experience in cyber attack and defense for many years has designed and developed a set of intelligent penetration and attack simulation system Ai.Scan, which is based on attack chain, knowledge graph and related evaluation algorithms. In this paper, the realization principle, main functions and application scenarios of Ai.Scan are introduced in detail. |
| Notes | ISSN: 2473-3547 |
| DOI | 10.1109/ISCID56505.2022.00052 |
| Citation Key | hao_intelligent_2022 |
Intelligent Penetration and Attack Simulation System Based on Attack Chain