Mr. Yongmin Cao Profile

Yongmin Cao

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Proceedings Article | 11 July 2024 Paper

Network intrusion detection algorithm combining blockchain and federated learning

Dongyang Cai, Kaili Zhao, Jie Bai, Rui Bo, Xuening Zhang, Guopeng Zhao, Yongmin Cao

Proceedings Volume 13210, 132101B (2024) https://doi.org/10.1117/12.3034788

KEYWORDS: Blockchain, Computer intrusion detection, Data transmission, Data processing, Data modeling, Computer security, Network security, Optical transmission, Detection and tracking algorithms

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With the development of network security technology, the situation of network intrusion is becoming increasingly serious. Traditional network intrusion detection methods have the problem of low detection efficiency and the lack of encryption processing in detection rules, which may be cracked by attackers. In order to improve the intrusion detection ability of frequent data transmission in the network, In this paper, a federated learning method based on blockchain technology is proposed, which uses blockchain technology, chain data structure and data block rules to verify the relevant information in passwords, and inserts password strings in multiple blocks to improve the intrusion detection ability of network information. At the same time, this paper analyzes the reasons of information theft and interference, summarizes the characteristics of network intrusion, puts forward the design idea of integrating blockchain technology, and verifies the correctness of this processing method, the fitting of network data and the degree of intrusion detection through actual cases. MATLAB simulation results show that the federated learning method has better network intrusion ability, the intrusion detection degree is over 90%, and the intrusion detection ability rises first and then declines, the overall index is better than the online monitoring method. Therefore, the fusion of blockchain and federated learning method proposed in this paper is suitable for the optimization of network intrusion monitoring. There are still some shortcomings in this research, mainly because there are few research materials related to blockchain technology, which leads to less research data in this paper, and more data will be collected for analysis in the future.

Proceedings Article | 8 December 2022 Paper

Research on security defect assessment technology for Java source code

Dongyang Cai, Yue Sun, Xiaolong Su, Yongmin Cao

Proceedings Volume 12474, 124740K (2022) https://doi.org/10.1117/12.2653742

KEYWORDS: Information security, Java, Network security, Computer security, Defect detection, Computer programming

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In recent years, with the rapid development of technology fields such as big data, cloud computing, Internet of Things, and mobile Internet, security incidents such as network attacks and data information leakage have occurred frequently, which shows that the current information system falls in the serious security situation, and methods relying on the traditional security protection mechanism to ensure information security has gradually become inadequate. Compared with other software languages, Java language is widely used in the development of large-scale business systems due to its high access, concurrency, and clustering. Source code is the basic element of building a business application system, and logic vulnerabilities or nonstandard programming in code are the roots of application security events. This paper proposes a source code security defect assessment method based on the entropy weight method by deeply analyzing the Java source code security defect detection and repair methods.

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