Model of Database NIDS Based on Artificial Immunology

doi:10.3969/j.issn.1000-3428.2006.20.054

Computer Engineering ›› 2006, Vol. 32 ›› Issue (20): 150-152.

• Security Technology • Previous Articles Next Articles

Model of Database NIDS Based on Artificial Immunology

WANG Yong 1,2, HUANG Guoxing1, PENG Daogang3

(1. Information Institute, East China Normal University, Shanghai 200062; 2. Dept. of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090; 3. Dept. of Information and Control Technology, Shanghai University of Electric Power, Shanghai 200090)

Received:1900-01-01 Revised:1900-01-01 Online:2006-10-20 Published:2006-10-20

基于人工免疫的NIDS数据库模型

王勇1,2，黄国兴1，彭道刚3

(1. 华东师范大学信息学院，上海 200062；2. 上海电力学院计算机科学与技术系，上海 200090； 3. 上海电力学院信息与控制技术系，上海 200090)

Abstract

Abstract: This paper gives a NIDS model using basics of relational database. This model is established on distributed self-organized characteristics of natural immune systems. It stresses on intrusion selection, recombination, reproduction of artificial immune system. A k-mating algorithm is given. The result of the experiment proves that the model is effective.

Key words: Intrusion detection, Network security, Artificial immunology

摘要： 结合关系数据库的常用方法，提出了一种网络入侵检测模型。该模型是根据人工免疫系统分布式自组织特征建立的。研究了人工免疫系统中的入侵、选择、交叉和复制的特征，给出了R位连续匹配算法。实验结果表明该模型是有效的。

关键词: 入侵检测, 网络安全, 人工免疫

WANG Yong ; HUANG Guoxing; PENG Daogang. Model of Database NIDS Based on Artificial Immunology[J]. Computer Engineering, 2006, 32(20): 150-152.

王勇;黄国兴;彭道刚. 基于人工免疫的NIDS数据库模型[J]. 计算机工程, 2006, 32(20): 150-152.

/ Recommend / Download Citations

URL:

https://www.ecice06.com/EN/Y2006/V32/I20/150

[1]	Qiong SHI, Hui DUAN, Zhibin SHI. Trusted Task Offloading Scheme Based on Deep Reinforcement Learning [J]. Computer Engineering, 2024, 50(8): 142-152.
[2]	ZHANG Huiyan, LIANG Yong, LAN Jinghong, ZHAO Qiang. Intrusion Detection Method Based on Memory Module and Filtered Generative Adversarial Network [J]. Computer Engineering, 2024, 50(6): 197-207.
[3]	YU Changhong, XU Konghao, ZHANG Ze, GAO Ming. Improving Network Intrusion Detection Methods in Isolated Forests Based on Split Points [J]. Computer Engineering, 2024, 50(6): 148-156.
[4]	Hong CHEN, Hanwen WANG, Haibo JIN. Intrusion Detection Model Combining Improved Self-Encoder and Residual Network [J]. Computer Engineering, 2024, 50(2): 188-195.
[5]	SHEN Xueli, LIU Shifeng. Intrusion Detection Model Based on Graph Edge Feature Attention [J]. Computer Engineering, 2024, 50(11): 236-245.
[6]	Sha ZHOU, Guowei SHEN, Chun GUO. Vulnerability Information Completion Based on Security Knowledge Graph and Reverse Features [J]. Computer Engineering, 2024, 50(1): 145-155.
[7]	Changhong YU, Ya LU, Haixin WANG, Ming GAO. Traffic Classification Algorithm for IoT Device Based on Sliding Time Window [J]. Computer Engineering, 2023, 49(7): 259-268.
[8]	CHEN Zhonglei, YI Peng, CHEN Xiang, HU Tao. Real-time Anomaly Detection Framework via System Calls Based on Integrated Learning [J]. Computer Engineering, 2023, 49(6): 162-169,179.
[9]	SHI Lei, ZHANG Jitao, GAO Yufei, WEI Lin, TAO Yongcai. Intrusion Detection of Network Traffic Based on Transformer and BiLSTM [J]. Computer Engineering, 2023, 49(3): 29-36,57.
[10]	LIU Qiang, ZHANG Ying, ZHOU Weixiang, JIANG Xiantao, ZHOU Weina, ZHOU Mouguo. Adaptive Class Incremental Learning-Based IoT Intrusion Detection System [J]. Computer Engineering, 2023, 49(2): 169-174.
[11]	Tianyu CHEN, Chengqian CHU, Siyuan WAN, Yongjing WAN, Jing SUN. Video Intrusion Detection Algorithm Based on Conditional Lightweight Neural Network [J]. Computer Engineering, 2023, 49(12): 152-160.
[12]	SUN Yangwei, QI Yong. Intrusion Detection Method for In-Vehicle CAN Based on Cluster Mixed Sampling and PSO-Stacking [J]. Computer Engineering, 2023, 49(1): 138-145.
[13]	LIU Jinshuo, ZHAN Daiyi, DENG Juan, WANG Lina. Network Intrusion Detection Based on Deep Neural Network and Federated Learning [J]. Computer Engineering, 2023, 49(1): 15-21,30.
[14]	DONG Weiyu, LI Haitao, WANG Ruimin, REN Huajuan, SUN Xuekai. Network Traffic Anomaly Detection Model Based on Stacked Convolutional Attention [J]. Computer Engineering, 2022, 48(9): 12-19.
[15]	JIN Haibo, ZHAO Xinyue. High-Reliability Intrusion Detection Algorithm Under Conformal Prediction Framework [J]. Computer Engineering, 2022, 48(7): 130-140.

Please choose a citation manager

Content to export

Model of Database NIDS Based on Artificial Immunology

基于人工免疫的NIDS数据库模型

PDF

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

模态框（Modal）标题

Please choose a citation manager

Content to export

Model of Database NIDS Based on Artificial Immunology

基于人工免疫的NIDS数据库模型

PDF

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments