Smart robots’ virus defense using data mining technology

IF 2.1 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jiao Ye, Hemant N. Patel, Sankaranamasivayam Meena, Renato R. Maaliw, Samuel-Soma M. Ajibade, Ismail Keshta
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引用次数: 0

Abstract

Abstract In order to realize online detection and control of network viruses in robots, the authors propose a data mining-based anti-virus solution for smart robots. First, using internet of things (IoT) intrusion prevention system design method based on network intrusion signal detection and feedforward modulation filtering design, the overall design description and function analysis are carried out, and then the intrusion signal detection algorithm is designed, and finally, the hardware design and software development for a breach protection solution for the IoT are completed, and the integrated design of the system is realized. The findings demonstrated that based on the mean value of 10,000 tests, the IoT’s average packet loss rate is 0. Conclusion: This system has high accuracy, good performance, and strong compatibility and friendliness.
基于数据挖掘技术的智能机器人病毒防御
摘要为了实现机器人网络病毒的在线检测与控制,提出了一种基于数据挖掘的智能机器人反病毒解决方案。首先,采用基于网络入侵信号检测和前馈调制滤波设计的物联网(IoT)入侵防御系统设计方法,进行总体设计描述和功能分析,然后设计入侵信号检测算法,最后完成针对物联网的入侵防御解决方案的硬件设计和软件开发,实现系统的集成化设计。结果表明,以10000次测试的平均值计算,物联网的平均丢包率为0。结论:该系统准确度高,性能好,兼容性和友好性强。
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来源期刊
Journal of Intelligent Systems
Journal of Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
5.90
自引率
3.30%
发文量
77
审稿时长
51 weeks
期刊介绍: The Journal of Intelligent Systems aims to provide research and review papers, as well as Brief Communications at an interdisciplinary level, with the field of intelligent systems providing the focal point. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. It covers contributions from the social, human and computer sciences to the analysis and application of information technology.
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