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Design of intelligent manufacturing monitoring system for internet of things based on encryption technology and intrusion detection technology

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THERMAL SCIENCE AND ENGINEERING PROGRESS 2024年 54卷

作者： Tian, Jiahao Mao, Wenjing Shao, Lisong Wang, Tiancheng Faizan, Mohammad Chen, Yutang Gao, Jian Shaoxing Univ Sch Mech & Elect Engn Shaoxing 312000 Peoples R China Shaoxing Univ Sch Marxism Shaoxing 312000 Peoples R China Nanjing Forestry Univ Res Inst Chinese Ecol Progress & Forestry Dev Nanjing 210037 Peoples R China Maulana Azad Natl Urdu Univ Sch Sci Bot Sect Hyderabad 500032 India Nanjing Forestry Univ Nanjing 210037 Peoples R China Inovance Technol Co Ltd Shenzhen 518110 Peoples R China

With the rapid development of intelligent manufacturing, energy consumption and safety issues have gradually attracted widespread attention. Heat loss not only leads to energy waste, but also may affect the efficiency of equipment operation and production safety. Therefore, this study aims to design an efficient iot intelligent manufacturing monitoring system, focusing on the synergistic effect of heat loss energy management and intrusion detection to improve energy utilization efficiency and optimize security monitoring. The system uses a sensor network to monitor the heat loss in the manufacturing environment in real time, and evaluates the energy efficiency performance combined with data analysis algorithms. Through intrusion detection technology, realtime monitoring of system security, using machine learning models to identify abnormal behavior. Integrate heat loss management and security monitoring to build an intelligent manufacturing platform based on the Internet of Things. The experimental results show that the monitoring system can effectively reduce the energy heat loss and improve the accuracy of intrusion detection. The implementation of the system significantly improves the energy efficiency and safety of the production line, reducing potential safety hazards. Therefore, the iot intelligent manufacturing monitoring system designed in this paper effectively integrates heat loss energy management and intrusion detection technology, and provides an efficient solution for intelligent manufacturing.

关键词： Heat loss Energy management intrusion detection technology Internet of things Intelligent manufacturing Monitoring system design

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Application of intrusion detection technology in network safety based on machine learning

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SAFETY SCIENCE 2020年第0期124卷 104604-000页

作者： Fang, Weijian Tan, Xiaoling Wilbur, Dominic Chongqing Three Gorges Univ Coll Comp Sci & Engn Chongqing Peoples R China Chongqing Three Gorges Univ Coll Elect & Informat Engn Chongqing Peoples R China Univ Rochester Dept Comp Sci Rochester NY 14627 USA

As an important means to ensure network safety, intrusion detection technology can be much more efficient by introducing machine learning. The present paper proposes a machine learning method for intrusion information detection, which can fully exploit the envelope advantages of Elman neural network and the advantages of robust SVM noise data elimination, and can then combine the two to solve the safety risks of intrusion detection of information systems to ensure the safety of information systems. Elman neural network intrusion detection clusters the text of the network packet by clustering algorithm, which largely reduces the defect of missing text information. It also improves the ability to detect abnormal behaviour between network packet sequences. Meanwhile, robust SVM neighbour classification intrusion detection can achieve the feature space weighting of the optimal classification face host system log, eliminate the negative impact of noise data, reduce the false alarm rate of intrusion detection, and improve the detection accuracy. The result shows that when the false alarm rate is 0, the intrusion detection rate based on robust SVM neighbour classification can achieve 87.3%;when the false alarm rate is 2.8%, the detection rate can reach as high as 100%.

关键词： Network safety Machine learning method intrusion detection technology Elman neural network Robust SVM

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Research on intrusion detection technology Based on Artificial Intelligence Algorithms

Research on Intrusion Detection Technology Based on Artifici...

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作者： Jing Huayang Yunnan Arts University Wenhua College

With the rapid development of information technology and computers, the number of attacks on the network is increasing, and a single firewall can no longer meet the needs of Internet users. The application of intrusion detection technology provides a security barrier for enterprise networks to be attacked. The emergence of intelligent algorithm intrusion detection system speeds up the speed of intrusion detection and the ability to prevent information. For example, record intrusion behavior, track intrusion behavior, recover or disconnect. This paper expounds the classification of intrusion detection technology, and verifies the effectiveness of the algorithm by analyzing intelligent detection technology and combining genetic algorithm and intrusion detection technology.

关键词： Artificial Intelligence Algorithms intrusion detection technology

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Research on intrusion detection technology Based on Nodes Optimization Deployment in Wireless Sensor Networks

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INTERNATIONAL JOURNAL OF SECURITY AND ITS APPLICATIONS 2016年第8期10卷 159-172页

作者： Sun, Zeyu Li, Longxing Li, Xuelun Luoyang Inst Sci Technol Sch Comp & Informat Engn Luoyang 471023 Henan Peoples R China Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Shanxi Peoples R China Tianjing Univ Sch Elect Informat Engn Tianjin 300072 Peoples R China

Security issues of wireless sensor networks (WSNs) have become increasingly prominent. As a reasonable complement for encryption, authentication and other security mechanisms, intrusion detection technology has become an important domain of WSNs security research. So it has very academic and practical value to design an intrusion detection approach adapting to wireless sensor networks characteristics. At the basis of the reputation computing model we designed, and after analyzing features of the sensor networks intrusion detection mechanism, we proposed an intrusion detection model based on trusty nodes inside clusters make use of the reputation computing model to calculate the coordinate nodes synthetic reputation values to check whether some invasion has taken place. If some nodes are being intruded, the messages will be reported to cluster head. When the numbers of the reporting nodes are more than the specified the head will report the information to sink nodes and start intrusion response at the same time. The experimental results show that the designed models can identify vicious nodes and low competitive nodes, helping to promote the security and reliability of the network, and embodying the equity of the network.

关键词： wireless sensor networks (WSNs) intrusion detection technology trust management behavior trust reputation model

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FWA-SVM Network intrusion Identification technology for Network Security

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IEEE ACCESS 2025年 13卷 18579-18593页

作者： Zhang, Yaohui Hunan Post & Telecommun Coll Informat & Commun Dept Changsha 410000 Hunan Peoples R China

In the digital age, the increasing demand for network security has driven research on efficient network intrusion detection systems. The effectiveness of traditional network intrusion is limited in the face of complex network attacks and constantly increasing data volume. Support vector machine has attracted much attention for its excellent classification ability, but it faces challenges in feature selection and parameter optimization when dealing with large-scale high-dimensional data. Therefore, the study introduces the fireworks algorithm to improve it and optimize parameter selection and feature subset selection. The study also proposes a discretized binary fireworks algorithm to further improve the efficiency and adaptability of support vector machines in feature selection. The experiment outcomes denote that on the feature dense Sonar dataset, the average number of features selected by the proposed method is 24.39, a decrease of 25.51% compared to the comparison algorithm, and a classification accuracy improvement of 2.99%. The average detection rate of the raised method is 96.43%, the false alarm rate is 0.91, and the average correlation coefficient is as high as 0.987, which is better than the other four comparative algorithms. The training and testing time are 26.12 seconds and 11.23 seconds, respectively. Consequently, the primary contribution of the research lies in solving key problems in network intrusion detection through the BFWA-SVM model. Introducing the discrete fireworks algorithm to optimize support vector machines has improved the ability to process large-scale high-dimensional data. This model significantly reduces false positive and false negative rates, enhances real-time security awareness, and provides new guidance for network security management.

关键词： Support vector machines Optimization Feature extraction Classification algorithms Accuracy Network security Fireworks algorithm Adaptation models Convolutional neural networks High dimensional data FWA SVM network security intrusion detection technology binary encoding feature selection

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Artificial intelligence detection system based on multi-sensor and wireless communication

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INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2024年第3期18卷 2577-2588页

作者： Li, Qiang Zibo Vocat Inst Sch Artificial Intelligence & Big Data Zibo Shandong Peoples R China

In today's world, Internet technology and wireless communication technology are becoming more and more mature, which has brought massive network information resources to all sectors of society. At the same time, the phenomenon of data loss caused by illegal network intrusion is becoming more and more common. Therefore, it is necessary to identify and deal with them in combination with IDS (intrusion detection system). The problem of data processing is also very important. Enterprises can build a data management system according to their own needs, and use this system to process data. With the help of science and technology, AI (Artificial Intelligence) technology has become more mature and applied in many industries. Therefore, this paper proposed to build an AI IDS, and combined the deep RL (reinforcement learning) algorithm to analyze the performance of the system. This paper tested and analyzed the system from the aspects of precision and recall. The experimental results showed that the average precision of the five data sets was 94.76%, and the average recall rate was 91.4%. From the above data, combined with the algorithm in this paper, the precision and recall of the system have been significantly improved. This paper also conducted benchmark energy consumption comparison experiments for different cloud data management systems. The results showed that in terms of loading, the benchmark energy consumption of HBase was the lowest, which was 86KJ. In terms of query, the benchmark energy consumption of GridSQL was the lowest, which was 56KJ. It can be seen that different systems have their own advantages in the benchmark energy consumption of loading and query.

关键词： Artificial intelligence intrusion detection technology artificial intelligence intrusion detection system data management system

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Application and optimization of intrusion detection system based on Artificial Intelligence 2

Application and optimization of intrusion detection system b...

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2nd IEEE International Conference on Civil Aviation Safety and Information technology (ICCASIT)

作者： Zhu, Kaidi Wu, Xiangwen Yu, Sun Huo, Da Li, Rui Pei, Xikai Second Res Inst CAAC Chengdu Peoples R China Inner Mongolia Autonomous Reg Civil Airports Grp Hulun Buir Branch Hulunbeir Peoples R China North China Regionnal Air Traff Management Bur CA Beijing Peoples R China China Civilaviat Adm Air Traff Management Bur Beijing Peoples R China

ISBN: (纸本)9781728199481

The traditional perimeter intrusion detection system will be faced more challenges in the new era, such as high-accuracy positioning, low energy dependence, high environmental robustness and so on. This paper introduces a new type of artificial intelligence intrusion detection technology. The RF sensor chip is embedded in the detection cable, and the radio frequency electromagnetic environment is formed in space through the sending and receiving of radio frequency signal, which is used to sense the surrounding environment to detect electromagnetic *** advanced space-time signal processing technology and machine learning technology, the influence of environmental interference on the system is effectively eliminated, and the intrusion detection system based on artificial intelligence algorithm has lower false alarm rate and higher environmental robustness.

关键词： image processing machine learning intrusion detection technology Microwave array technology

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Design and Implementation of an “Intruding detection System” for Web Server

Design and Implementation of an “Intruding Detection System...

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2012 International Conference on Management Sciences and Information technology(MSIT 2012)

作者： Yang Zong-chang School of Information and Electronical Engineering Hunan University of Science and Technology

Situation of Internet security in China is facing serious challenges though it has made a rapid development in information field. intrusion detection technology is a developing network security technology. However, many administers of web server and small businesses hesitate to buy its productions, for its high costs due to its complex implementing methods to achieve its active and initiative pre-defense. In this paper, an idea of "intruding detection system" based on the passive current-defense and workable implementation is proposed. By using change-notification mechanism that real-timely monitoring the changes of file conditions of web page resource, while capturing IP packets by sniffing technique to decode TCP packets and analyze data in the TCP packets according to HTTP, network's behaviors of the web visitor can be tracked, and corresponding countermeasures will be taken when intruding happens. Considering window operation systems are widely used in many small businesses and PC, one practical design and implementation for web server in windows is presented.

关键词： intrusion detection technology Network security Web server intruding detection systems Windows

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Study on Campus Network Security and Protection technology

Study on Campus Network Security and Protection Technology

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2nd International Conference on Advanced Design and Manufacturing Engineering (ADME 2012)

作者： Fu, Weihong Liu, Jianhua Anyang Inst Technol Anyang 455000 Peoples R China

ISBN: (纸本)9783037855034

While the popularization of campus network plays an inestimable role in accelerating the information processing, making full use of excellent education resources, improving work efficiency and implementing the resources sharing, the security of campus network has become more and more prominent. This paper based on the analysis on the current situation of campus network, proposes some strategies to put the security under control. The strategies proposed have been put into application, which has improved the network management efficiency and strengthened the availability and controllability of campus network.

关键词： Campus network Hackers Firewal intrusion detection technology

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Study on Campus Network Security and Protection technology

Study on Campus Network Security and Protection Technology

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2011 3rd IEEE International Conference on Information Management and Engineering(ICIME 2011)

作者： Fu Weihong Anyang Institute of technology Anyang,China 455000 Liu Jianhua Senior High School in Anyang Developing District Anyang,China 455000

While the popularization of campus network plays an inestimable role in accelerating the information processing,making full use of excellent education resources,improving work efficiency and implementing the resources sharing,the security of campus network has become more and more *** paper based on the analysis on the current situation of campus network,proposes some strategies to put the security under *** strategies proposed have been put into application,which has improved the network management efficiency and strengthened the availability and controllability of campus network.

关键词： Campus network Hackers,Firewall intrusion detection technology

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