Artificial intelligence and machine learning aided blockchain systems to address security vulnerabilities and threats in the industrial Internet of things

Baqasah

et al. 2023

In order to improve the library's information retrieval and resource sharing capabilities and establish an intelligent library information management system, this paper proposes a library information management system development technology based on data mining technology. The system development is divided into two modules: library information retrieval and data mining algorithm design and software development of information management system. Using big data fusion and feature clustering methods to design intelligent information retrieval algorithm in library information management, establish library management database, carry out software development and design of library information management system in embedded environment, and finally carry out experimental test analysis. The test results show that using the method in this paper for library information management can improve the accuracy of book recommendation, which is 16.7% higher than the traditional method on average, and has good data mining and information retrieval capabilities. Performance indicators are better. Therefore, the algorithm is not only a means of automatic management of library systems, but also an effective means of realizing the modernization of library information.Povzetek: Sistem upravljanja knjižnice je nadgrajen z metodami strojnega rudarjenja in gručenja.

Section: Analysis Of Library Information Managementmentioning

confidence: 99%

Study on Library Management System Based on Data Mining and Clustering Algorithm

Wang¹,

Baqasah

et al. 2023

“…Although face recognition technology is in continuous development and improvement [13][14][15][16][17][18][19][20], the recognition rate, anti-counterfeiting, fingerprint, retina, and other has a large gap [21][22][23][24][25]. The large passenger flow and complex environmental characteristics of urban rail transit also affect the application of face recognition technology in urban rail transit.…”

Section: Literature Reviewmentioning

confidence: 99%

Design and Study of Urban Rail Transit Security System Based on Face Recognition Technology

Guo

Xiao

et al. 2022

In the modern world, it is difficult to prevent terrorism due to the relatively closed environment, dense personnel, large passenger flow, long line and wide coverage of urban rail transit. Identity recognition is a core element of security. The design and study of an urban rail transit security system based on face recognition technology are proposed in this paper. Through the study on the face recognition algorithm of intelligent security systems in urban rail transit, the related introduction of face recognition technology is done. The analysis of the main mode of face recognition is carried out utilizing the practical application design ideas. The results by experimental analysis show that if FAR is set to a very low range (such as 0.1% or even 0.01%) meanwhile FRR can reach a very low level (such as less than 1%). Such a system has practical value and otherwise, it may face a large number of passenger affairs and complaints to be handled. When FAR is set to 0.1% and N is 1.6 million, FRR can reach 2.1%. However, according to the test, when the picture quality deteriorates (during image captured by a webcam), the FRR will increase by 2 to 3 times. If a Webcam is used for recognition in Mugshot, the lowest FRR of the three top algorithms is only 5.21%.Povzetek: Tehnologija prepoznavanja obrazov je uporabljena za nadzor osumljencev -teroristov na vlakih.

“…Lei, Y. will first introduce big data and artificial intelligence, after analyzing the application of artificial intelligence in computer networks in the current era of big data, in this way, it can be used as a reference for relevant people to communicate [13]. Xia, M. Can use the effective application of artificial intelligence virus detection and killing technology in enterprise information security situation awareness system can realize the effective identification and timely detection and killing of virus, and reduce the damage caused by virus to computer system [14][15][16][17][18].Because these studies have large loopholes, or the detection is not comprehensive enough, this paper proposes a method based on artificial intelligence on the basis of existing studies [19][20][21][22][23][24][25][26][27]. The design and deployment of the system, effective detection, threat perception, determination and threat risk tracking of information security threats can realize the comprehensive improvement of enterprises and their ability to detect security threats and security attacks [28][29][30][31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Big Data Intelligent Collection and Network Failure Analysis Based on Artificial Intelligence

Ding

Baqasah

et al. 2022

To study smart data collection and network error analysis, this paper proposes intelligent data collection and network error analysis based on artificial intelligence. It examines the establishment of an enterprise-level information security situation awareness system and proposes specific information security models, architectures, and implementation methods. By designing and deploying the system, businesses can effectively detect information security threats, receive threats, filter risks, control threats, and comprehensively improve businesses' ability to detect security threats and security attacks. Test results: Through this platform, it is possible to manually intervene in the unknown threat of large data analysis in the system, and professionals can perform a detailed analysis to determine the means, goals and objectives of the attack and restore the complete picture. Intruder through artificial intelligence combined with big data knowledge and intrusion. Dimensional human characteristics. Including similar Trojans and malicious servers with different application forms, encodings, and attack principles, they "track" intruders by their general characteristics, constantly detect unknown threats, and ultimately ensure the accuracy of unknown threat detection, creating a local threat intelligence analytics platform. Practice has shown that the intelligent acquisition of large data by artificial intelligence can effectively analyze network failures.Povzetek: S pomočjo umetne inteligence je narejena analiza napak v omrežjih in zbiranje podatkov.