[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126042-en":3,"doc-seo-126042-105":31,"detail-sidebar-cat-0-en-105":93},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},126042,962084928904,"Asher","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Detection of Intrusions Based on Text Analysis and Machine Learning Methods in the Development of Information Systems","The paper analyzes core cyber security concepts and cyber security technologies, focusing on how artificial intelligence and machine learning can be applied to intrusion detection. It presents a host-based intrusion detection system built on intelligent text analysis, addressing data source difficulties and proposing a methodology for penetration testing. The study classifies techniques for detecting SQL injection, XSS, and path traversal attacks, and reports performance measurements for multiple ML models. Security recommendations are provided to IT administrators to help remediate detected vulnerabilities and strengthen baseline protection standards.","Detection of intrusions based on text analysis and machine learning methods in the development of information systems  \nSvitlana Popereshnyak1,*,†, Viktor Ovcharenko2,†, Yuriy Novikov2,† and Hennadii Hulak3, 4,†  \n1 National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 37 Prospect Beresteiskyi, 03056 Kyiv, Ukraine  \n2 Institute of Software Systems of the National Academy of Sciences of Ukraine, 40-5 Akademik Hlushkov ave., 03187 Kyiv, Ukraine  \n3 Borys Grinchenko Kyiv Metropolitan University, 18/2 Bulvarno-Kudriavska str., 04053 Kyiv, Ukraine  \n4 Institute of Mathematical Machines and Systems Problems of the National Academy of Sciences of Ukraine, 42 Ac. Glushkov ave., 03680 Kyiv, Ukraine  \nAbstract  \nThe paper analyzes the main concepts of cyber security, and cyber security technologies, investigates the features of the use of artificial intelligence in cyber security, analyzes the applied methods of machine learning, and presents the results of experimental research on the application of machine learning methods in cyber security. In this work, a host intrusion detection system based on the technique of intelligent text analysis will be implemented. The work describes the difficulties that data sources may face, for example, suffering from the method of complex functions. The paper proposes a classification of methods for detecting SQL injection, XSS, and path traversal attacks, and also provides performance measurements for the specified models. Penetration testing methodology was applied. This technique detects vulnerabilities related to the most popular attacks, such as SQL injection (SQLi), cross-site scripting (XSS), and sensitive data disclosure. Security solutions and suggestions were presented that IT administrators can use as a guide to protect the system against cybercriminal threats. Thus, the effectiveness of the proposed system was substantiated by fixing all detected vulnerabilities to achieve basic security standards. A host-based intrusion detection system (HIDS) was developed using text analysis techniques.  \nKeywords  \ncybersecurity, attack, smart home, Internet of Things, machine learning, host, cybercrime, risk, threat, software  \n1. Introduction  \nNowadays, information technologies are becoming an integral part ofall areas ofour lives in cyberspace. With the development of the Internet of Things (IoT) and the progress of the smart home, network security threats arise. Providing protection becomes important in light of the increasing number of connected devices that may be subject to cyberattacks. This highlights the need for research and implementation of cybersecurity measures in IoT networksand smart homes [1, 2] . These measures are critical to protecting the confidentiality, integrity, and security of data and to ensuring the safety of users and their property [3, 4] .  \nServices aimed at safeguarding networks, systems, and confidential data are referred to as cybersecurity measures,  \nwhich can be deployed through the utilization of [HTTP/](HTTP/)[HTTPS protocols](HTTPS protocols) [5].  \nCPITS-II 2024: Workshop on Cybersecurity Providing in Information and Telecommunication Systems II, October 26, 2024, Kyiv, Ukraine ∗ Corresponding author.  \n† These authors contributed equally.  \n [spopereshnyak@gmail.com](spopereshnyak@gmail.com) (S. Popereshnyak);  \n[viktor.ov4arenko@gmail.com](viktor.ov4arenko@gmail.com) (V. Ovcharenko);  \n[ynovikov@gmail.com](ynovikov@gmail.com) (Y. Novikov);  \n[hulak@kubg.edu.ua](hulak@kubg.edu.ua) (H. Hulak)  \nCEUR ~~  ~~[Workshop](Workshop ceur-ws.org)[ ceur-ws.org](Workshop ceur-ws.org)[ ](Workshop ceur-ws.org)[Proceedings](Proceedings ISSN 1613-0073)[ ISSN 1613-0073](Proceedings ISSN 1613-0073)   \nResearch shows that code injection on web pages is gradually increasing and accounts for up to 96.15% of all web attacks in recent years [6] . Additionally, according to WAAR, which focuses on the most common types of injection attacks [7], cross-s","cbCaihoTB2Pdnlxt","https://ap.wps.com/l/cbCaihoTB2Pdnlxt","pdf",2491405,6,1,9,"English","en",105,"# Introduction\n## Cybersecurity threats in IoT and smart homes\n## Web injection attacks and their prevalence\n## Need for malicious request detection\n# Proposed host intrusion detection approach\n## Dataset selection and preprocessing\n## Machine learning models used\n## Classification of detection methods and performance evaluation\n# Security implications","[{\"question\":\"What type of intrusion detection system does the paper propose?\",\"answer\":\"It implements a host-based intrusion detection system (HIDS) using techniques of intelligent text analysis.\"},{\"question\":\"Which attacks are targeted for detection and classification?\",\"answer\":\"The paper focuses on SQL injection, cross-site scripting (XSS), and path traversal attacks.\"},{\"question\":\"How is the proposed system validated in the study?\",\"answer\":\"A penetration testing methodology is applied, and performance measurements are provided for several machine learning models to substantiate effectiveness.\"}]","Detection of Intrusions Based on Text Analysis and Machine Learning Methods in the Development of Information Systems | 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type of intrusion detection system does the paper propose?","Question",{"text":77,"@type":78},"It implements a host-based intrusion detection system (HIDS) using techniques of intelligent text analysis.","Answer",{"name":80,"@type":75,"acceptedAnswer":81},"Which attacks are targeted for detection and classification?",{"text":82,"@type":78},"The paper focuses on SQL injection, cross-site scripting (XSS), and path traversal attacks.",{"name":84,"@type":75,"acceptedAnswer":85},"How is the proposed system validated in the study?",{"text":86,"@type":78},"A penetration testing methodology is applied, and performance measurements are provided for several machine learning models to substantiate 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