Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning
The automated system for detecting cyber bot attacks in 5G networks relies on cloud servers to store data, facilitating the global access necessary for online transactions and services, but points to the rise of cybercrime with information security flaws and human stealth Attackers known as "...
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| Format: | Article |
| Language: | English English |
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INTI International University
2024
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| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/2068/ http://eprints.intimal.edu.my/2068/2/609 http://eprints.intimal.edu.my/2068/3/joit2024_31b.pdf |
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| author | Thrupthi, C.P. Chitra, K. Harilakshmi, V.M. |
| author_facet | Thrupthi, C.P. Chitra, K. Harilakshmi, V.M. |
| author_sort | Thrupthi, C.P. |
| building | INTI Institutional Repository |
| collection | Online Access |
| description | The automated system for detecting cyber bot attacks in 5G networks relies on cloud servers
to store data, facilitating the global access necessary for online transactions and services, but
points to the rise of cybercrime with information security flaws and human stealth Attackers
known as "Botmasters" spread Trojan malware to grow bots on the network causing DDOS
attacks. Botnets are compromised computer networks controlled by attackers that are visible
for this reason. Machine learning algorithms have been proposed to identify bot networks with
a focus on extracting features from high-dimensional datasets. However, the literature pays
little attention to selection methods, which are crucial for developing effective machinelearning
models. |
| first_indexed | 2025-11-14T11:58:40Z |
| format | Article |
| id | intimal-2068 |
| institution | INTI International University |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T11:58:40Z |
| publishDate | 2024 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-20682025-07-11T03:12:54Z http://eprints.intimal.edu.my/2068/ Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning Thrupthi, C.P. Chitra, K. Harilakshmi, V.M. QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TJ Mechanical engineering and machinery The automated system for detecting cyber bot attacks in 5G networks relies on cloud servers to store data, facilitating the global access necessary for online transactions and services, but points to the rise of cybercrime with information security flaws and human stealth Attackers known as "Botmasters" spread Trojan malware to grow bots on the network causing DDOS attacks. Botnets are compromised computer networks controlled by attackers that are visible for this reason. Machine learning algorithms have been proposed to identify bot networks with a focus on extracting features from high-dimensional datasets. However, the literature pays little attention to selection methods, which are crucial for developing effective machinelearning models. INTI International University 2024-11 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2068/2/609 text en cc_by_4 http://eprints.intimal.edu.my/2068/3/joit2024_31b.pdf Thrupthi, C.P. and Chitra, K. and Harilakshmi, V.M. (2024) Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning. Journal of Innovation and Technology, 2024 (31). pp. 1-6. ISSN 2805-5179 http://ipublishing.intimal.edu.my/joint.html |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TJ Mechanical engineering and machinery Thrupthi, C.P. Chitra, K. Harilakshmi, V.M. Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning |
| title | Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning |
| title_full | Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning |
| title_fullStr | Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning |
| title_full_unstemmed | Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning |
| title_short | Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning |
| title_sort | automated system for detecting cyber bot attacks in 5g networks using machine learning |
| topic | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TJ Mechanical engineering and machinery |
| url | http://eprints.intimal.edu.my/2068/ http://eprints.intimal.edu.my/2068/ http://eprints.intimal.edu.my/2068/2/609 http://eprints.intimal.edu.my/2068/3/joit2024_31b.pdf |