Machine Learning in Information and Communications Technology: A Survey
The rapid growth of data and the increasing complexity of modern networks have driven the demand for intelligent solutions in the information and communications technology (ICT) domain. Machine learning (ML) has emerged as a powerful tool, enabling more adaptive, efficient, and scalable systems in t...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/16/1/8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832588329961390080 |
|---|---|
| author | Elias Dritsas Maria Trigka |
| author_facet | Elias Dritsas Maria Trigka |
| author_sort | Elias Dritsas |
| collection | DOAJ |
| description | The rapid growth of data and the increasing complexity of modern networks have driven the demand for intelligent solutions in the information and communications technology (ICT) domain. Machine learning (ML) has emerged as a powerful tool, enabling more adaptive, efficient, and scalable systems in this field. This article presents a comprehensive survey on the application of ML techniques in ICT, covering key areas such as network optimization, resource allocation, anomaly detection, and security. Specifically, we review the effectiveness of different ML models across ICT subdomains and assess how ML integration enhances crucial performance metrics, including operational efficiency, scalability, and security. Lastly, we highlight the challenges and future directions that are critical for the continued advancement of ML-driven innovations in ICT. |
| format | Article |
| id | doaj-art-2285e6348bb24fcd97fd46aff93a3178 |
| institution | Kabale University |
| issn | 2078-2489 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj-art-2285e6348bb24fcd97fd46aff93a31782025-01-24T13:35:07ZengMDPI AGInformation2078-24892024-12-01161810.3390/info16010008Machine Learning in Information and Communications Technology: A SurveyElias Dritsas0Maria Trigka1Industrial Systems Institute (ISI), Athena Research and Innovation Center, 26504 Patras, GreeceIndustrial Systems Institute (ISI), Athena Research and Innovation Center, 26504 Patras, GreeceThe rapid growth of data and the increasing complexity of modern networks have driven the demand for intelligent solutions in the information and communications technology (ICT) domain. Machine learning (ML) has emerged as a powerful tool, enabling more adaptive, efficient, and scalable systems in this field. This article presents a comprehensive survey on the application of ML techniques in ICT, covering key areas such as network optimization, resource allocation, anomaly detection, and security. Specifically, we review the effectiveness of different ML models across ICT subdomains and assess how ML integration enhances crucial performance metrics, including operational efficiency, scalability, and security. Lastly, we highlight the challenges and future directions that are critical for the continued advancement of ML-driven innovations in ICT.https://www.mdpi.com/2078-2489/16/1/8machine learninginformation and communications technologynetwork optimizationresource allocationanomaly detectionsecurity |
| spellingShingle | Elias Dritsas Maria Trigka Machine Learning in Information and Communications Technology: A Survey Information machine learning information and communications technology network optimization resource allocation anomaly detection security |
| title | Machine Learning in Information and Communications Technology: A Survey |
| title_full | Machine Learning in Information and Communications Technology: A Survey |
| title_fullStr | Machine Learning in Information and Communications Technology: A Survey |
| title_full_unstemmed | Machine Learning in Information and Communications Technology: A Survey |
| title_short | Machine Learning in Information and Communications Technology: A Survey |
| title_sort | machine learning in information and communications technology a survey |
| topic | machine learning information and communications technology network optimization resource allocation anomaly detection security |
| url | https://www.mdpi.com/2078-2489/16/1/8 |
| work_keys_str_mv | AT eliasdritsas machinelearningininformationandcommunicationstechnologyasurvey AT mariatrigka machinelearningininformationandcommunicationstechnologyasurvey |