| Autor: |
Pandya Darshana, Jadeja Abhijeetsinh, Bhuptani Madhavi, Patel Vandana, Mehta Kinjal, Brahmbhatt Dipal |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
ITM Web of Conferences, Vol 65, p 03010 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2271-2097 |
| DOI: |
10.1051/itmconf/20246503010 |
| Popis: |
Securing data and the systems that manage or store it is known as cyber security. Cyber security violations are the most frequent crime performed by online attackers using one or more systems on one or more networks or systems. These cyberthreats can rapidly steal or lose data, as well as partially or totally shut down network systems. Because cyber-attacks are always developing, manually detecting them can be time-consuming and expensive. Consequently, they may be found and classified using machine learning approaches. This study focuses on a survey of the current algorithms for machine learning research in cyber security. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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