The prediction of information security level in the enterprise
| dc.contributor.author | Khashimova D. | |
| dc.date.accessioned | 2025-08-11T04:41:33Z | |
| dc.date.available | 2025-08-11T04:41:33Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | This thesis presents the results of an analysis to identify groups of threats specific to the infrastructure and systems of an enterprise, which is one of the main stages in forecasting. The state of information security at enterprises is considered, the qualifications of security threats and classification methods based on attack methods and the impact of threats are analyzed. Threats for the safe use of the Internet and hacking sites, data theft, phishing attacks and social engineering are assessed; Identification of cloud computing security threats that are encountered in the enterprise's Internet networks. The advantages and disadvantages of Web Application Firewall, which are used to protect attacks, such as DDoS attacks, SQL injections, cross-site scripting, and others, are studied. Works for providing protection using artificial intelligence and machine learning are presented. | |
| dc.identifier.citation | Khashimova D / The prediction of information security level in the enterprise / 6M070400 - Department of Mathematics / 2020 | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1852 | |
| dc.language.iso | en | |
| dc.publisher | faculty of engineering and natural sciences | |
| dc.subject | Machine learning | |
| dc.subject | AdaBoost | |
| dc.subject | Protection from DDoS-attacks | |
| dc.title | The prediction of information security level in the enterprise | |
| dc.type | Thesis |