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http://hdl.handle.net/10609/117789
Title: Security analytics with Elastic
Author: Vázquez Pesado, David
Director: García Font, Víctor
Tutor: Canto Rodrigo, Pau del
Keywords: Elastic
SIEM
monitoring
machine learning
Issue Date: 2-Jun-2020
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: This project was created to cover the growing need in companies for the implementation of control and security monitoring systems, which allow for the improvement of asset and infrastructure security in business environments. The project is based entirely on the Elastic Suite, a set of tools that allow a simple analysis of existing information sources in business environments, from which security information is extracted, such as DNS, Netflow, System Events, Audit, etc. The objective is to use the tools provided by Elastic for the analysis of business data, to later integrate them with Elastic SIEM and, by means of Machine Learning techniques, achieve improved prevention and detection of security threats. This is really useful to visualize in real time the state of the assets and the infrastructure, which allows to keep a total control of what is happening in every moment. This entails, if necessary, to prompt action for the prevention or mitigation of a security threat. The final product becomes a comprehensive security system, which allows not only to control possible security threats, but also provides useful information through continuous monitoring of assets, being able to know the current status of the infrastructure in real time.
Language: Spanish
URI: http://hdl.handle.net/10609/117789
Appears in Collections:Bachelor thesis, research projects, etc.

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