Email spam detection using machine learning based text analysis
Phishing is the most common cyber security type of attack that threatens the integrity of all sorts of companies or individuals and is responsible for an incalculable amount of information leakage and economic loss. In this project, an exhaustive investigation has been done regarding the possibility...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/386385 |
| Acceso en línea: | https://hdl.handle.net/2117/386385 |
| Access Level: | acceso abierto |
| Palabra clave: | Computer security Machine learning phishing spam machine learning detection cyber security detección Seguretat informàtica Aprenentatge automàtic Àrees temàtiques de la UPC::Informàtica::Seguretat informàtica |
| Sumario: | Phishing is the most common cyber security type of attack that threatens the integrity of all sorts of companies or individuals and is responsible for an incalculable amount of information leakage and economic loss. In this project, an exhaustive investigation has been done regarding the possibility of using machine learning algorithms to analyze email text, in order to generate models capable of recognizing particular senders or in the contrary, recognize possible impersonation. Moreover, a testing-phased tool has been developed in order to fulfill that purpose, allowing users to authenticate with their gmail account and generate the models that will be used over the desired emails so possible phishing is marked as dangerous in their inboxes. |
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