Projecte llegit
Títol: Big Data for Digital Forensics
Estudiants que han llegit aquest projecte:
CUZCANO COSSI, ALFREDO DANIEL (data lectura: 22-02-2018)- Cerca aquest projecte a Bibliotècnica
CUZCANO COSSI, ALFREDO DANIEL (data lectura: 22-02-2018)Director/a: HERNÁNDEZ SERRANO, JUAN
Departament: ENTEL
Títol: Big Data for Digital Forensics
Data inici oferta: 27-06-2017 Data finalització oferta: 27-02-2018
Estudis d'assignació del projecte:
- MU MASTEAM 2015
| Tipus: Individual | |
| Lloc de realització: EETAC | |
| Paraules clau: | |
| Big Data MapReduce SLIPS IDS IPS Digital Network Forensics | |
| Descripció del contingut i pla d'activitats: | |
| Overview (resum en anglès): | |
| Digital Forensics and its sub-branch Network Forensics are important and relevant topics which have gained further attention with the DDoS attacks delivered by botnets.
This work focuses on a novel IDS solution called: SLIPS. This is a free software that uses Machine Learning to detect malicious behaviors in a network with the use of Markov Chain based detection and previously trained models. A major limitation of SLIPS lies on its performance, and this work also touches on the topic of Big Data, and more specifically MapReduce, in order to aid SLIPS with a better resource utilization. With the redistribution of SLIPS tasks across workers, adding a pre-processing of data, the proposed solution using MapReduce presented performance improvements of up to 433 times with the datasets tested. |
|