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Projecte llegit

Títol: Big Data for Digital Forensics

Estudiants que han llegit aquest projecte:


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.

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