| KEYWORD |
Bigdata and extreme scale analysis with CPU intensive applications acceleration on FPGA/GPU architecture in cybersecurity techniques.
Thesis in external company
keywords BIG DATA, CYBERSECURITY, MACHINE LEARNING
Reference persons MARCO MELLIA
External reference persons The thesis will be developed in collaboration with Istituto Superiore Mario Boella - ISMB - under the supervision of Oliver Terzo and Alberto lato
Research Groups SmartData@PoliTO, Telecommunication Networks Group
Thesis type SOFTWARE DEVELOPMENT
Description Next generation tools, as well as new programming and computational methods are paramount for the evolution of Information and Communication Technologies (ICT) domain. The growing interest on methods for processing large amount of heterogeneous data and new cognitive systems creates new challenges and opportunities.
In the ICT domain, a major effort will be spent on improving and applying machine learning techniques: for example in extreme scale data analysis in cybersecurity domain.
This thesis will investigate on a computational framework (i.e., software stack, hardware system, programming tools, etc.) for implementing a machine learning (ML), Artifical Intelligence Model (IA), running on modern high performance heterogenous architectures. The goal will be to develop a DL/ML solution for accelerating analysis in CPU intensive application scenarios.
Required skills Good programming skills, knowledge of machine learning
Deadline 07/09/2019
PROPONI LA TUA CANDIDATURA