The SmartData@PoliTO center focuses on Big Data technologies, Data Science and Machine Learning approaches.
We blend interdisciplinary people and competences from different domains to provide cross-domain solutions to the widest spectrum of knowledge discovery challenges, by leveraging advanced expertise in data science, from data management, to data modeling, analytics, and engineering.
We are a well-recognized center where experts in methodologies and domain experts from various disciplines work in a single space, facing both theoretical problems and helping companies toward applications.

SmartTalks

Deep Learning and Layer-wise Relevance Propagation for Backbone Identification in Discrete Fracture Networks

Presenters: Antonio Mastropietro & Francesco Della SantaMonday, May 8th, 2020 16:30Location: Microsoft Teams – click here to join Antonio Mastropietro: Layer-Wise Relevance Propagation for Deep Learning Surrogate Model investigation Nowadays engineering applications involve the use of computationally heavy simulations to solve dynamical systems that model a given physical phenomenon. By training a surrogate model of […]

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SmartTalks

Sensing the noise: unveiling communities in darknet traffic.

Presenter: Francesca SoroMonday, May 25th, 2020 16:30Location: Microsoft Teams – click here to join Darknets are ranges of IP addresses advertised without answering any traffic. Darknets help to uncover interesting network events, such as misconfigurations and network scans. Interpreting darknet traffic helps against cyber-attacks — e.g., malware often reaches darknets when scanning the Internet for […]

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News

AI4NET - Huawei Research Chair AI for Anomalous Traffic Analysis

On Tuesday the 19 of May, we’ll have the (virtual) kickoff meeting of the AI4NET project – the Huawei Research Chair on AI for Anomalous Traffic analysis.It marks the start of an exiting collaboration between SmartData@PoliTO and Huawei Datacom FRC lab in Paris on topics related to network data analysis for anomaly detection using novel […]

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Open Datasets & Libraries

Domains per web users

This page collects the open datasets and codeused in the papers: Azadeh Faroughi, Andrea Morichetta, Luca Vassio, Flavio Figueiredo, Marco Mellia and Reza Javidan, Towards Website Domain Name Classification Using Graph Based Semi-supervised Learning, Currently Under Review, 2020 The partially labeled dataset with the visited domains and their category and can be downloaded from here […]

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