BIG-DAMA
BIG DATA ANALYTICS FOR NETWORK TRAFFIC MONITORING AND ANALYSIS

TeamNEWS

What IS IT ABOUT?

The complexity of the Internet has dramatically increased in the last few years, making it more important and challenging to design scalable Network Traffic Monitoring and Analysis applications and tools. The Big-DAMA project is conceiving novel scalable techniques and big-data frameworks capable to analyze both online network traffic data streams and offline massive traffic datasets. The team is exploring scalable online and offline data mining and machine learning-based techniques to monitor and characterize extremely large network traffic datasets.

Big Data Frameworks

We are using SQL and No-SQL frameworks for Big Data Analytics, including stream- and batch-based networking data processing

Machine Learning

We are building and testing novel Machine-Learning based approaches for large-scale network measurements analytics

Benchmarking

We are conceiving new benchmarks for comparing the performance of big data stream analysis and big network traffic monitoring solutions

Network Monitoring

We are developing novel techniques for large-scale network traffic monitoring and analysis, including network security and anomaly detection

PROJECT PARTNERS

The Big-DAMA project is funded by the Vienna Science and Technology Fund (WWTF) through project ICT15-129, “BigDAMA”, as well as by the other partner institutions (Austrian Institute of Technology, Technische Universität Wien and Politecnico di Torino).

              

Big-DAMA Use cases

Network Security and Anomaly Detection are our main applications.

Cyber attackers are continuously looking for new ways to access valuable information and disrupt services. Big-DAMA builds and evaluates specific Big Data Analytics frameworks and techniques for the purpose of detection and characterization of network attacks, considering both on-line data analysis, as well as the extraction of relevant patterns for data forensics analysis.

Despite the long literature and assorted list of proposed systems for performing automatic detection and diagnosis of anomalies in large-scale operational networks, Internet Service Providers (ISPs) are still looking for a Holy Grail which might effectively detect and diagnose the ever-growing number of network traffic anomalies they face in their daily business. Big-DAMA is conceiving a novel framework for detection and diagnosis of network traffic anomalies.

  • Detection of 0-day attacks, based on unsupervised analysis techniques

  • On-line detection and classification of network and service anomalies

  • Internet performance evaluation through large-scale measurements analysis

  • Using machine learning techniques to monitor networks from a user-centric perspective

Big-DAMA Team

The Big-DAMA team consists of a mix of young and confirmed researchers in the domain of Network Traffic Monitoring and Analysis

Pedro Casas

Principal Investigator
Team Leader
Pedro (PhD 2010) is Scientist at the Center for Digital Safety & Security of AIT. His research areas span the monitoring and analysis of network traffic, network security and anomaly detection, QoE assessment, as well as machine-learning based approaches for Networking.

Michael Seufert

Senior Investigator
Michi (PhD 2017) is Postdoctoral Fellow at the Center for Digital Safety & Security of AIT. He is expert in network measurements for user-centric networking, as well as on machine learning based approaches for data analysis.

Tanja Zseby

Co-Principal Investigator
Tanja (PhD 2005) is professor of communication networks at the faculty of electrical engineering and information technology at the Vienna University of Technology. She works in the areas of Network Security, Anomaly Detection and Smart Grid Security.

Marco Mellia

Senior Investigator
Marco (PhD 2001) is Associate Professor at the Electronics and Telecommunications department of Politecnico di Torino. He is a highly recognized researcher in the area of network traffic monitoring and analysis, and he is leading the BigData@Polito initiative on big data analysis.

Alessandro D’Alconzo

Senior Investigator (2016-2018)
Alessandro (PhD 2007) was Scientist at the Center for Digital Safety & Security of AIT. He is expert in the network measurements and traffic monitoring area. He was part of the core team till early 2018.

Félix Iglesias Vázquez

Senior Investigator
Félix (PhD 2012) is Postdoc University Assistant at the Vienna University of Technology. His research topics include machine learning, data analysis and network security.

Andrea Morichetta

Junior Investigator
Andrea is PhD candidate at the Electronics and Telecommunications department of Politecnico di Torino. He is working on network security and anomaly detection using clustering techniques and big data platforms.

Martino Trevisan

Junior Investigator
Martino is PhD candidate at Politecnico di Torino. He is expert on Big Data analytics for network monitoring and analysis.

Idilio Drago

Senior Investigator
Idilio (PhD 2013) is Assistant Professor at the Telecommunication Networks Group in Politecnico di Torino. His research interests include Internet measurements, Big Data analysis, and network security.

Stefano Traverso

Senior Investigator
Stefano (PhD 2012) is a researcher at the Telecommunication Networks Group in Politecnico di Torino. His research interests include Internet measurements and network security.

Daniel Ferreira

Junior Investigator
Daniel is PhD candidate at the faculty of electrical engineering and information technology at the Vienna University of Technology. He is working in the area of Network Security, Anomaly Detection and Big Data.

Juan Vanerio

Junior Investigator (2017)
Juan is Electrical Engineer and Master of Science at the Electrical Engineering institute of the University of Uruguay (UdelaR). He is working on machine learning tools and techniques for network security and anomaly detection using big data platforms.

Sarah Wassermann

Junior Investigator
Sarah is PhD candidate at INRIA Paris. She is working on machine learning modeling and prediction of Internet path dynamics. Her research areas span the monitoring and analysis of network traffic, distributed Internet measurements, as well as machine-learning.

Francesca Soro

Junior Investigator (2017)
Francesca is PhD candidate at Politecnico di Torino. She joined the Big-DAMA team to develop Big Data analytics and Machine Learning algorithms on the Big-DAMA platform.

Gonzalo Marín

Junior Investigator (2018)
Gonzalo is Master of Science candidate at UdelaR in Uruguay. He is working on deep learning approaches for cyber-security.

Pavol Mulinka

Junior Investigator (2018)
Pavol is PhD candidate at Czech Technical University in Prague. He is working on machine learning for the analysis of network measurements, with a particular focus on stream-based ML and clustering approaches.

Nikolas Wehner

Junior Investigator (2018)
Niko is research engineering at AIT Center for Technology Experience. In Big-DAMA, he focused on the development of ML models of user-centric networking.

Sami Ben Mariem

Junior Investigator (2018)
Sami is Master of Science candidate at the University of Liège. He is working on network measurements and clustering techniques to characterize distributed, P2P networks.

International Collaboration Institutions

Big-DAMA has active collaboration with 3 top-level international research institutions

Big-DAMA News

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Get in touch

We are always open to collaborations and joint activities, so just drop as a line in case you have some cool idea on Big-DAMA
Big-DAMA @AIT-DSS
Austrian Institute of Technology
Giefinggasse 4
1210 Vienna, Austria
Big-DAMA @TU Wien
Technische Universität Wien
Gusshausstraße 25 / E389
1040 Vienna, Austria
Big-DAMA @Polito
Politecnico di Torino
Corso Duca degli Abruzzi 24
10129 Turin, Italy