COMM

The application of machine learning models to network security and anomaly detection problems has largely increased in the last decade; however, there is still no clear best-practice or silver bullet approach to address these problems in a general ...

In the big-data era, the amount of traffic is rapidly increasing. Therefore, scaling methods are commonly used. For instance, an appliance composed of several instances (scaled-out method), and a load-balancer that distributes incoming traffic among ...

We present Net2Vec, a flexible high-performance platform that allows the execution of deep learning algorithms in the communication network. Net2Vec is able to capture data from the network at more than 60Gbps, transform it into meaningful tuples and ...

At the heart of many computer network planning, deployment, and operational tasks lie hard algorithmic problems. Accordingly, over the last decades, we have witnessed a continuous pursuit for ever more accurate and faster algorithms. We propose an ...

The analysis of flow traces can help to understand a network's usage patterns. We present a hierarchical clustering algorithm for network flow data that can summarize terabytes of IP traffic into a parsimonious tree model. The method automatically finds ...

We study the problem of predicting Internet path changes and path performance using traceroute measurements and machine learning models. Path changes are frequently linked to path inflation and performance degradation, therefore the relevance of the ...

Greater network flexibility through software defined networking and the growth of high bandwidth services are motivating faster service provisioning and capacity management in the optical layer. These functionalities require increased capacity along ...

The exploitation of cellular network data for studying human mobility has been a popular research topic in the last decade. Indeed, mobile terminals could be considered ubiquitous sensors that allow the observation of human movements on large scale ...

Encryption at the application layer is often promoted to protect privacy, i.e., to prevent someone in the network from observing users' communications. In this work we explore how to build a profile for a target user by observing only the names of the ...