The automatic classification of applications and services is an invaluable feature for new
generation mobile networks. Here, we propose and validate algorithms to perform this task …

Among the smart capabilities promised by the next generation cellular networks (5G and
beyond), it is fundamental that potential network anomalies are detected and timely treated …

Traffic Classification (TC) systems allow inferring the application that is generating the traffic
being analyzed. State-of-the-art TC algorithms are based on Deep Learning (DL) and have …

Passive cyber-security attacks do not require any modification of the data stream generated
by the victim, nor the creation of a false statement; in particular, those attacks based on …

Traffic recognition is commonly done using deep packet inspection or packet‐based
approaches. However, these methods require the listening device to be part of the network …

Abstract Mobile Traffic Classification (TC) has become nowadays the enabler for valuable
profiling information, other than being the workhorse for service differentiation or blocking …

The vast majority of Internet traffic is now end-to-end encrypted, and while encryption
provides user privacy and security, it has made network surveillance an impossible task …

Deep learning has proven to be promising for traffic fingerprinting that explores features of
packet timing and sizes. Although well-known for automatic feature extraction, it is faced with …

In complex networks systems like mobile edge infrastructures, real-time traffic classification
according to application types is an enabling technique for network resource optimization …

The massive adoption of hand-held devices has led to the explosion of mobile traffic
volumes traversing home and enterprise networks, as well as the Internet. Traffic …