Paper Accepted at IEEE/ACM TMA’18

Our paper:

“Mobile Encrypted Traffic ClassificationUsing Deep Learning”,

has been accepted to the next IEEE/ACM Traffic Measurement and Analysis Conference.

The present work proposes the adoption of Deep Learning to classification of mobile traffic. Is that a piece of cake? No! domain expertise still counts 🙂

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Paper accepted in IEEE TDSC

Our paper:

“Anonymity Services Tor, I2P and JonDonym: Classifying in the Dark”,

has been accepted within IEEE Transactions on Dependable and Secure Computing.

The present work delves into classification of encrypted anonymity services. Could the present tools be identified only by looking at some (suitably-designed) statistical features? The response is affirmative, in most cases.

Paper accepted at Globecom 2017

Our paper:

“Traffic Classification of Mobile Apps through Multi-classification”,

has been accepted within IEEE Global Communications Conference (GLOBECOM), 2017.

The present work proposes a classifier fusion framework for combinining state-of-the-art classifiers with the aim of improving performance in recognition of mobile app traffic.