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.

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Paper accepted in JNCA

Our paper:

“Multi-Classification Approaches for Classifying Mobile App Traffic”,

has been accepted within Elsevier Journal of Network and Computer Applications.

The present work proposes a classifier fusion framework for combinining state-of-the-art classifiers (with either hard- or soft-outputs) with the aim of improving performance in recognition of mobile app traffic.

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.

Paper accepted at ITC 29

Our paper:

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

has been accepted within 29th International Teletraffic Congress (ITC 29), 2017.

The present work analyzes whether Anonimity Tools can be discerned/classified by statistical (no packet inspection) classification techniques and, in affirmative case, to which degree.