@article{1813,
  author = {Mario Barbareschi, Alessandra De Benedictis},
  title = {Providing Mobile Traffic Analysis As-a-service: Design of a Service-based Infrastructure to Offer High-accuracy Traffic Classifiers Based on Hardware Accelerators},
  journal = {Journal of Digital Information Management},
  year = {2015},
  volume = {13},
  number = {4},
  doi = {},
  url = {http://dline.info/fpaper/jdim/v13i4/v13i4_6.pdf},
  abstract = {Mobile traffic is significantly growing, thanks
to the increased access capacity provided by 3G and 4G
technologies and to the rising computing power of the
latest smart devices. Due to the widespread diffusion of
mobile applications that require and process sensitive
customers data, mobile traffic is more and more subject
to security attacks. Recently, traffic analysis techniques
are being successfully adopted to characterize, from a
security point of view, applications and networks behaviour
in order to detect and avoid intrusion attempts, malware
injections and data theft. When applied to the mobile
domain, such techniques have to cope on the one hand
with the performance constraints posed by the limited
devices resources and, on the other hand, with the need
for accurate and up-to-date traffic models, resulting from
a continuous processing of meaningful traffic data and
threat-related information.

To face these issues, we propose a two-tier service-based
traffic analysis infrastructure: at the mobile network layer,
mobile devices run a high-accuracy hardware traffic
analyser, which allows for the processing of large data
sets in an energy-efficient way; at the service layer, a
high-scale traffic analyser takes advantage of the
correlation of traffic data involving heterogeneous and
geographically distributed sources, in order to produce
enhanced traffic models, which can be distributed to the
devices in an on-demand fashion, according to the as-a-
Service approach.

To show the feasibility of our proposal, we provide a case
study based on the implementation of a decision treebased
traffic analyser on a Xilinx Zynq 7000 architecture,and present an overview of the service layer, by referring
to a cloud infrastructure for its implementation.},
}