  With the pervasive network based services in smart homes, traditional network
management cannot guarantee end-user quality-of-experience (QoE) for all
applications. End-user QoE must be supported by efficient network
quality-of-service (QoS) measurement and efficient network resource allocation.
With the software-defined network technology, the core network may be
controlled more efficiently by a network service provider. However, end-to-end
network QoS can hardly be improved the managing the core network only. In this
paper, we propose an encrypted packet classification scheme for smart home
gateways to improve end-to-end QoS measurement from the network operator side.
Furthermore, other services such as statistical data collecting, billing to
service providers, etc., can be provided without compromising end-user privacy
nor security of a network. The proposed encrypted packet classification scheme
has a two-level hierarchical structure. One is the service level, which is
based on applications that have the same network QoS requirements. A faster
classification scheme based on deep learning is proposed to achieve real-time
classification with high accuracy. The other one is the application level,
which is based on fine-grained applications. A non-real-time classifier can be
applied to provide high accuracy. Evaluation is conducted on both level
classifiers to demonstrate the efficiency and accuracy of the two types of
classifiers.
