Title
Generation of SDN policies for protecting android environments based on automata learning.
Abstract
Software-defined networking offers new opportunities for protecting end users and their applications. In that context, dedicated chains can be built to combine different security functions, such as firewalls, intrusion detection systems and services for preventing data leakage. To configure these security chains, it is important to have an adequate model of the patterns that end user applications exhibit when accessing the network. We propose an automated strategy for learning the networking behavior of end applications using algorithms for generating finite state models. These models can be exploited for inferring SDN policies ensuring that applications respect the observed behavior: such policies can be formally verified and deployed on SDN infrastructures in a dynamic and flexible manner. Our solution is prototypically implemented as a collection of Python scripts that extend our Synaptic verification package. The performance of our strategy is evaluated through extensive experimentations and is compared to the Synoptic and Invarimint automata learning algorithms.
Year
Venue
Field
2018
IEEE IFIP Network Operations and Management Symposium
Android (operating system),Learning automata,End user,Computer science,Intrusion detection system,Automata learning,Python (programming language),Humanoid robot,Scripting language,Distributed computing
DocType
ISSN
Citations 
Conference
1542-1201
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Nicolas Schnepf112.04
Remi Badonnel215422.43
Abdelkader Lahmadi39018.46
Stephan Merz474159.44