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Security Analysis of SDN Applications for Big Data

: Ahmad, P.; Jacob, S.; Khondoker, R.


Khondoker, R.:
SDN and NFV Security. Security Analysis of Software-Defined Networking and Network Function Virtualization
Cham: Springer International Publishing, 2018 (Lecture Notes in Networks and Systems 30)
ISBN: 978-3-319-71760-9 (Print)
ISBN: 978-3-319-71761-6 (Online)
Aufsatz in Buch
Fraunhofer SIT ()

Big Data is a term that describes structured and unstructured large data sets. One of the frameworks to store , process and analyze this data is Apache Hadoop. Software Defined Networking (SDN) enhances the performance aspects of Hadoop by optimizing bandwidth utilization and improving network management. Security attacks on the SDN controller and switches can compromise the whole Hadoop system, that may cause loss or manipulation of valuable data. We selected the three most advanced approaches that focus on accelerating the data transfer between the cluster nodes. FlowComb , Pythia and Hadoop-Acceleration (Hadoop-A ) focus mainly on optimizing performance but do not consider any security aspect in their design. This motivates us to analyze the security aspects of these SDN applications. This paper focuses on the analysis of security features with STRIDE threat modeling technique. All approaches need improvements to gain security. We find that Pythia is natively the most secure approach while other approaches can be secured by deploying add-on security mechanisms.