Visible to the public Biblio

Filters: Keyword is SDN controller security  [Clear All Filters]
2020-03-18
Boukria, Sarra, Guerroumi, Mohamed, Romdhani, Imed.  2019.  BCFR: Blockchain-based Controller Against False Flow Rule Injection in SDN. 2019 IEEE Symposium on Computers and Communications (ISCC). :1034–1039.

Software Defined Networking (SDN) technology increases the evolution of Internet and network development. SDN, with its logical centralization of controllers and global network overview changes the network's characteristics, on term of flexibility, availability and programmability. However, this development increased the network communication security challenges. To enhance the SDN security, we propose the BCFR solution to avoid false flow rules injection in SDN data layer devices. In this solution, we use the blockchain technology to provide the controller authentication and the integrity of the traffic flow circulated between the controller and the other network elements. This work is implemented using OpenStack platform and Onos controller. The evaluation results show the effectiveness of our proposal.

2019-06-28
Röpke, Christian, Holz, Thosten.  2018.  Preventing Malicious SDN Applications From Hiding Adverse Network Manipulations. Proceedings of the 2018 Workshop on Security in Softwarized Networks: Prospects and Challenges. :40-45.

In Software-Defined Networks (SDN), so called SDN controllers are responsible for managing the network devices building such a network. Once such a core component of the network has been infected with malicious software (e.g., by a malicious SDN application), an attacker typically has a strong interest in remaining undetected while compromising other devices in the network. Thus, hiding a malicious network state and corresponding network manipulations are important objectives for an adversary. To achieve this, rootkit techniques can be applied in order to manipulate the SDN controller's view of a network. As a consequence, monitoring capabilities of SDN controllers as well as SDN applications with a security focus can be fooled by hiding adverse network manipulations. To tackle this problem, we propose a novel approach capable of detecting and preventing hidden network manipulations before they can attack a network. In particular, our method is able to drop adverse network manipulations before they are applied on a network. We achieve this by comparing the actual network state, which includes both malicious and benign configurations, with the network state which is provided by a potentially compromised SDN controller. In case of an attack, the result of this comparison reveals network manipulations which are adversely removed from an SDN controller's view of a network. To demonstrate the capabilities of this approach, we implement a prototype and evaluate effectiveness as well as efficiency. The evaluation results indicate scalability and high performance of our system, while being able to protect major SDN controller platforms.