MLSNet: A Policy Complying Multilevel Security Framework for Software Defined Networking

Stefan Achleitner, Quinn Burke, Patrick McDaniel, Trent Jaeger, Thomas La Porta, Srikanth Krishnamurthy

Research output: Contribution to journalArticlepeer-review

Abstract

Ensuring that information flowing through a network is secure from manipulation and eavesdropping by unauthorized parties is an important task for network administrators. Many cyber attacks rely on a lack of network-level information flow controls to successfully compromise a victim network. Once an adversary exploits an initial entry point, they can eavesdrop and move laterally within the network (e.g., scan and penetrate internal nodes) to further their malicious goals. In this paper, we propose a novel multilevel security (MLS) framework to enforce a secure inter-node information flow policy within the network and therein vastly reduce the attack surface available to an adversary who has penetrated it. In contrast to prior work on multilevel security in computer networks which relied on enforcing the policy at network endpoints, we leverage the centralization of software-defined networks (SDNs) by moving the task to the controller and providing this service transparently to all network nodes. Our framework, MLSNet, formalizes the generation of a policy compliant network configuration (i.e., set of flow rules on the SDN switches) as network optimization problems, with the objectives of (1) maximizing the number of flows satisfying all security constraints and (2) minimizing the security cost of routing any remaining flows to guarantee availability. We demonstrate that MLSNet can securely and efficiently route flows that satisfy the security constraints and route the remaining flows with a minimal security cost (e.g., route >85% of flows, where the heuristic achieves 89% and 87% of the optimal solutions for the optimization problems).

Original languageEnglish (US)
JournalIEEE Transactions on Network and Service Management
DOIs
StateAccepted/In press - 2020

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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