Events

Fast and Secure Routing Algorithms for Quantum Key Distribution Networks

  • 04

    Nov

    2022


Name of the Speaker: Krishnakumar G (EE19D410)
Name of the Guide: Dr. Abhishek Sinha, Dr. Venkatesh R
Link: https://meet.google.com/kue-rfkj-twh
Date/Time: 4th November 2022, 3.00pm

Abstract
In this talk, we consider the problem of secure packet routing at the maximum achievable rate in multi-hop Quantum Key Distribution (QKD) networks. We consider a practical setup where a QKD protocol randomly generates symmetric private key pairs for secure communication over each link in a network. The quantum key generation process is modeled using a stochastic counting process. Packets are first encrypted with the available quantum keys and then transmitted on a point-to-point basis over the links. A fundamental problem in this setting is the design of a secure and capacity-achieving routing policy that takes into account the time-varying availability of the encryption keys and finite link capacities. To address this problem, we propose a new secure throughput-optimal policy called Tandem Queue Decomposition (TQD). The TQD policy integrates the QKD process with the state-of-the-art Universal Max Weight routing policy. We show that the TQD policy solves the problem of secure and efficient packet routing for a broad class of traffic, including unicast, broadcast, multicast, and anycast. In brief, the TQD policy works by reducing the problem to the generalized network flow problem without the key availability constraints over a transformed network. The proposed policy is then proven stable by using a Lyapunov drift argument on the virtual queues.We note that the previous setting makes a rather strong assumption that the nodes can be fully trusted and the adversary can eavesdrop on the links only. To address this, in our ongoing work, we investigate the problem of secure throughput-optimal routing when the nodes can only be partially trusted with a pre-specified set of beliefs. Finally, we demonstrate the competitiveness of the TQD policy over other existing algorithms by numerically comparing them on a simulator built on top of the state-of-the-art OMNeT++ network simulator platform.