Dynamic Network Control for Confidential Multi-hop Communications

TL;DR

This paper presents a dynamic control algorithm for confidential multihop networks that optimizes resource allocation, routing, and secrecy encoding to maximize utility while ensuring message confidentiality from intermediate nodes.

Contribution

It introduces a provably optimal, adaptive control scheme integrating flow control, routing, and secrecy encoding, considering finite packet encoding and practical implementation challenges.

Findings

The scheme approaches optimal secrecy rates with increasing block size.

Dynamic policies effectively adapt to channel and queue states.

Numerical results demonstrate robustness under various network conditions.

Abstract

We consider the problem of resource allocation and control of multihop networks in which multiple source-destination pairs communicate confidential messages, to be kept confidential from the intermediate nodes. We pose the problem as that of network utility maximization, into which confidentiality is incorporated as an additional quality of service constraint. We develop a simple, and yet provably optimal dynamic control algorithm that combines flow control, routing and end-to-end secrecy-encoding. In order to achieve confidentiality, our scheme exploits multipath diversity and temporal diversity due to channel variability. Our end-to-end dynamic encoding scheme encodes confidential messages across multiple packets, to be combined at the ultimate destination for recovery. We first develop an optimal dynamic policy for the case in which the number of blocks across which secrecy encoding is performed is asymptotically large. Next, we consider encoding across a finite number of packets, which eliminates the possibility of achieving perfect secrecy. For this case, we develop a dynamic policy to choose the encoding rates for each message, based on the instantaneous channel state information, queue states and secrecy outage requirements. By numerical analysis, we observe that the proposed scheme approaches the optimal rates asymptotically with increasing block size. Finally, we address the consequences of practical implementation issues such as infrequent queue updates and de-centralized scheduling. We demonstrate the efficacy of our policies by numerical studies under various network conditions.