ITCRMay 14, 2013

Using Feedback for Secrecy over Graphs

arXiv:1305.3051v26 citations
Originality Incremental advance
AI Analysis

This addresses secure communication in networked systems, but appears incremental as it builds on existing graph and coding theory frameworks.

The paper tackles secure message multicasting over graphs with passive adversaries, showing that feedback via cycles or undirected edges enables higher rates than in directed acyclic graphs with the same mincut, demonstrated through code constructions for canonical combination networks.

We study the problem of secure message multicasting over graphs in the presence of a passive (node) adversary who tries to eavesdrop in the network. We show that use of feedback, facilitated through the existence of cycles or undirected edges, enables higher rates than possible in directed acyclic graphs of the same mincut. We demonstrate this using code constructions for canonical combination networks (CCNs). We also provide general outer bounds as well as schemes for node adversaries over CCNs.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes