DynNet: A Lightweight Distributed Framework for Topology Obfuscation in Dynamic Networks

Network Topology Obfuscation (NTO) has emerged as a promising scheme to conceal the physical layout of networks, thereby preventing adversaries from targeting critical nodes or links. By constructing deceptive virtual topologies, NTO schemes can obscure essential components and deploy honeypots to mislead and detect malicious behavior. However, existing NTO methods suffer from two major limitations. First, their high computational overhead makes them impractical for dynamic environments such as vehicular networks, where rapid topology adaptation is essential. Second, most current solutions depend on centralized controllers, typically within Software-defined Networking (SDN) architectures, which limits their applicability in decentralized or ad hoc settings. To address these challenges, we propose DynNet, a distributed and probabilistic NTO framework that adapts to dynamic topologies. Each node in DynNet independently handles probing packets (e.g., packets with low time-to-live (TTL) values) by probabilistically choosing to respond truthfully, return deceptive data, or remain silent. This probabilistic framework allows nodes to rapidly update their behavior in response to topology changes with minimal overhead. To ensure consistency, we propose a bucket-based probabilistic mapping to ensure that packets from the same flow consistently trigger the same response. Our evaluation shows that DynNet maintains effective topology concealment in highly dynamic scenarios while significantly reducing computational and communication overhead. The results demonstrate its suitability for deployment in distributed, rapidly changing network environments.