G-Lox: Group-Adaptive, Privacy-Preserving Bridge Distribution with Two-Party Computation

2026-06-17

AI Summary

This work proposes the first group-level, state-aware adaptive bridge assignment mechanism that preserves both distributor blindness and user privacy. Leveraging a two-server architecture, the adaptive logic is shielded behind a privacy barrier, enabling private access to and updates of group states through dual-server DPF/FSS and two-party secure computation (implemented via the C++/EMP framework). The design supports private blocking reports, transmission-aware reassignment, and privacy-preserving group splitting, while ensuring that neither server learns group identifiers or assignment relationships. Experimental results demonstrate that with a state space of size 2¹⁶, each iteration incurs only a few kilobytes of communication overhead and approximately 0.25 seconds of client latency. Policy simulations further confirm its significant superiority over baseline schemes such as Lox and rBridge under group-specific blocking and Sybil attacks.

Abstract

We present G-Lox (group-adaptive Lox), a bridge-distribution system that preserves Lox-style distributor blindness while enabling hidden, stateful group-level adaptation. G-Lox places adaptive assignment logic behind a two-server privacy wall, so no single server learns group identifiers or group-to-bridge assignments. Private state access and state-dependent updates use two-server DPF/FSS protocols and secure two-party computation, supporting blockage reporting, transport-aware reassignment, and privacy-preserving group splitting. We evaluate G-Lox through system measurements and policy simulation. In our C++/EMP implementation over real TCP sockets, private state access has low client-visible overhead: across state sizes up to 2^16, communication remains in the low-KiB range per iteration. At M=1024, the client sends 1,968 bytes, receives 1,280 bytes, and completes an iteration in about 0.25 s. Simulations with group-specific blocking and Sybil enumeration show that G-Lox improves robustness over Lox- and rBridge-like baselines among systems that maintain broad issuance.

Problem

• bridge distribution
• privacy-preserving
• group-adaptive
• distributor blindness
• two-party computation

Innovation

• privacy-preserving
• two-party computation
• group-adaptive
• bridge distribution
• DPF/FSS