PIPE: Identity-Aware Privacy-Enhanced Source and Path Verification for Strengthened Network Accountability
Jianfeng Guan, Kexian Liu, Su Fen Yao, HU Xiao-long, Ye Qin, Jianli Liu, Songtao Fu, Xiangyu Gao, Ke Xu · 2025
Network-layer security threats have become increasingly sophisticated, exposing significant vulnerabilities in the current Internet architecture. Despite various proposed solutions, the field faces fundamental challenges in balancing user privacy with network security and achieving practical deployment. This paper presents a novel approach called PIPE (Privacy-preserving Identity and Path Enhancement), which leverages a distributed infrastructure of Key Distribution Servers (KDS) to integrate Decentralized Identity (DID) with source and path verification. Our solution binds user identity, address, path, and data while maintaining privacy through encryption and per-hop address transformation. By embedding DID information in address and implementing encrypted path verification, we achieve enhanced network accountability without compromising privacy. Experimental results demonstrate PIPE’s practicality and advantages over existing approaches in terms of deployment flexibility and security guarantees. Our work contributes to the evolution of secure network architectures by balancing accountability requirements with privacy protection while ensuring practical deployability.