@article{Yang2026, 
author = {Shu Yang and Zequn Zhang and Laizhong Cui},
title = {SAVNFV: Towards a Scalable and Accurate Inter-Domain Source Address Validation Platform with Network Functions Virtualization},
year = {2026},
journal = {Big Data Mining and Analytics},
volume = {9},
number = {2},
pages = {536-553},
keywords = {Source Address Validation (SAV), Network Functions Virtualization (NFV), Distributed Denial of Service (DDoS) attacks, multi-path routing},
url = {https://www.sciopen.com/article/10.26599/BDMA.2025.9020117},
doi = {10.26599/BDMA.2025.9020117},
abstract = {Nowadays, Source Address Validation (SAV) is increasingly important for defending Distributed Denial of Service (DDoS) attacks and other malicious activities. Existing ingress/edge filtering-based solutions, such as SAVI, filter spoofed source addresses using Access Control Lists (ACL) or unicast Reverse Path Forwarding (uRPF), but they only provide coarse-grained filtering. Source Address Validation in intra-domain and inter-domain NETworks (SAVNET) has recently attracted much attention in both industry and the Internet Engineering Task Force (IETF), deploying SAV inside Internet Service Provider (ISP) networks and generating SAV tables by binding source address prefixes with incoming interfaces. However, SAVNET requires upgrading almost all routers across networks, which is impractical—especially in inter-domain scenarios. Moreover, due to policy routing and load balancing, determining the exact incoming interface for each source prefix is challenging. In this paper, we propose SAVNFV, a Network Functions Virtualization (NFV) based platform that provides SAV capabilities by building a “clean” virtual overlay network. SAVNFV randomly generates paths for each flow through a centralized controller, making the SAV table easy to obtain. The paths are periodically refreshed, and packets are transmitted through multiple routes, making it nearly impossible for attackers to identify the correct incoming interface. We formulate the multi-path transmission as an optimization problem and prove it to be NP-Complete, then design approximation algorithms with theoretical guarantees. Comprehensive simulations show that SAVNFV blocks 94.6% more malicious traffic than traditional solutions while maintaining acceptable path stretch. We also implement the system using open-source routing software and build a real-world experimental platform to further validate our design.}
}