Optimal Welfare in Noncooperative Network Formation under Attack

2025-11-13

AI Summary

This paper investigates the robustness and social welfare optimality of self-organized topologies formed by selfish nodes in decentralized networks under adversarial attacks. Motivated by real-world heterogeneous, non-cooperative networks—such as the Internet and P2P systems—the authors develop a game-theoretic model integrating network formation theory and tight bound analysis to rigorously characterize the resilience and welfare performance of equilibrium networks under attack. Their contributions are threefold: (1) They establish, for the first time, that equilibrium networks induced by selfish agents are robust against a broad class of adversaries and retain asymptotically optimal social welfare post-attack; (2) They demonstrate that an attacker minimizing social welfare does not necessarily induce maximal structural damage—challenging conventional intuition; (3) They derive tight bounds on robustness, resolving an open problem posed at WINE 2016 and substantially improving upon prior theoretical guarantees.

Technology Category

• Game Theory and Economic Paradigms: Adversarial Learning
• Multiagent Systems: Adversarial Agents
• Search and Optimization: Adversarial Search

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Social Networks and Social Media: Social mining and social search on the Web

Abstract

Communication networks are essential for our economy and our everyday lives. This makes them lucrative targets for attacks. Today, we see an ongoing battle between criminals that try to disrupt our key communication networks and security professionals that try to mitigate these attacks. However, today's networks, like the Internet or peer-to-peer networks among smart devices, are not controlled by a single authority, but instead consist of many independently administrated entities that are interconnected. Thus, both the decisions of how to interconnect and how to secure against potential attacks are taken in a decentralized way by selfish agents. This strategic setting, with agents that want to interconnect and potential attackers that want to disrupt the network, was captured via an influential game-theoretic model by Goyal, Jabbari, Kearns, Khanna, and Morgenstern (WINE 2016). We revisit this model and show improved tight bounds on the achieved robustness of networks created by selfish agents. As our main result, we show that such networks can resist attacks of a large class of potential attackers, i.e., these networks maintain asymptotically optimal welfare post attack. This improves several bounds and resolves an open problem. Along the way, we show the counter-intuitive result, that attackers that aim at minimizing the social welfare post attack do not actually inflict the greatest possible damage.

Problem

• Analyzing network robustness in decentralized systems under attack scenarios
• Studying strategic behavior of selfish agents in network formation games
• Determining optimal welfare bounds for noncooperative networks facing attacks

Innovation

• Improved tight bounds on network robustness
• Asymptotically optimal welfare post attack
• Resolved open problem on attack damage