GTAINov 13, 2025

Optimal Welfare in Noncooperative Network Formation under Attack

arXiv:2511.10845v1h-index: 13
Originality Incremental advance
AI Analysis

This addresses the problem of securing decentralized networks like the Internet against attacks, with incremental improvements to existing theoretical bounds.

The paper revisits a game-theoretic model of decentralized network formation under attack, showing that networks created by selfish agents can resist a large class of attackers and maintain asymptotically optimal welfare post-attack, improving several bounds and resolving an open problem.

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.

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