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This paper introduces BGPay, a market-based mechanism designed to address the incentive misalignment in BGP hijack filtering by allowing prefix owners to post bounties for filtering invalid announcements. By leveraging public route collectors as an independent root of trust, BGPay transforms the filtering process into a private transaction, ensuring that filterers are compensated based on evidence rather than the prefix owner's subjective judgment. Analysis of 1,000 real hijack incidents demonstrates that the visibility provided by current collectors is sufficient to effectively incentivize ASes to contain hijacks, thereby reducing malicious behavior.
Turning BGP hijack filtering from altruism into a market-driven transaction could fundamentally change how networks protect themselves against malicious announcements.
BGP hijacking remains a persistent threat as existing defenses, including RPKI/ROV suffer from a fundamental incentive misalignment: the networks best positioned to filter malicious announcements bear operational costs but receive no direct benefit, while the victim prefix owner captures all the value. We advocate a market-based alternative in which prefix owners post standing bounties for filtering invalid announcements of their prefixes, turning filtering from altruism into a private transaction. Our insight is that neither a propagating hijack nor its absence can hide from public route collectors, whose committed routing tables could become an independent root of trust for releasing funds of the bounty. We build on this insight to design BGPay, an escrow protocol in which filterers and monitors commit before either reveals, and a smart contract pays out on evidence rather than on the prefix owner's judgment. Analyzing 1K real hijack incidents, we find that today's collectors already provide enough visibility where it matters: ASes that are more important for containing the hijack are also highly visible from the public monitors. Hence, setting rewards proportionately to containment impact discourages misbehavior.
