Problem
Research questions and friction points this paper is trying to address.
Mitigating DoS attacks
Cost-effective server pricing
Estimator-based job distribution
Bankrupting DoS Attackers
🤖 AI Summary
This paper addresses the severe cost asymmetry between attackers and defenders in Denial-of-Service (DoS) attacks by proposing an economic deterrence mechanism based on dynamic pricing. The server employs a lightweight probabilistic estimator to continuously characterize legitimate traffic features and dynamically prices each incoming request, thereby ensuring that the attacker’s per-unit cost asymptotically exceeds the combined cost incurred by the server and honest users. Theoretical contributions include: (i) the first asymptotically optimal guarantee wherein the attacker’s cost strictly dominates the defender’s; (ii) provably optimal online pricing algorithms for both synchronous and asynchronous adversarial models; and (iii) tight lower bounds linking estimation error to cost growth. Experimental and competitive analysis demonstrates that, under constant-factor estimation error, the server’s total cost grows strictly slower than the attacker’s—significantly enhancing the economic sustainability and deterrent efficacy of DoS defense.
📝 Abstract
Can we make a denial-of-service attacker pay more than the server and honest clients? Consider a model where a server sees a stream of jobs sent by either honest clients or an adversary. The server sets a price for servicing each job with the aid of an estimator, which provides approximate statistical information about the distribution of previously occurring good jobs. We describe and analyze pricing algorithms for the server under different models of synchrony, with total cost parameterized by the accuracy of the estimator. Given a reasonably accurate estimator, the algorithm's cost provably grows more slowly than the attacker's cost, as the attacker's cost grows large. Additionally, we prove a lower bound, showing that our pricing algorithm yields asymptotically tight results when the estimator is accurate within constant factors.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Dynamic pricing with estimator
Asymptotically tight cost control
Server-attacker cost differentiation
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