A Policy Driven AI-Assisted PoW Framework

2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S)(2022)

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摘要
Proof of Work (PoW) based cyberdefense systems require incoming network requests to expend effort solving an arbitrary mathematical puzzle. Current state of the art is unable to differentiate between trustworthy and untrustworthy connections, requiring all to solve complex puzzles. In this paper, we introduce an Artificial Intelligence (AI)-assisted PoW framework that utilizes IP traffic based features to inform an ‘adaptive’ issuer which can then generate puzzles with varying hardness. The modular framework uses these capabilities to ensure that untrustworthy clients solve harder puzzles thereby incurring longer latency than authentic requests to receive a response from the server. Our preliminary findings reveal our approach effectively throttles untrustworthy traffic.
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关键词
trustworthy connections,IP traffic,modular framework,untrustworthy clients,harder puzzles,authentic requests,untrustworthy traffic,artificial intelligence-assisted PoW framework,cyberdefense systems,policy driven AI-assisted proof of work framework
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