# A Policy Driven AI-Assisted PoW Framework

arXiv: https://arxiv.org/abs/2203.10698 · HTML: https://mlsanity.com/paper/2203.10698/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 4 references that are in the map.
- First posted on arXiv 21 Mar 2022.

## Builds on (most cited first, 1 of 1)

- [Proof of Work Without All the Work: Computationally Efficient Attack-Resistant Systems](https://mlsanity.com/paper/1708.01285/) (2017)

## Built on by (most cited first, 1 of 1)

- [CAPoW: Context-Aware AI-Assisted Proof of Work based DDoS Defense](https://mlsanity.com/paper/2301.11767/) (2023)

## Abstract (arXiv)

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.