  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.
