  Proof of Stake (PoS) blockchains offer promising alternatives to traditional
Proof of Work (PoW) systems, providing scalability and energy efficiency.
However, blockchains operate in a decentralized manner and the network is
composed of diverse users. This openness creates the potential for malicious
nodes to disrupt the network in various ways. Therefore, it is crucial to embed
a mechanism within the blockchain network to constantly monitor, identify, and
eliminate these malicious nodes without involving any central authority. In
this paper, we propose MRL-PoS+, a novel consensus algorithm to enhance the
security of PoS blockchains by leveraging Multi-agent Reinforcement Learning
(MRL) techniques. Our proposed consensus algorithm introduces a penalty-reward
scheme for detecting and eliminating malicious nodes. This approach involves
the detection of behaviors that can lead to potential attacks in a blockchain
network and hence penalizes the malicious nodes, restricting them from
performing certain actions. Our developed Proof of Concept demonstrates
effectiveness in eliminating malicious nodes for six types of major attacks.
Experimental results demonstrate that MRL-PoS+ significantly improves the
attack resilience of PoS blockchains compared to the traditional schemes
without incurring additional computation overhead.
