Ethereum 2.0 uses a Proof-of-Stake-based consensus which aims to minimize the impact of malicious validators by decentralizing the voting protocol. In this paper we investigate the lifecycle of a validator in a consensus protocol similar to Ethereum 2.0 but with simplifications introduced for tractability. In particular, the protocol operates with near-single slot finality and includes the impact of behaviors such as truthful and false voting, abstention from voting, voluntary exit from the validator committee, and return to the committee upon depositing the required stake. Using probabilistic techniques and a Markov chain model, we examine the impact of all those factors on consensus probability. Our results indicate that the probability of truthful voting has a predominant effect on consensus, although the interplay between probabilities of voluntary exit and waiting before returning to the committee also plays an important role. We also investigate the process of fork resolution and model the behavior of the blockchain in the presence of multiple tips, and we show that probability of truthful voting is equally important in this case as higher values accelerate fork resolution.

Implementing a consensus protocol in a Proof-of-Stake context requires a delicate tradeoff between different system parameters. Ethereum 2.0, probably the most popular PoS system today, uses a large number of validators to achieve decentralization, but long time windows, during which both blocks and attestations for those blocks are considered valid, open up the possibility for a number of attacks that target the process of consensus. A possible remedy would be to try to achieve single-slot finality similar to that obtained in Practical Byzantine Fault Tolerance (PBFT). In this paper, we develop a Markov chain model of validator lifecycle in an Ethereum 2.0-like system with single-slot finality which includes penalties and rewards, as well as the possibility of voluntary exit and waiting to rejoin the validator pool. Using the model, we obtain the probability of achieving consensus as the function of probabilities of different events, most notably the probability of truthful voting by the validator. Our results indicate that consensus is rather sensitive to false voting, and that low probability of waiting and low probability of voluntary exit help improve the probability of consensus.

In this paper, we analyze the performance of Ethereum data distribution network using a probabilistic model which allows accurate modeling of data propagation but also of forking, which happens when the blockchain maintained by the network temporarily splits into multiple versions due to a disagreement over the validity of a particular block. We also investigate the duration of inconsistent states of the ledger, which refers to the amount of time that the network remains split or partitioned. Finally, we model the block withholding attack and block slowdown attack, and analyze their impact on network performance of the network in terms of quality indicators such as block delivery time, the duration of ledger inconsistency, and forking probability. We also propose countermeasures for the block withholding attack.

In this paper, we analyze the performance of Ethereum data distribution network using a probabilistic model which allows accurate modeling of data propagation. We then apply the model to analyze the performance of data propagation in Ethereum when using geth protocol under block withholding attack, Eclipse attack, and block slowdown attack. We also propose countermeasures for the block withholding attack and Eclipse attack.

We provide a comprehensive analytical model for block distribution in the Ethereum distribution network. We begin with a model for node connectivity based on reported measurements' and model the distribution of blocks using a Jackson network together with a priority M/G/1 queuing system. Our results show that the probability distribution of block response time is close to exponential distribution, while block delivery time exhibits a hypo-exponential distribution. Both distributions exhibit a thicker tail than the exponential distribution due to the peculiarities of the gossip-like protocol used to propagate blocks and transactions in Ethereum.