  The Ethereum blockchain network is a decentralized platform enabling smart
contract execution and transactions of Ether (ETH) [1], its designated
cryptocurrency. Ethereum is the second most popular cryptocurrency with a
market cap of more than 100 billion USD, with hundreds of thousands of
transactions executed daily by hundreds of thousands of unique wallets. Tens of
thousands of those wallets are newly generated each day. The Ethereum platform
enables anyone to freely open multiple new wallets [2] free of charge
(resulting in a large number of wallets that are controlled by the same
entities). This attribute makes the Ethereum network a breeding space for
activity by software robots (bots). The existence of bots is widespread in
different digital technologies and there are various approaches to detect their
activity such as rule-base, clustering, machine learning and more [3,4]. In
this work we demonstrate how bot detection can be implemented using a network
theory approach.
