March 29, 2024, 4:10 a.m. | Thomas Niedermayer, Pietro Saggese, Bernhard Haslhofer

cs.CR updates on arXiv.org arxiv.org

arXiv:2403.19530v1 Announce Type: new
Abstract: The integration of bots in Distributed Ledger Technologies (DLTs) fosters efficiency and automation. However, their use is also associated with predatory trading and market manipulation, and can pose threats to system integrity. It is therefore essential to understand the extent of bot deployment in DLTs; despite this, current detection systems are predominantly rule-based and lack flexibility. In this study, we present a novel approach that utilizes machine learning for the detection of financial bots on …

arxiv automation blockchain bot bots can cs.cr cs.lg current deployment distributed distributed ledger efficiency ethereum financial integration integrity ledger manipulation market market manipulation system technologies threats trading understand

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