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Using Artificial Intelligence To Detect Fraud On The Blockchain

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dc.contributor.advisor Buckley, Jim
dc.contributor.advisor Le Gear, Andrew Ghassemi Toosi, Farshad Sai, Ashish Rajendra 2019-07-17T09:23:44Z 2019-07-17T09:23:44Z 2019
dc.description peer-reviewed en_US
dc.description.abstract Cryptocurrencies witnessed extensive attention from both academia and industry after the inflation in 2017. This broad recognition has led to its adoption by people beyond the research domain. This increased adoption may be attributed to the overall increase in the valuation of the cryptocurrencies which at its peak in 2017 reached a combined valuation of 900 Billion USD (Cryptocurrency Market Capitalizations 2019). At the time of writing, the cryptocurrencies hold a combined valuation of 200 Billion USD (Cryptocurrency Market Capitalizations 2019). This market capitalization makes cryptocurrencies very lucrative for attackers with malicious intents. A well-orchestrated attack on these cryptocurrencies may allow an attacker to attain monetary gain. The research on the security of blockchain has identified a number of attack vectors (Chia et al., 2018). One such attack vector is the coordinated manipulation of the blockchain services (for example, a pump and dump scheme to artificially inflate the price of an Initial Coin Offering (Li, Shin, and Wang, 2018)). en_US
dc.language.iso eng en_US
dc.relation.ispartofseries 27th European Conference on Information Systems (ECIS 2019), 7-13 June; Kista, Sweden; Workshop Paper (Extended abstract)
dc.subject Blockchain en_US
dc.subject Fraud Detection en_US
dc.subject artificial intellegence en_US
dc.title Using Artificial Intelligence To Detect Fraud On The Blockchain en_US
dc.type info:eu-repo/semantics/conferenceObject en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US

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