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Using Crypto-Currencies to Measure Financial Activities and Uncover Potential Identities of Actors Involved.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Using Crypto-Currencies to Measure Financial Activities and Uncover Potential Identities of Actors Involved./
Author:	Huang, Yuxing.
Description:	1 online resource (154 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9780355546002

Using Crypto-Currencies to Measure Financial Activities and Uncover Potential Identities of Actors Involved.
Huang, Yuxing.

Using Crypto-Currencies to Measure Financial Activities and Uncover Potential Identities of Actors Involved. - 1 online resource (154 pages)

Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.

Thesis (Ph.D.)--University of California, San Diego, 2017.

Includes bibliographical references

Bitcoin is a digital currency that has recently gathered significant interest. From ecommerce sites to darkweb marketplaces, merchants accept Bitcoin as a form of payment. Every day, millions of dollars are transacted across Bitcoin's payment network. The value of a single bitcoin has increased from $500 to $3,000 in a one-year period since July 2016.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355546002Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

Using Crypto-Currencies to Measure Financial Activities and Uncover Potential Identities of Actors Involved.
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245 1 0 $a Using Crypto-Currencies to Measure Financial Activities and Uncover Potential Identities of Actors Involved.
264 0 $c 2017
300 $a 1 online resource (154 pages)
336 $a text $b txt $2 rdacontent
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500 $a Source: Dissertation Abstracts International, Volume: 79-05(E), Section: B.
500 $a Advisers: Alex C. Snoeren; Kirill Levchenko.
502 $a Thesis (Ph.D.)--University of California, San Diego, 2017.
504 $a Includes bibliographical references
520 $a Bitcoin is a digital currency that has recently gathered significant interest. From ecommerce sites to darkweb marketplaces, merchants accept Bitcoin as a form of payment. Every day, millions of dollars are transacted across Bitcoin's payment network. The value of a single bitcoin has increased from $500 to $3,000 in a one-year period since July 2016.
520 $a A part of the interest may stem from the decentralized design of Bitcoin. A peer-to-peer network collectively generates new coins and maintains the distributed transaction ledger, also known as the blockchain. The blockchain records transactions between public keys, rather than between real-world identities. This detachment from real-world identities makes it hard to measure financial activities and identify actors on the network, such as four cases that we study: (i) botnets stealing computational cycles, (ii) speculatively investing in digital currencies, (iii) delaying the processing of Bitcoin payments, and (iv) purchasing ads with illegal contents.
520 $a Despite this challenge, the decentralized design of Bitcoin and similar digital currencies offers public information on every transaction and the associated identities. This dissertation demonstrates that, using the four cases as examples, we can leverage this public information to analyze financial activities --- e.g. measuring the cost and revenue --- and to potentially uncover the identities of the actors involved.
520 $a In particular, we can measure the revenue and cost for Cases (i) through (iii). For (i), we show that botnets made a modest income of $118,000 between 2012 and 2013, but for some botnets we estimate the cost to victims to be more than twice the botnets' revenue. For (ii), we develop a new way to estimate the profitability of investing in digital currency markets. By simulating multiple investment strategies, we show the drastic variations in profitability and thus the extreme risks associated with digital currency investment. For (iii), we show that an adversary delayed Bitcoin transaction processing time from 0.33 to 2.67 hours, at a modest cost of $4,900 per day. Furthermore, we can uncover the potential identities of the actors involved. For (i), we identify 10 distinct botnet operations. For (iv), we identify ads paid for by potentially the same criminals.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, San Diego. $b Computer Science. $3 1182161
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10620153 $z click for full text (PQDT)