Demo Data from EDBT 2026 / reviewers in the wild / expert
Andrea Marie Weintraud
dblp:195/8314
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Blockchain and cryptocurrency security · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational finance and economics · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Blockchain and cryptocurrency security › decentralized finance
decentralized exchange |
0.5 | 1 | 2021 | Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges · WWW 2021 |
Blockchain and cryptocurrency security › fraud detection
wash trading detection |
0.5 | 1 | 2021 | Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges · WWW 2021 |
Computational finance and economics
market manipulation |
0.1 | 1 | 2021 | Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges · WWW 2021 |
Methods — techniques the papers use, named apart from their topics
blockchain analysis · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency ExchangesabstractCryptoassets such as cryptocurrencies and tokens are increasingly traded on decentralized exchanges. The advantage for users is that the funds are not in custody of a centralized external entity. However, these exchanges are prone to manipulative behavior. In this paper, we illustrate how wash trading activity can be identified on two of the first popular limit order book-based decentralized exchanges on the Ethereum blockchain, IDEX and EtherDelta. We identify a lower bound of accounts and trading structures that meet the legal definitions of wash trading, discovering that they are responsible for a wash trading volume in equivalent of 159 million U.S. Dollars. While self-trades and two-account structures are predominant, complex forms also occur. We quantify these activities, finding that on both exchanges, more than 30% of all traded tokens have been subject to wash trading activity. On EtherDelta, 10% of the tokens have almost exclusively been wash traded. All data is made available for future research. Our findings underpin the need for countermeasures that are applicable in decentralized systems. Friedhelm Victor, Andrea Marie Weintraud |
WWW | 2 |