EDBT 2026 Demo / reviewers in the wild / expert
Paturi Varun Chowdhary
dblp:159/2759 · also Varun Chowdhary Paturi
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 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 |
Digital forensics and information hiding · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Digital forensics and information hiding
cryptocurrency forensics |
0.8 | 1 | 2024 | Pulling Off The Mask: Forensic Analysis of the Deceptive Creator Wallets Behind Smart Contract Fraud · SP 2024 |
Digital forensics and information hiding › digital forensics
forensic analysis |
0.8 | 1 | 2024 | Pulling Off The Mask: Forensic Analysis of the Deceptive Creator Wallets Behind Smart Contract Fraud · SP 2024 |
Methods — techniques the papers use, named apart from their topics
forensic analysis pipeline · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Pulling Off The Mask: Forensic Analysis of the Deceptive Creator Wallets Behind Smart Contract FraudabstractCriminals, using crypto wallets referred to as Deceptive Creator Wallets (DCWs), have orchestrated fraudulent activities by luring victims to transfer funds to fraud smart contracts. Since it is almost impossible to reverse the transactions or pinpoint the true identity of the criminals, the industry has turned to flagging such contracts as user warnings. However, current mitigation efforts focus on individual contracts, overlooking the DCWs behind the scenes. Consequently, our research found that this oversight allows fraud to thrive. To address this, we developed CoCo, an automated forensic analysis pipeline that processes a single fraud contract and generates evidence that the legal authorities need to mitigate the fraud. Applying CoCo to 157 confirmed fraud contracts, our research uncovered 1,283,198 associated contracts linked to 91 DCWs, responsible for 2,638,752 ETH ($2,089,504,682) in illicit profits. More alarmingly, CoCo traces the fraudulent activities back to September 2017. In response, we are closely collaborating with Etherscan and the FBI to combat the fraud identified in our study. Mingxuan Yao, Haichuan Xu, Shih-Huan Chou, Paturi Varun Chowdhary, Amit Kumar Sikder, Brendan Saltaformaggio |
SP | 5 |