Seunghyeon Lee (KAIST, S2W LAB Inc.), Changhoon Yoon (S2W LAB Inc.), Heedo Kang (KAIST), Yeonkeun Kim (KAIST), Yongdae Kim (KAIST), Dongsu Han (KAIST), Sooel Son (KAIST), Seungwon Shin (KAIST, S2W LAB Inc.)

The Dark Web is notorious for being a major distribution channel of harmful content as well as unlawful goods. Perpetrators have also used cryptocurrencies to conduct illicit financial transactions while hiding their identities. The limited coverage and outdated data of the Dark Web in previous studies motivated us to conduct an in-depth investigative study to understand how perpetrators abuse cryptocurrencies in the Dark Web. We designed and implemented MFScope, a new framework which collects Dark Web data, extracts cryptocurrency information, and analyzes their usage characteristics on the Dark Web. Specifically, MFScope collected more than 27 million dark webpages and extracted around 10 million unique cryptocurrency addresses for Bitcoin, Ethereum, and Monero. It then classified their usages to identify trades of illicit goods and traced cryptocurrency money flows, to reveal black money operations on the Dark Web. In total, using MFScope we discovered that more than 80% of Bitcoin addresses on the Dark Web were used with malicious intent; their monetary volume was around 180 million USD, and they sent a large sum of their money to several popular cryptocurrency services (e.g., exchange services). Furthermore, we present two real-world unlawful services and demonstrate their Bitcoin transaction traces, which helps in understanding their marketing strategy as well as black money operations.

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TIMBER-V: Tag-Isolated Memory Bringing Fine-grained Enclaves to RISC-V

Samuel Weiser (Graz University of Technology), Mario Werner (Graz University of Technology), Ferdinand Brasser (Technische Universität Darmstadt), Maja Malenko (Graz University of Technology), Stefan Mangard (Graz University of Technology), Ahmad-Reza Sadeghi (Technische Universität Darmstadt)

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We Value Your Privacy ... Now Take Some Cookies:...

Martin Degeling (Ruhr-Universität Bochum), Christine Utz (Ruhr-Universität Bochum), Christopher Lentzsch (Ruhr-Universität Bochum), Henry Hosseini (Ruhr-Universität Bochum), Florian Schaub (University of Michigan), Thorsten Holz (Ruhr-Universität Bochum)

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DIAT: Data Integrity Attestation for Resilient Collaboration of Autonomous...

Tigist Abera (Technische Universität Darmstadt), Raad Bahmani (Technische Universität Darmstadt), Ferdinand Brasser (Technische Universität Darmstadt), Ahmad Ibrahim (Technische Universität Darmstadt), Ahmad-Reza Sadeghi (Technische Universität Darmstadt), Matthias Schunter (Intel Labs)

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Cleaning Up the Internet of Evil Things: Real-World Evidence...

Orcun Cetin (Delft University of Technology), Carlos Gañán (Delft University of Technology), Lisette Altena (Delft University of Technology), Takahiro Kasama (National Institute of Information and Communications Technology), Daisuke Inoue (National Institute of Information and Communications Technology), Kazuki Tamiya (Yokohama National University), Ying Tie (Yokohama National University), Katsunari Yoshioka (Yokohama National University), Michel van Eeten (Delft…

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