The First International Workshop on Big Data Against Darknet Crimes (BadAce) is co-located with IEEE Big Data conference in Los Angeles, CA, USA on December 9-12, 2019.

1. Introduction

The darknet is a portion of the Internet that limits the ability to track users' identity. The Onion Routing (Tor) system provides hidden services for hosting the .onion darknet websites. Other platforms include I2P and freenet. While these platforms protect the freedom and privacy, they become the hotbeds of darknet crimes especially after Bitcoin appears. Since both Tor and Bitcoin hide users' identity, performing crimes in darknet has minimal risks.

Numerous illicit darknet websites are created and facilitating criminal activities. For example, cryptomarkets have facilitated illicit product trading and transformed the methods used for illicit product transactions. Using this system has made buying illicit products online as easy as an Amazon purchase. Payments are made using Bitcoin and products are delivered to a pick-up address or to an email address. The proliferation of illicit darknet websites is an increasingly menacing threat to the national and global security.

Even the darknet keep users anonymized, the distributed nature allows us to easily obtain lots of anonymized public data. Examples data sources include ads and ratings in cryptomarkets, discussion posts in darknet forums, public ledgers and P2P network traffic packets in cryptocurrency, and Tor network traffic packets. This big darknet data creates new opportunities and challenges for understanding criminal activities, which can lead to disruption.

This workshop aims to draw the attention of big data researchers to this new research domain and bring multidiscipline researchers together to generate new methods and systems to gather intelligence from the darknet and eventually lead to disruption.

2. Research topics (not limited to):

Search engine for searching new .onion sites
Darknet website scrapers/parsers and database design
Cryptomarket websites data analysis including product description, vendor profiles, and ratings
Knowledge based construction tailed for darknet ads
Fingerprints from text, image, traffic packets, and transactions and can link darknet users and/or clearnet users in social platforms
Network analysis in darknet including community detection, information infusion and influence analysis
Dynamic multilayer network analysis in darknet
Cryptocurrency public ledger analysis
Fraud and illicit transaction detection in cryptocurrencies
Mixing services and its role in darknet crimes
Similarity and difference between financial activities in darknet and clearnet commercial markets
Similarity and difference between social behaviors/networks in darknet and clearnet social platforms/forums
Tor network traffic packet analysis and how to use it to track criminals
Bitcoin network traffic packet analysis and how to use it to link bitcoin addresses with computers
Forensics that can be extracted from darknet data
Analyzing the data collected from I2P or Freenet that can be used for combating darknet crimes
Operations that can disrupt the illicit supply chains
Application domains include any cyber crimes and any products that are being sold in darknet. Examples include human trafficking, opioids or any other kinds of drugs, financial fraud, and cybersecurity.