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Abstract:
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Online anonymous marketplaces or darknet marketplaces are commercial marketplaces that run on the dark web (parts of the web accessible only through anonymizing software such as Tor). Buyers and sellers preserve anonymity by using cryptocurrencies and PGP. As a result these marketplaces are used primarily for illegal activities such as sales of drugs. There are many such marketplaces, and sellers can operate accounts on different marketplaces, or multiple accounts on the same marketplace. We explore methods to match these accounts, to predict which of them belong to the same sellers. This is analogous to the forensic matching of DNA, cartridge cases, and so forth. In this talk we describe various approaches to matching, beginning with supervised methods, where labels are generated using PGP keys. Some of these labels might be erroneous, and we try to fix these, for example using an active learning approach. We also consider the possibility of using semi-supervised or unsupervised methods.
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