The rise of decentralized networks, such as Tor and cryptocurrencies like
Bitcoin, has enabled numerous applications, and these technologies offer
the potential to enable many more. One could also argue, however, that
they have enabled new types of crime. For example, the number of
underground markets selling drugs and other illicit goods, such as Silk
Road, has grown enormously after the introduction of Bitcoin (and they
also rely on the use of Tor). Attacks such as ransomware also seem to some
extent impossible to carry out without the use of these technologies.
In order to remove any regulatory obstacles to the adoption of the
positive applications of these technologies, it is therefore important to
address these negative applications and convince regulators they can be
dealt with appropriately. To achieve this, we will develop (1) new
heuristics for identifying relationships in a cryptocurrency ecosystem;
(2) tools for collecting and analyzing data from underground markets; and
(3) new techniques to ensure that honest users continue to maintain their
privacy. Eventually, these will all be incorporated into a microservice
architecture that provides a forensic tool.
This project is funded by an EU H2020 grant, and will be carried out with
partners across Europe. The ideal
candidate will have a strong degree in Computer Science, Mathematics, or a
related MSc or BSc course, and some proficiency with cryptography, machine
learning, and/or data analytics. To see funding information and to apply for
the position, please go
here.
I joined UCL in September 2014 as a Lecturer (Assistant Professor) in the
departments of Computer Science and
Security
and Crime Science. I am affiliated with the Information Security Group and have
broad research interests in security and cryptography.