Bitcoin is an immutable permissionless blockchain system that has been extensively used as a public bulletin board by many different applications that heavily relies on its immutability. However, Bitcoin's immutability is not without its fair share of demerits. Interpol exposed the existence of harmful and potentially illegal documents, images and links

In recent years, cryptocurrencies have increasingly been used in cybercrime and have become the key means of payment in darknet marketplaces, partly due to their alleged anonymity. Furthermore, the research attacking the anonymity of even those cryptocurrencies that claim to offer anonymity by design is growing and is being applied by law enforcement agencies in the fight against cybercrime. Their investigative measures require a certain degree of suspicion and it is unclear whether findings resulting from attacks on cryptocurrencies’ anonymity can indeed establish that required degree of suspicion. The reason for this is that these attacks are partly based upon uncertain assumptions which are often not properly addressed in the corresponding papers. To close this gap, we extract the assumptions in papers that are attacking Bitcoin, Monero and Zcash, major cryptocurrencies used in darknet markets which have also received the most attention from researchers. We develop a taxonomy to capture the different nature of those assumptions in order to help investigators to better assess whether the required degree of suspicion for specific investigative measures could be established. We found that assumptions based on user behaviour are in general the most unreliable and thus any findings of attacks based on them might not allow for intense investigative measures such as pre-trial detention. We hope to raise awareness of the problem so that in the future there will be fewer unlawful investigations based upon uncertain assumptions and thus fewer human rights violations.

An individual’s genetic information is possibly the most valuable personal information. While knowledge of a person’s DNA sequence can facilitate the diagnosis of several heritable diseases and allow personalized treatment, its exposure comes with significant threats to the patient’s privacy. Currently known solutions for privacy-respecting computation require the owner of the DNA to either be heavily involved in the execution of a cryptographic protocol or to completely outsource the access control to a third party. This motivates the demand for cryptographic protocols which enable computation over encrypted genomic data while keeping the owner of the genome in full control. We envision a scenario where data owners can exercise arbitrary and dynamic access policies, depending on the intended use of the analysis results and on the credentials of who is conducting the analysis. At the same time, data owners are not required to maintain a local copy of their entire genetic data and do not need to exhaust their computational resources in an expensive cryptographic protocol. In this work, we present METIS, a system that assists the computation over encrypted data stored in the cloud while leaving the decision on admissible computations to the data owner. It is based on garbled circuits and supports any polynomially-computable function. A critical feature of our system is that the data owner is free from computational overload and her communication complexity is independent of the size of the input data and only linear in the size of the circuit’s output. We demonstrate the practicality of our approach with an implementation and an evaluation of several functions over real datasets.

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