In this talk, we will first describe one of our novel heuristics to link wallets based on the patterns observed in the Ripple network as the result of two wallet owners settling a Bitcoin exchange over their Ripple credit link. This heuristic facilitates the linking of Bitcoin and Ripple wallets owned by the two involved users, therefore allowing for the first time to perform clustering of wallets across two different payment networks. In fact, it is not restricted to Bitcoin, and enables the clustering of Ripple wallets with other cryptocurrencies wallets (i.e., altcoins), thereby enlarging the set of clustered wallets. Second, we will discuss the analysis of our findings. In particular, to analyze the efficacy of our heuristics, we crawl the Ripple network (as of December 2015) obtaining a total of 174, 738 wallets, 115, 996 credit links, and 17, 645, 343 transactions using them. We deploy our heuristics over this dataset, resulting in the clustering of 959 Ripple wallets, 3, 113 Bitcoin wallets and 1, 130 Altcoin wallets, which are involved in 934, 484 transactions in total. The set of clustered wallets has allowed us to reconstruct the complete set of transactions of the most widely deployed gateways1, and showed that is indeed bigger than the set of transactions associated to their publicly announced Ripple wallets, as shown in Fig. 1. Finally, we will also discuss the privacy implications of setting a Ripple validator server on the Ripple network. These servers collects transactions from the Ripple users and can significantly increase the deanonymization rate from the observed