Bitcoin is a peer-to-peer cryptocurrency that prevents double spending using a distributed public ledger (known as the blockchain). Due to this, true anonymity is not present in Bitcoin because funds can be traced as they pass via different addresses. It is sometimes possible to link various addresses and obtain information not apparent in the beginning (such as loops). We present a method to enhance the anonymity of Bitcoin-type cryptocurrencies. Our method uses a new primitive known as one-way aggregate signature (OWAS). The anonymity in our scheme is based on the hardness of the computation Diffie-Hellman assumption in bilinear maps and the knapsack problem. At a high level, the idea is based on 'mixing' funds and can be summarized as follows. In the blockchain, each individual block holds a list of transactions that cryptographically link the sending and receiving addresses. We modify the protocol so that transactions (and blocks) do not contain any links between sending and receiving address. Using this, we obtain a far higher degree of anonymity than what is currently offered. We use two techniques to unlink the input and output addresses of a transaction-using OWAS and applying the knapsack problem to further obfuscate the funds going in and out.

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The ever-rising computation demand is forcing the move from the CPU to heterogeneous specialized hardware, which is readily available across modern datacenters through disaggregated infrastructure. On the other hand, trusted execution environments (TEEs), one of the most promising recent developments in hardware security, can only protect code confined in the CPU, limiting TEEs’ potential and applicability to a handful of applications. We observe that the TEEs’ hardware trusted computing base (TCB) is fixed at design time, which in practice leads to using untrusted software to employ peripherals in TEEs. Based on this observation, we propose composite enclaves with a configurable hardware and software TCB, allowing enclaves access to multiple computing and IO resources. Finally, we present two case studies of composite enclaves: i) an FPGA platform based on RISC-V Keystone connected to emulated peripherals and sensors, and ii) a large-scale accelerator. These case studies showcase a flexible but small TCB (2.5 KLoC for IO peripherals and drivers), with a low-performance overhead (only around 220 additional cycles for a context switch), thus demonstrating the feasibility of our approach and showing that it can work with a wide range of specialized hardware.

Permissionless blockchains offer many advantages but also have significant limitations including high latency. This prevents their use in important scenarios such as retail payments, where merchants should approve payments fast. Prior works have attempted to mitigate this problem by moving transactions off the chain. However, such Layer-2 solutions have their own problems: payment channels require a separate deposit towards each merchant and thus significant locked-in funds from customers; payment hubs require very large operator deposits that depend on the number of customers; and side-chains require trusted validators.In this paper, we propose Snappy, a novel solution that enables recipients, like merchants, to safely accept fast payments. In Snappy, all payments are on the chain, while small customer collaterals and moderate merchant collaterals act as payment guarantees. Besides receiving payments, merchants also act as statekeepers who collectively track and approve incoming payments using majority voting. In case of a double-spending attack, the victim merchant can recover lost funds either from the collateral of the malicious customer or a colluding statekeeper (merchant). Snappy overcomes the main problems of previous solutions: a single customer collateral can be used to shop with many merchants; merchant collaterals are independent of the number of customers; and validators do not have to be trusted. Our Ethereum prototype shows that safe, fast (<2 seconds) and cheap payments are possible on existing blockchains.