BlockPKI: An Automated, Resilient, and Transparent Public-Key Infrastructure

This paper describes BlockPKI, a blockchain-based public-key infrastructure that enables an automated, resilient, and transparent issuance of digital certificates. Our goal is to address several shortcomings of the current TLS infrastructure and its proposed extensions. In particular, we aim at reducing the power of individual certification authorities and make their actions publicly visible and accountable, without introducing yet another trusted third party. To demonstrate the benefits and practicality of our system, we present evaluation results and describe our prototype implementation.Comment: Workshop on Blockchain and Sharing Economy Application

ARPA Whitepaper

We propose a secure computation solution for blockchain networks. The correctness of computation is verifiable even under malicious majority condition using information-theoretic Message Authentication Code (MAC), and the privacy is preserved using Secret-Sharing. With state-of-the-art multiparty computation protocol and a layer2 solution, our privacy-preserving computation guarantees data security on blockchain, cryptographically, while reducing the heavy-lifting computation job to a few nodes. This breakthrough has several implications on the future of decentralized networks. First, secure computation can be used to support Private Smart Contracts, where consensus is reached without exposing the information in the public contract. Second, it enables data to be shared and used in trustless network, without disclosing the raw data during data-at-use, where data ownership and data usage is safely separated. Last but not least, computation and verification processes are separated, which can be perceived as computational sharding, this effectively makes the transaction processing speed linear to the number of participating nodes. Our objective is to deploy our secure computation network as an layer2 solution to any blockchain system. Smart Contracts\cite{smartcontract} will be used as bridge to link the blockchain and computation networks. Additionally, they will be used as verifier to ensure that outsourced computation is completed correctly. In order to achieve this, we first develop a general MPC network with advanced features, such as: 1) Secure Computation, 2) Off-chain Computation, 3) Verifiable Computation, and 4)Support dApps' needs like privacy-preserving data exchange

Secure Multiparty Computation with Partial Fairness

A protocol for computing a functionality is secure if an adversary in this protocol cannot cause more harm than in an ideal computation where parties give their inputs to a trusted party which returns the output of the functionality to all parties. In particular, in the ideal model such computation is fair -- all parties get the output. Cleve (STOC 1986) proved that, in general, fairness is not possible without an honest majority. To overcome this impossibility, Gordon and Katz (Eurocrypt 2010) suggested a relaxed definition -- 1/p-secure computation -- which guarantees partial fairness. For two parties, they construct 1/p-secure protocols for functionalities for which the size of either their domain or their range is polynomial (in the security parameter). Gordon and Katz ask whether their results can be extended to multiparty protocols. We study 1/p-secure protocols in the multiparty setting for general functionalities. Our main result is constructions of 1/p-secure protocols when the number of parties is constant provided that less than 2/3 of the parties are corrupt. Our protocols require that either (1) the functionality is deterministic and the size of the domain is polynomial (in the security parameter), or (2) the functionality can be randomized and the size of the range is polynomial. If the size of the domain is constant and the functionality is deterministic, then our protocol is efficient even when the number of parties is O(log log n) (where n is the security parameter). On the negative side, we show that when the number of parties is super-constant, 1/p-secure protocols are not possible when the size of the domain is polynomial

Enhancing Trust in Devices and Transactions of the Internet of Things

With the rise of the Internet of Things (IoT), billions of smart embedded devices will interact frequently.These interactions will produce billions of transactions.With IoT, users can utilize their phones, home appliances, wearables, or any other wireless embedded device to conduct transactions.For example, a smart car and a parking lot can utilize their sensors to negotiate the fees of a parking spot.The success of IoT applications highly depends on the ability of wireless embedded devices to cope with a large number of transactions.However, these devices face significant constraints in terms of memory, computation, and energy capacity.With our work, we target the challenges of accurately recording IoT transactions from resource-constrained devices. We identify three domain-problems: a) malicious software modification, b) non-repudiation of IoT transactions, and c) inability of IoT transactions to include sensors readings and actuators.The motivation comes from two key factors.First, with Internet connectivity, IoT devices are exposed to cyber-attacks.Internet connectivity makes it possible for malicious users to find ways to connect and modify the software of a device.Second, we need to store transactions from IoT devices that are owned or operated by different stakeholders.The thesis includes three papers. In the first paper, we perform an empirical evaluation of Secure Boot on embedded devices.In the second paper, we propose IoTLogBlock, an architecture to record off-line transactions of IoT devices.In the third paper, we propose TinyEVM, an architecture to execute off-chain smart contracts on IoT devices with an ability to include sensor readings and actuators as part of IoT transactions