JaxNet: Scalable Blockchain Network

Today's world is organized based on merit and value. A single global currency that's decentralized is needed for a global economy. Bitcoin is a partial solution to this need, however it suffers from scalability problems which prevent it from being mass-adopted. Also, the deflationary nature of bitcoin motivates people to hoard and speculate on them instead of using them for day to day transactions. We propose a scalable, decentralized cryptocurrency that is based on Proof of Work.The solution involves having parallel chains in a closed network using a mechanism which rewards miners proportional to their effort in maintaining the network.The proposed design introduces a novel approach for solving scalability problem in blockchain network based on merged mining.Comment: 55 pages. 10 figure

Distributed Markovian Bisimulation Reduction aimed at CSL Model Checking

The verification of quantitative aspects like performance and dependability by means of model checking has become an important and vivid area of research over the past decade.\ud \ud An important result of that research is the logic CSL (continuous stochastic logic) and its corresponding model checking algorithms. The evaluation of properties expressed in CSL makes it necessary to solve large systems of linear (differential) equations, usually by means of numerical analysis. Both the inherent time and space complexity of the numerical algorithms make it practically infeasible to model check systems with more than 100 million states, whereas realistic system models may have billions of states.\ud \ud To overcome this severe restriction, it is important to be able to replace the original state space with a probabilistically equivalent, but smaller one. The most prominent equivalence relation is bisimulation, for which also a stochastic variant exists (Markovian bisimulation). In many cases, this bisimulation allows for a substantial reduction of the state space size. But, these savings in space come at the cost of an increased time complexity. Therefore in this paper a new distributed signature-based algorithm for the computation of the bisimulation quotient of a given state space is introduced.\ud \ud To demonstrate the feasibility of our approach in both a sequential, and more important, in a distributed setting, we have performed a number of case studies

Tree-formed Verification Data for Trusted Platforms

The establishment of trust relationships to a computing platform relies on validation processes. Validation allows an external entity to build trust in the expected behaviour of the platform based on provided evidence of the platform's configuration. In a process like remote attestation, the 'trusted' platform submits verification data created during a start up process. These data consist of hardware-protected values of platform configuration registers, containing nested measurement values, e.g., hash values, of loaded or started components. Commonly, the register values are created in linear order by a hardware-secured operation. Fine-grained diagnosis of components, based on the linear order of verification data and associated measurement logs, is not optimal. We propose a method to use tree-formed verification data to validate a platform. Component measurement values represent leaves, and protected registers represent roots of a hash tree. We describe the basic mechanism of validating a platform using tree-formed measurement logs and root registers and show an logarithmic speed-up for the search of faults. Secure creation of a tree is possible using a limited number of hardware-protected registers and a single protected operation. In this way, the security of tree-formed verification data is maintained.Comment: 15 pages, 11 figures, v3: Reference added, v4: Revised, accepted for publication in Computers and Securit

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