Interoperability Among Heterogeneous Blockchains: A Systematic Literature Review
Authors: Manar Abu Talib, Sohail Abbas, Qassim Nasir, Fatima Dakalbab, Takua Mokhamed, Khawla Hassan, and Khaldoun Senjab
Blockchain technology is evolving rapidly; it has proved to be capable of solving many of the issues encountered by industries such as banking, supply chain management, and healthcare. However, several challenges must be overcome for it to reach its full potential and be adopted on a large scale. In a blockchain context, interoperability is the ability to connect multiple networks, thus enabling the exchange of assets, the invocation of smart contracts, and the verification of data, all while ensuring consistency between systems. In reality, most of the existing blockchain networks operate in a stand-alone environment, isolated from other blockchain networks. This causes a lack of communication that further leads to restrictions imposed on data, i.e., preventing it from transmitting freely to and from various blockchains regardless of the underlying infrastructure. Given the potential of blockchain interoperability, researchers have proposed many protocols over the last few years, and the solutions being offered are on the rise. In this chapter, we will discuss the methodologies used in the available solutions and compare several of their characteristics, including throughput, average block confirmation time, and consensus mechanism. Furthermore, we will present the projects currently implementing these protocols and their future directions.
Balancing Trust and Performance in Digital Currency and Smart Contract Systems
Author: Karl Wüst
The development of blockchain technology, starting with Bitcoin in 2008, has received considerable attention and sparked an incredible amount of innovation. While the main contribution of Bitcoin was the creation of a peer-to-peer digital currency system without the need for a central trusted party, newer developments have focused on smart contracts and privacy enhancing technology.
One of the defining aspects of blockchain systems is their decentralization. This decentralization can help to reduce the required trust assumptions, but it also comes with a price: Decentralized systems, like blockchains, tend to be less efficient and less scalable than more centralized solutions and they often put heavy requirements on clients. They can also make some properties, such as privacy, harder to achieve, since all information is disseminated to all participants.
While blockchains, in particular permissionless blockchains, are often presented as trustless, this is not actually the case. They do not require trust in one single central party, but they still come with explicit and implicit trust assumptions, for example, the assumption that a majority of the mining power is in the hands of honest miners in proof-of-work blockchains.
In this thesis, we explore how small changes in the explicit trust assumptions can be used in digital currency and smart contract systems to gain new properties or improve performance. In particular, we consider three topics – privacy for lightweight clients, smart contract scalability, and central bank digital currencies (CBDCs) – and show how each of them can be improved in terms of the achievable performance or properties, by either introducing trusted hardware, trusted committees, or a central party trusted for some aspects of the system.
First, we develop two systems, called Bite and ZLiTE that use trusted execution environments to improve the privacy of lightweight clients in systems like Bitcoin and that enable privacy-preserving lightweight clients for anonymous cryptocurrencies like Zcash. We show how these systems can be protected against adversaries with full control over a node running these systems by eliminating leakage through network traffic, disk accesses and digital side-channels.
Second, we design two systems, ACE and Bitcontracts, that improve the scalability of smart contracts. ACE enable the execution of computationv ally complex smart contracts and Bitcontracts enables the execution of expressive smart contracts on top of legacy cryptocurrencies, like Bitcoin, that do not natively support such contracts. Both systems execute contracts in committees that are chosen in a contract-specific trust model and thus provide hybrids between permissionless and permissioned systems. ACE is the first system that securely enables cross-contract calls given this trust model and allows for execution of contracts with a computational complexity several orders of magnitude higher than existing systems. Bitcontracts combines ACE’ trust model with a new execution model and is the first to securely allow the execution of Ethereum-style contracts on top of legacy blockchains.
Finally, we show for central bank digital currencies, how privacy, regulation, and performance can be achieved simultaneously in a permissioned blockchain setting, with PRCash, or in a setting that explicitly trusts the central bank for the integrity of the currency, with Platypus. PRCash adds a privacy preserving regulation mechanism on top of commitment-based transactions for blockchain systems that hide the identities of the transaction parties and the transaction value. We then show with Platypus how the centralized setting that exists for CBDCs in practice can be leveraged to achieve even stronger privacy properties and massive scalability.
Implementation and evaluation of the DAOM framework and support tool for designing blockchain decentralized applications
Authors: Chibuzor Udokwu, Patrick Brandtner, Alex Norta, Alexandr Kormiltsyn, and Raimundas Matulevičius
Inter-organizational collaboration is an important aspect of organizational operations. Traditional systems that support organizations in executing these collaborations are inefficient, not inter-operable and insecure. Novel functions provided by blockchain technology yields the potential for addressing problems that affect organizational collaborations by enabling tamper-proof, transparent, and secure systems for the exchange of information between organizations. Still, a proper approach for building blockchain-decentralized applications (DApps) that support inter-organizational collaborations is missing. The DAOM framework addresses this gap by providing a model-driven design approach for building DApps. This paper shows the development of the semantics of the DAOM framework, implementation of the support tool, and the evaluation of the DAOM framework and support tool. We conducted an evaluation to understand the usefulness of the DAOM framework in developing blockchain DApps and the effectiveness of the support tool in producing DAOM diagram models. The evaluation result shows that the framework is useful and applicable for developing DApps for inter-organizational collaborations. Furthermore, evaluation of the tool support shows that DApps can be modelled efficiently and correctly with the implemented enterprise-modelling software.
Deep learning classification of bitcoin miners and exploration of upper confidence bound algorithm with less regret for the selection of honest mining
Authors: M. J. Jeyasheela Rakkini & K. Geetha
Bitcoin is the most popular cryptocurrency and it uses proof of work protocol for consensus of all transactions in a block. The blocks are to be appended to the digital ledger, the blockchain. The miners compete for the mining of blocks in the main canonical blockchain. A miner can participate in block mining either individually with his computational power or join a mining pool. Here, the classification of crypto address, whether it belongs to a mining pool or an individual miner, is done with a deep learning Keras framework. The classification accuracy of 99.47% is obtained with 100,000 addresses which is higher than the machine learning random forest classification obtained by Kaggle with 22,000 addresses. The miners in mining pools deploy selfish mining or honest mining to mine a block and get the reward accordingly. In block mining, both honest and selfish miners expose the blocks produced by them. The default protocol of the main canonical blockchain leads to the selection of the longest branch of blocks of the selfish miner, discarding the honest miner’s block. To alleviate this, we deploy a reinforcement learning algorithm to choose the block with high upper confidence bound value. This selection explores the branch exposed by honest miners. The algorithm is deployed after the first difficulty adjustment algorithm, where there is more selfish mining activity. Our promising results show that the main blockchain exhibits less regret by selecting the honest miner’s branch.
Link: Deep learning classification of bitcoin miners and exploration of upper confidence bound algorithm with less regret for the selection of honest mining - Journal of Ambient Intelligence and Humanized Computing
Networks of Ethereum Non-Fungible Tokens: A graph-based analysis of the ERC-721 ecosystem
Authors: S. Casale-Brunet, P. Ribeca, P. Doyle, and M. Mattavelli
Non-fungible tokens (NFTs) as a decentralized proof of ownership represent one of the main reasons why Ethereum is a disruptive technology. This paper presents the first systematic study of the interactions occurring in a number of NFT ecosystems. We illustrate how to retrieve transaction data available on the blockchain and structure it as a graph-based model. Thanks to this methodology, we are able to study for the first time the topological structure of NFT networks and show that their properties (degree distribution and others) are similar to those of interaction graphs in social networks. Time-dependent analysis metrics, useful to characterize market influencers and interactions between different wallets, are also introduced. Based on those, we identify across a number of NFT networks the widespread presence of both investors accumulating NFTs and individuals who make large profits.
Formal Verification of the Ethereum 2.0 Beacon Chain
Authors: Franck Cassez, Joanne Fuller, and Aditya Asgaonkar
We report our experience in the formal verification of the reference implementation of the Beacon Chain. The Beacon Chain is the backbone component of the new Proof-of-Stake Ethereum 2.0 network: it is in charge of tracking information about the validators, their stakes, their attestations (votes) and if some validators are found to be dishonest, to slash them (they lose some of their stakes). The Beacon Chain is mission-critical and any bug in it could compromise the whole network. The Beacon Chain reference implementation developed by the Ethereum Foundation is written in Python, and provides a detailed operational description of the state machine each Beacon Chain’s network participant (node) must implement. We have formally specified and verified the absence of runtime errors in (a large and critical part of) the Beacon Chain reference implementation using the verification-friendly language Dafny. During the course of this work, we have uncovered several issues, proposed verified fixes. We have also synthesised functional correctness specifications that enable us to provide guarantees beyond runtime errors. Our software artefact is available at GitHub - ConsenSys/eth2.0-dafny: Eth2.0 spec in Dafny.
An Exploration of Governing via IT in Decentralized Autonomous Organizations
Authors: Tobias Mini, Eleunthia Wong Ellinger, Robert W. Gregory, and Thomas Widjaja
A decentralized autonomous organization (DAO) is a distinct form of platform meta-organization that heavily relies on smart contracts running on blockchains to govern a distributed network of autonomous actors, thereby continuing the shift toward governance via IT. Motivated by the fact that this shift toward governance via IT in DAOs challenges established assumptions in the literature on IT governance, we explore how DAOs are governed via IT. For this purpose, we applied techniques of grounded theory to build inductive theory by analyzing five cases of DAOs (Aragon, Flare Networks, KyberDAO, MakerDAO, and MolochDAO) based on white papers, blog entries, and newspaper articles. Our findings implicate that DAOs governed via IT synthesize autonomy and alignment through the mechanism of “establishing algorithmic organization.” At the same time, DAOs rely on a more pluralistic and decentralized form of algorithmic management through the mechanism of “taming algorithmic power.”