The Metaverse has emerged as the next generation of the Internet. It aims to provide an immersive, persistent virtual space where people can live, learn, work and interact with each other. However, the existing technology is inadequate to guarantee high visual quality and ultra-low latency service for the Metaverse players. Mobile Edge Computing (MEC) is a paradigm where proximal edge servers are utilized to perform computation-intensive and latency-sensitive tasks like image processing and video analysis. In MEC, the large amount of data is processed by edge servers closest to where it is captured, thus significantly reducing the latency and providing almost real-time performance. In this paper, we integrate fundamental elements (5G and 6G wireless communications, Blockchain, digital twin and artificial intelligence) into the MEC framework to facilitate the Metaverse. We also elaborate on the research problems and applications in the MEC-enabled Metaverse. Finally, we provide a case study to establish a thorough knowledge of the user utility maximization problem in a real-world scenario and gain some insights about trends in potential research directions.
Decentralized Storage Networks (DSNs) can gather storage resources from mutually untrusted providers and form worldwide decentralized file systems. Compared to traditional storage networks, DSNs are built on top of blockchains, which can incentivize service providers and ensure strong security. However, existing DSNs face two major challenges. First, deduplication can only be achieved at the directory-level. Missing file-level deduplication leads to unavoidable extra storage and bandwidth cost. Second, current DSNs realize file indexing by storing extra metadata while blockchain ledgers are not fully exploited. To overcome these problems, we propose FileDAG, a DSN built on DAG-based blockchain to support file-level deduplication in storing multi-versioned files. When updating files, we adopt an increment generation method to calculate and store only the increments instead of the entire updated files. Besides, we introduce a two-layer DAG-based blockchain ledger, by which FileDAG can provide flexible and storage-saving file indexing by directly using the blockchain database without incurring extra storage overhead. We implement FileDAG and evaluate its performance with extensive experiments. The results demonstrate that FileDAG outperforms the state-of-the-art industrial DSNs considering storage cost and latency.
Samuel Karumba, Salil S. Kanhere, Raja Jurdak, Subbu Sethuvenkatraman
Flexible resources in built environments are seen as a low-cost opportunity for delivering grid management services. Consequently, the centralised aggregator model, where the aggregator is used to bundle demand flexibility from flexible resources and deliver it to flexibility customers such as Distributed/Transmission System Operator (DSO/TSO) in flexibility markets, has been adopted. However, the aggregator role introduces various security and trust challenges. In this work, we propose a blockchain-based flexibility trading framework dubbed PlexiChain to address the security and trust challenges the aggregator poses in the centralised aggregator model. The security evaluations performed using a real-world dataset show that PlexiChain is robust against known security attacks, such as MadIoT and False Data Injection attacks. Additionally, the performance evaluations show that PlexiChain has lower computation and communication costs than other blockchain-based applications in resource-constrained environments.
Data/Web Hosting is a service that lets enterprises or selves present their data on the internet that users can access. The firm providing such services are web/data host. Apart from that, such services require incessant support, and not everyone can afford a particular centralized data host service. The peer-to-peer(P2P) protocol, the Interplanetary file system(IPFS), is augmenting into a legitimate alternative to traditional data and web hosting. This paper put forward a decentralized blockchain IPFS-based interactive manageable model, and the work presents an application and schematic that serves as a Proof of Concept(PoC) of decentralized blockchain technology that can be wielded to create an immutable record of energy and resource usage for further analysis and estimation of yield at a scale. IPFS hosts an immutable record that would be independently verifiable and available in perpetuity. First, having the user connect to the service through an IPFS node, then requesting the user upload their data. Then the data is uploaded, and a CID(Content Identification) and a QR code are returned to the user, who can then compute and visualize the results through the application. This system enables the novel application of decentralized data storage to capture, add and visualize yield and environmental data and track it further down the supply chain.
Blockchain has become a popular emergent technology in many industries. It is suitable for a broad range of applications, from its base role as an immutable distributed ledger to the deployment of distributed applications. Many organizations are adopting the technology, but choosing a specific blockchain implementation in an emerging field exposes them to significant technology risk. Selecting the wrong implementation could expose an organization to security vulnerabilities, reduce access to its target audience, or cause issues in the future when switching to a more mature protocol. Blockchain interoperability aims to solve this adaptability problem by increasing the extensibility of blockchain, enabling the addition of new use cases and features without sacrificing the performance of the original blockchain. However, most existing blockchain platforms need to be designed for interoperability, and simple operations like sending assets across platforms create problems. Cryptographic protocols that are secure in isolation may become insecure when several different (individually secure) protocols are composed. Similarly, utilizing trusted custodians may undercut most of the benefits of decentralization offered by blockchain-based systems. Even though there is some research and development in the field of blockchain interoperability, a characterization of the interoperability solutions for various infrastructure options is lacking. This paper presents a methodology for characterizing blockchain interoperability solutions that will help focus on new developments and evaluate existing and future solutions in this space.
Web3 aims at creating a decentralized platform that is competitive with modern cloud infrastructures that support today's Internet. However, Web3 is still limited, supporting only applications in the domains of content creation and sharing, decentralized financing, and decentralized communication. This is mainly due to the technologies supporting Web3: blockchain, IPFS, and libp2p, that although provide a good collection of tools to develop Web3 applications, are still limited in terms of design and performance. This motivates the need to better understand these technologies as to enable novel optimizations that can push Web3 to its full potential. Unfortunately, understanding the current behavior of a fully decentralized large-scale distributed system is a difficult task, as there is no centralized authority that has full knowledge of the system operation. To this end, in this paper we characterize the workload of IPFS, a key enabler of Web3. To achieve this, we have collected traces from accesses performed by users to one of the most popular IPFS gateways located in North America for a period of two weeks. Through the fine analysis of these traces, we gathered the amount of requests to the system, and found the providers of the requested content. With this data, we characterize both the popularity of requested and provided content, as well as their geo-location (by matching IP address with the MaxMind database). Our results show that most of the requests in IPFS are only to a few different content, that is provided by large portion of peers in the system. Furthermore, our analysis also shows that most requests are provided by the two largest portions of providers in the system, located in North America and Europe. With these insights, we conclude that the current IPFS architecture is sub-optimal and propose a research agenda for the future.
Networks are composed of logical nodes and edges for communications. The atomistic component of things connected to the network is a memory chip. Accordingly, the unique linkage of a memory chip and a logical node can be promising to resolve the root-of-trust problem on the Internet-of-Things. For this aim, we propose a protocol of challenge-response using a memory chip. For the central management, a central node controls the entry of electronic appliances with a memory chip into the network, and excludes a fake node (e.g., the spoofing entity) from the network that the central node manages. For the decentralized communications, Merkle's tree turns out to be composed of memory chips to which the logical nodes are uniquely linked, respectively. The root of Merkle turns out to be the memory chip that stores the latest record of data transactions. We can register this memory chip as a new block by satisfying the requirement of the proof-of-consensus. After blocks are chained, it gets harder for even the central node to manipulate transaction record among memory chips. By this way, the decentralized system (e.g., blockchain) and the central management can coexist. A new idea of security state is also discussed briefly.
Andrei Tonkikh, Pavel Ponomarev, Petr Kuznetsov, Yvonne-Anne Pignolet
A typical blockchain protocol uses consensus to make sure that mutually mistrusting users agree on the order in which their operations on shared data are executed. However, it is known that asset transfer systems, by far the most popular application of blockchains, can be implemented without consensus. Assuming that no account can be accessed concurrently and every account belongs to a single owner, one can efficiently implement an asset transfer system in a purely asynchronous, consensus-free manner. It has also been shown that implementing asset transfer with shared accounts is impossible without consensus. In this paper, we propose CryptoConcurrency, an asset transfer protocol that allows concurrent accesses to be processed in parallel, without involving consensus, whenever possible. More precisely, if concurrent transfer operations on a given account do not lead to overspending, i.e. can all be applied without the account balance going below zero, they proceed in parallel. Otherwise, the account's owners may have to access an external consensus object. Notably, we avoid relying on a central, universally-trusted, consensus mechanism and allow each account to use its own consensus implementation, which only the owners of this account trust. This provides greater decentralization and flexibility.
Blokchain is a promising technology to enable distributed and reliable data sharing at the network edge. The high security in blockchain is undoubtedly a critical factor for the network to handle important data item. On the other hand, according to the dilemma in blockchain, an overemphasis on distributed security will lead to poor transaction-processing capability, which limits the application of blockchain in data sharing scenarios with high-throughput and low-latency requirements. To enable demand-oriented distributed services, this paper investigates the relationship between capability and security in blockchain from the perspective of block propagation and forking problem. First, a Markov chain is introduced to analyze the gossiping-based block propagation among edge servers, which aims to derive block propagation delay and forking probability. Then, we study the impact of forking on blockchain capability and security metrics, in terms of transaction throughput, confirmation delay, fault tolerance, and the probability of malicious modification. The analytical results show that with the adjustment of block generation time or block size, transaction throughput improves at the sacrifice of fault tolerance, and vice versa. Meanwhile, the decline in security can be offset by adjusting confirmation threshold, at the cost of increasing confirmation delay. The analysis of capability-security trade-off can provide a theoretical guideline to manage blockchain performance based on the requirements of data sharing scenarios.
In this work, we review the architecture design of existing federated General Adversarial Networks (GAN) solutions and highlight the security and trust-related weaknesses in the existing designs. We then describe how these weaknesses make existing designs unsuitable for the requirements needed for a consortium of health registries working towards generating synthetic datasets for research purposes. Moreover, we propose how these weaknesses can be addressed with our novel architecture solution. Our novel architecture solution combines several building blocks to generate synthetic data in a decentralised setting. Consortium blockchains, secure multi-party computations, and homomorphic encryption are the core building blocks of our proposed architecture solution to address the weaknesses in the existing design of federated GANs. Finally, we discuss our proposed solution's advantages and future research directions.
Swarm learning (SL) is an emerging promising decentralized machine learning paradigm and has achieved high performance in clinical applications. SL solves the problem of a central structure in federated learning by combining edge computing and blockchain-based peer-to-peer network. While there are promising results in the assumption of the independent and identically distributed (IID) data across participants, SL suffers from performance degradation as the degree of the non-IID data increases. To address this problem, we propose a generative augmentation framework in swarm learning called SL-GAN, which augments the non-IID data by generating the synthetic data from participants. SL-GAN trains generators and discriminators locally, and periodically aggregation via a randomly elected coordinator in SL network. Under the standard assumptions, we theoretically prove the convergence of SL-GAN using stochastic approximations. Experimental results demonstrate that SL-GAN outperforms state-of-art methods on three real world clinical datasets including Tuberculosis, Leukemia, COVID-19.
We study security-latency bounds for Nakamoto consensus, i.e., how secure a block is after it becomes k-deep in the chain. We improve the state-of-the-art bounds by analyzing the race between adversarial and honest chains in three different phases. We find the probability distribution of the growth of the adversarial chains under models similar to those in Guo and Ren (2022) when a target block becomes k-deep in the chain. We analyze certain properties of this race to model each phase with random walks that provide tighter bounds than the existing results. Combining all three phases provides novel upper and lower bounds for blockchains with small$\lambda \Delta $.
The financial sector's adoption of technology-driven data analysis has enhanced operational efficiency and revenue generation by leveraging personal sensitive data. However, the inherent characteristics of blockchain hinder decentralized finance (DeFi) from accessing necessary sensitive user data. To address this challenge, we introduce a protocol that both safeguards user privacy and ensures data availability through the incorporation of homomorphic encryption and zero-knowledge-proof techniques in blockchain technology. This novel protocol helps mitigate privacy risks caused by sensitive data leaks while improving the capital efficiency of the DeFi market. Furthermore, we explore the applicability of these privacy-preserving methods in on-chain ecosystems and cross-border financial applications. Our solution contributes to secure, user-centric solutions for DeFi while upholding principles of decentralization and privacy protection.
MEV attacks have been an omnipresent evil in the blockchain world, an implicit tax that uninformed users pay for using the service. The problem arises from the miners' ability to reorder and insert arbitrary transactions in the blocks they mine. This paper proposes a 2-phased transaction protocol to eliminate MEV attacks. The user requests an interaction token from the on-chain counter-party. This token serves as a blind preemption for the counter-party and prevents the reordering of transactions at lower levels in the blockchain framework. We prove the correctness of the CoMMA protocol and demonstrate its efficacy against MEV attacks.
Non-fungible tokens (NFTs) are unique digital items with blockchain managed ownership. Ethereum blockchain based smart contract created the environment for NFTs (ERC721) to reach its one of the most important future application domains. Non fungible tokens got more attention when the market saw record breaking sales in 2021. Virtually anything of value can be traced and traded on the blockchain network by minting them as NFTs. NFTs provide the users with a decentralized proof of ownership representation, as every transaction and trade of NFTs gets recorded in the Ethereum network blocks. The value of NFTs is derived from their being non fungible meaning that the token cannot be replaced with an identical token (giving it inherent scarcity). In this paper, we study the growth rate and evolutionary nature of the NFT network and try to understand the NFT ecosystem. We explore the evolving nature of the NFT interaction network from a temporal graph perspective. We study the growth rate and observer the semantics of the network. Here on the observer network, we will run two graph algorithms on the dataset. Lastly, observe and forecast the survival of NFTs bubble by applying the Logarithmic periodic power law (LPPL) model to the time series data on one of the most famous NFT collections CryptoPunks (predicting price increase), which has seen sales of around $23.7 million around mid of 2021.
Sarah Azouvi, Christian Cachin, Le, Duc V., Marko Vukolić · 5 authors
Blockchain protocols implement total-order broadcast in a permissionless setting, where processes can freely join and leave. In such a setting, to safeguard against Sybil attacks, correct processes rely on cryptographic proofs tied to a particular type of resource to make them eligible to order transactions. For example, in the case of Proof-of-Work (PoW), this resource is computation, and the proof is a solution to a computationally hard puzzle. Conversely, in Proof-of-Stake (PoS), the resource corresponds to the number of coins that every process in the system owns, and a secure lottery selects a process for participation proportionally to its coin holdings. Although many resource-based blockchain protocols are formally proven secure in the literature, the existing security proofs fail to demonstrate why particular types of resources cause the blockchain protocols to be vulnerable to distinct classes of attacks. For instance, PoS systems are more vulnerable to long-range attacks, where an adversary corrupts past processes to re-write the history, than Proof-of-Work and Proof-of-Storage systems. Proof-of-Storage-based and Proof-of-Stake-based protocols are both more susceptible to private double-spending attacks than Proof-of-Work-based protocols; in this case, an adversary mines its chain in secret without sharing its blocks with the rest of the processes until the end of the attack. In this paper, we formally characterize the properties of resources through an abstraction called resource allocator and give a framework for understanding longest-chain consensus protocols based on different underlying resources. In addition, we use this resource allocator to demonstrate security trade-offs between various resources focusing on well-known attacks (e.g., the long-range attack and nothing-at-stake attacks).
According to experts, one third of all IT vulnerabilities today are due to inadequate software verification. Internal program processes are not sufficiently secured against manipulation by attackers, especially if access has been gained. There is a lack of internal control instances that can monitor and control program flows. Especially when a software vulnerability becomes known, quick action is required, whereby the consequences for an individual application are often not foreseeable. With our approach (B)LOCKBOX, software building blocks act as verified entities within a transaction-based blockchain network. Source Code, binaries and application execution become supervised. Unwanted interference and manipulation are prevented by the integrity of the distributed system.
Redactable Blockchain aims to ensure immutability of the data for most of appications, and provide authorized mutability for some specific applications such as removing illegal content from blockchains. However, the existing redactable blockchain scheme has low redacting efficiency, and lacks an accountable and updatable fine-grained mechanism to control redacting rights. To solve the above problems, we propose an efficient and fine-grained redactable blockchain scheme with accountability and updatable policies. In our scheme, the transaction owner can set the updatable policy associated with the transaction, and only users who meet the policy can become the redactor of the transaction. In order to prevent redactors from abusing redacting right, we introduce the concept of a witness group. A redacted transaction is legal if and only if it contains the signatures of redactor and witness group. We first give the concept of witness group, and then show the proposed scheme. Finally, we demonstrate that scheme is feasible and efficient through a series of experiments and analysis.
Despite the success in various scenarios, blockchain systems, especially EVM-compatible ones that serially execute transactions, still face the significant challenge of limited throughput. Concurrent transaction execution is a promising technique to accelerate transaction processing and increase the overall throughput. Existing concurrency control algorithms, however, fail to obtain enough speedups in real-world blockchains due to the high-contention workloads. In this paper, we propose a novel operation-level concurrency control algorithm designed for blockchains. The core idea behind our algorithm is that only operations depending on conflicts should be executed serially, while all other conflict-free operations can be executed concurrently. Therefore, in contrast to the traditional approaches, which block or abort the entire transaction when encountering conflicts, our algorithm introduces a redo phase to resolve conflicts at the operation level by re-executing conflicting operations only. We also develop a set of data dependency tracking mechanisms to achieve precise identification and speedy re-execution for conflicting operations. We implement an open-source prototype based on Go Ethereum and evaluate it using real-world Ethereum blocks. The evaluation results show that our algorithm achieves an average speedup of 4.28$\times$. If combined with state prefetching techniques, our approach can further accelerate the transaction execution by 7.11$\times$.
Proof-of-Work (PoW) consensus mechanism is popular among current blockchain systems, which leads to an increasing concern about the tremendous waste of energy due to massive meaningless computation. To address this issue, we propose a novel and energy-efficient blockchain system, CrowdMine, which exploits useful crowdsourcing computation to achieve decentralized consensus. CrowdMine solves user-proposed computing tasks and utilizes the computation committed to the task solving process to secure decentralized on-chain storage. With our designed ``Proof of Crowdsourcing Work'' (PoCW) protocol, our system provides an efficient paradigm for computation and storage in a trustless and decentralized environment. We further show that the system can defend against potential attacks on blockchain, including the short-term 51\% attack, the problem-constructing attack, and the solution-stealing attack. We also implement the system with 40 distributed nodes to demonstrate its performance and robustness. To the best of our knowledge, this is the first system that enables decentralized Proof of Useful Work (PoUW) with general user-proposed tasks posted in a permissionless and trustless network.
Fail-prone systems, and their quorum systems, are useful tools for the design of distributed algorithms. However, fail-prone systems as studied so far require every process to know the full system membership in order to guarantee safety through globally intersecting quorums. Thus, they are of little help in an open, permissionless setting, where such knowledge may not be available. We propose to generalize the theory of fail-prone systems to make it applicable to permissionless systems. We do so by enabling processes not only to make assumptions about failures, but also to make assumptions about the assumptions of other processes. Thus, by transitivity, processes that do not even know of any common process may nevertheless have intersecting quorums and solve, for example, reliable broadcast. Our model generalizes existing models such as the classic fail-prone system model [Malkhi and Reiter, 1998] and the asymmetric fail-prone system model [Cachin and Tackmann, OPODIS 2019]. Moreover, it gives a characterization with standard formalism of the model used by the Stellar blockchain.
The execution of decentralized applications on blockchains is limited today by technical and organizational barriers, including scalability and the high complexity to specify execution correctly for developers as well as for domain experts in organizations. Overcoming these limitations could allow for decentralized coordination beyond data, where distributed parties rely on higher-level abstractions for coordinating their actions using decentralized applications, not limited to organizations. Towards this goal, the paper at hand proposes executable models as high-level abstraction that can be observed and tracked by distributed parties. In particular, it is investigated how executable models on cloud platforms can be coupled with smart contracts for tracking their execution, concluding with an architecture as exploratory research result towards supporting scalability and decentralized coordination.
Cross-chain swaps enable exchange of different assets that reside on different blockchains. Several protocols have been proposed for atomic cross-chain swaps. However, those protocols are not fault-tolerant, in the sense that if any party deviates, no asset transfer can happen. In this paper, we propose two alternative protocols for structuring composable and robust cross-chain swaps. Participants can propose multiple swaps simultaneously and then complete a subset of those swaps according to their needs. Their needs are expressed as predicates which capture acceptable payoff of each participant. Our proposed protocols are thus more expressive due to the introduction of predicates. The proposed protocols are fault-tolerant since, even if some participants deviate, those predicates can still be satisfied, and conforming parties can complete an acceptable set of swaps.
Sergio Demian Lerner, Federico Jinich, Diego Masini, Shreemoy Mishra
Uncontrolled growth of blockchain state can adversely affect client performance, decentralization and security. Previous attempts to introduce duration-based state storage pricing or 'storage rent' in Ethereum have stalled, partly because of complexity. We present a new approach with finer granularity to "spread" rent payments across peers. Our proposal shifts the burden of state rent from accounts to transaction senders in a quasi-random manner. This proposal offers a simple path for initial adoption on Ethereum Virtual Machine (EVM) compatible chains, and serve as a foundation to address remaining challenges.