Distributed ledgers are a new type of database technology that allows open access to data stored across distributed, decentralised, publicly maintained infrastructures. Current implementations of the such ledgers expect competition between participants, are often energy hungry, poor in maintaining the natural structure of data and suffer from scalability constraints. The aim of my research work is to develop a distributed ledger-based middleware for data modelling and collection on household energy generation and use, while addressing scalability and energy inefficiency concerns of the ledger for this particular application domain. The energy data collected and made available through this middleware will be used for digital energy service delivery (e.g., automated peer to peer energy trading, topological estimations, etc.). The middleware also provides a platform for a consumer focused digital energy service delivery, as well as service model evaluation. The model evaluation will enable the prospective service users to evaluate the suitability of the given service for their needs before making a decision of service subscription.
Roberta Galici, Laura Ordile, Michele Marchesi, Andrea Pinna · 5 authors
We present a novel strategy, based on the Extract, Transform and Load (ETL) process, to collect data from a blockchain, elaborate and make it available for further analysis. The study aims to satisfy the need for increasingly efficient data extraction strategies and effective representation methods for blockchain data. For this reason, we conceived a system to make scalable the process of blockchain data extraction and clustering, and to provide a SQL database which preserves the distinction between transaction and addresses. The proposed system satisfies the need to cluster addresses in entities, and the need to store the extracted data in a conventional database, making possible the data analysis by querying the database. In general, ETL processes allow the automation of the operation of data selection, data collection and data conditioning from a data warehouse, and produce output data in the best format for subsequent processing or for business. We focus on the Bitcoin blockchain transactions, which we organized in a relational database to distinguish between the input section and the output section of each transaction. We describe the implementation of address clustering algorithms specific for the Bitcoin blockchain and the process to collect and transform data and to load them in the database. To balance the input data rate with the elaboration time, we manage blockchain data according to the lambda architecture. To evaluate our process, we first analyzed the performances in terms of scalability, and then we checked its usability by analyzing loaded data. Finally, we present the results of a toy analysis, which provides some findings about blockchain data, focusing on a comparison between the statistics of the last year of transactions, and previous results of historical blockchain data found in the literature. The ETL process we realized to analyze blockchain data is proven to be able to perform a reliable and scalable data acquisition process, whose result makes stored data available for further analysis and business.
Jean-Marc Seigneur, Sophie Pusterla, Xavier Socquet-Clerc
Relational capital for companies has been theorized and modeled in the past, but so far, no real Web application has tried to bring its value to light, especially concerning the real estate application domain. In this paper, we present the results of our surveys on how the types of relations who have contributed to a product impact price premium and what real estate agencies think about real estate relational value, especially as implemented on our Web marketplace connected to Facebook social network and NEO public blockchain for products certifications transparency.
Scalability has been a bottleneck for major blockchains such as Bitcoin and Ethereum. Despite the significantly improved scalability claimed by several high-profile blockchain projects, there has been little effort to understand how their transactional throughput is being used. In this paper, we examine recent network traffic of three major high-scalability blockchains---EOSIO, Tezos and XRP Ledger (XRPL)---over a period of seven months. Our analysis reveals that only a small fraction of the transactions are used for value transfer purposes. In particular, 96% of the transactions on EOSIO were triggered by the airdrop of a currently valueless token; on Tezos, 76% of throughput was used for maintaining consensus; and over 94% of transactions on XRPL carried no economic value. We also identify a persisting airdrop on EOSIO as a DoS attack and detect a two-month-long spam attack on XRPL. The paper explores the different designs of the three blockchains and sheds light on how they could shape user behavior.
The blockchain paradigm provides a mechanism for content dissemination and distributed consensus on Peer-to-Peer (P2P) networks. While this paradigm has been widely adopted in industry, it has not been carefully analyzed in terms of its network scaling with respect to the number of peers. Applications for blockchain systems, such as cryptocurrencies and IoT, require this form of network scaling. In this paper, we propose a new stochastic network model for a blockchain system. We identify a structural property called \emph{one-endedness}, which we show to be desirable in any blockchain system as it is directly related to distributed consensus among the peers. We show that the stochastic stability of the network is sufficient for the one-endedness of a blockchain. We further establish that our model belongs to a class of network models, called monotone separable models. This allows us to establish upper and lower bounds on the stability region. The bounds on stability depend on the connectivity of the P2P network through its conductance and allow us to analyze the scalability of blockchain systems on large P2P networks. We verify our theoretical insights using both synthetic data and real data from the Bitcoin network.
As eBook readers have expanded on the market, various online eBook markets have arisen as well. Currently, the online eBook market consists of at least publishers and online platform providers and authors, and these actors inevitably incur intermediate costs between them. In this paper, we introduce a blockchain-based eBook market system that enables self-published eBook trading and direct payments from readers to authors without any trusted party; because authors publish themselves and readers purchase directly from authors, neither actor incurs any intermediate costs. However, because of this trustless environment, the validity, ownership and intellectual property of digital contents cannot be verified and protected, and the safety of purchase transactions cannot be ensured. To address these shortcomings, we propose a secure and reliable eBook transaction system that satisfies the following security requirements: (1) verification of the ownership of each eBook, (2) confidentiality of eBook contents, (3) authorization of a right to read a book, (4) authentication of a legitimate purchaser, (5) verification of the validity and integrity of eBook contents, (6) safety of direct purchase transactions, and (7) preventing eBook piracy and illegal distribution. We provide practical cryptographic protocols for the proposed system and analyze the security and simulated performance of the proposed schemes.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Suyash Gupta, Sajjad Rahnama, Jelle Hellings, Mohammad Sadoghi
Recent developments in blockchain technology have inspired innovative new designs in resilient distributed and database systems. At their core, these blockchain applications typically use Byzantine fault-tolerant consensus protocols to maintain a common state across all replicas, even if some replicas are faulty or malicious. Unfortunately, existing consensus protocols are not designed to deal with geo-scale deployments in which many replicas spread across a geographically large area participate in consensus. To address this, we present the Geo-Scale Byzantine FaultTolerant consensus protocol (GeoBFT). GeoBFT is designed for excellent scalability by using a topological-aware grouping of replicas in local clusters, by introducing parallelization of consensus at the local level, and by minimizing communication between clusters. To validate our vision of high-performance geo-scale resilient distributed systems, we implement GeoBFT in our efficient ResilientDB permissioned blockchain fabric. We show that GeoBFT is not only sound and provides great scalability, but also outperforms state-of-the-art consensus protocols by a factor of six in geo-scale deployments.
Sami Ben Mariem, Pedro Casas, Matteo Romiti, Benoît Donnet · 6 authors
Blockchains are typically managed by peer-to-peer (P2P) networks providing the support and substrate to the so-called distributed ledger (DLT), a replicated, shared, and synchronized data structure, geographically spread across multiple nodes. The Bitcoin (BTC) blockchain is by far the most well known DLT, used to record transactions among peers, based on the BTC digital currency. In this paper, we focus on the network side of the BTC P2P network, analyzing its nodes from a purely network measurements-based approach. We present a BTC crawler able to discover and track the BTC P2P network through active measurements, and use it to analyze its main properties. Through the combined analysis of multiple snapshots of the BTC network as well as by using other publicly available data sources on the BTC network and DLT, we unveil the BTC P2P network, locate its active nodes, study their performance, and track the evolution of the network over the past two years. Among other relevant findings, we show that (i) the size of the BTC network has remained almost constant during the last 12 months - since the major BTC price drop in early 2018, (ii) most of the BTC P2P network resides in US and EU countries, and (iii) despite this western network locality, most of the mining activity and corresponding revenue is controlled by major mining pools located in China. By additionally analyzing the distribution of BTC coins among independent BTC entities (i.e., single BTC addresses or groups of BTC addresses controlled by the same actor), we also conclude that (iv) BTC is very far from being the decentralized and uncontrolled system it is so much advertised to be, with only 4.5% of all the BTC entities holding about 85% of all circulating BTC coins.
Traditional public distributed ledgers have not been able to scale-out well and work efficiently. Sharding is deemed as a promising way to solve this problem. By partitioning all nodes into small committees and letting them work in parallel, we can significantly lower the amount of communication and computation, reduce the overhead on each node's storage, as well as enhance the throughput of the distributed ledger. Existing sharding-based protocols still suffer from several serious drawbacks. The first thing is that all non-faulty nodes must connect well with each other, which demands a huge number of communication channels in the network. Moreover, previous protocols have faced great loss in efficiency in the case where the honesty of each committee's leader is in question. At the same time, no explicit incentive is provided for nodes to actively participate in the protocol. We present CycLedger, a scalable and secure parallel protocol for distributed ledger via sharding. Our protocol selects a leader and a partial set for each committee, who are in charge of maintaining intra-shard consensus and communicating with other committees, to reduce the amortized complexity of communication, computation, and storage on all nodes. We introduce a novel semi-commitment scheme between committees and a recovery procedure to prevent the system from crashing even when leaders of committees are malicious. To add incentive for the network, we use the concept of reputation, which measures each node's trusty computing power. As nodes with a higher reputation receive more rewards, there is an encouragement for nodes with strong computing ability to work honestly to gain reputation. In this way, we strike out a new path to establish scalability, security, and incentive for the sharding-based distributed ledger.
The Lightning Network (LN) was released on Bitcoin's mainnet in January 2018 as a solution to favor scalability. This work analyses the evolution of the LN during its first year of existence in order to assess its impact over some of the core fundamentals of Bitcoin, such as: node centralization, resilience against attacks and disruptions, anonymity of users, autonomous coordination of its members. Using a network theory approach, we find that the LN represents a centralized configuration with few highly active nodes playing as hubs in that system. We show that the removal of these central nodes is likely to generate a remarkable drop in the LN's efficiency, while the network appears robust to random disruptions. In addition, we observe that improvements in efficiency during the sample period are primarily due to the increase in the capacity installed on the channels, while nodes' synchronization does not emerge as a distinctive feature of the LN. Finally, the analysis of the structure of the network suggests a good preservation of nodes' identity against attackers with prior knowledge about topological characteristics of their targets, but also that LN is probably weak against attackers that are within the system.
Bin Qu, Li-e Wang, Peng Liu, Zhenkui Shi · 5 authors
To achieve the tamper-proof, reliability and traceability of transactions in a trustless environment, the blockchain requires each peer node to store the whole global ledger. However, as transactions keep increasing over time, the storage cost of each node increases. In addition, many schemes have been proposed to boost rapid transactions which will even lead transactions to grow explosively. The problem of storage is becoming one challenge of blockchain since the storage overhead of each node increase rapidly. Reducing the storage overhead of each participant is very urgent and worthy. In this paper, we present GCBlock: a grouping overlay network storage scheme for the blockchain which can reduce the storage overhead of nodes and cut the whole storage cost of the blockchain greatly while keeping the underlying protocols. In our scheme, we try to group the nodes according to their physical fuzzy distance to reduce the overall delay when tracing. We set rules of autonomous check to deal with evil behavior within the group. To further enhance the stability of our scheme, we propose the transcript fractional repetition code which is newly constructed based on the fractional repetition code to encode data. Finally, we make a comprehensive evaluation of GCBlock and the results show that it is workable and reasonable.
E-voting is the process of conducting the voting process through online. The voters can cast their votes from different locations and these votes are collected and recorded electronically. Therefore, there is a need for a system to provide control and security to the whole procedure. Blockchain, a distributed ledger technology can be integrated to provide a decentralized system. Blockchain uses distributed ledger technology (DLT) to avoid forged voting option & non-repudiation and one time login of the user is also ensured. By integrating the above techniques, a secure user authentication for e-voting supported blockchain in p2p network is projected. This system would increase the safety by avoiding the forgery of votes. Similarly, the blockchain are often integrated to a spread of voting situations and a few alternative applications.
Open access
2 source records
Blockchain Technology Applications and Security
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
Gianmaria Del Monte, Diego Pennino, Maurizio Pizzonia
Public blockchains should be able to scale with respect to the number of nodes and to the transactions workload. The blockchain scalability trilemma has been informally conjectured. This is related to scalability, security and decentralization, stating that any improvement in one of these aspects should negatively impact on at least one of the other two. In fact, despite the large research and experimental effort, all known approaches turn out to be tradeoffs. We theoretically describe a new blockchain architecture that scales to arbitrarily high workload provided that a corresponding proportional increment of nodes is provisioned. We show that, under reasonable assumptions, our approach does not require tradeoffs on security or decentralization. To the best of our knowledge, this is the first result that disprove the trilemma considering the scalability of all architectural elements of a blockchain and not only the consensus protocol. While our result is currently only theoretic, we believe that our approach may stimulate significant practical contributions.
Distributed ledger technology is envisioned as one of the cornerstones of promising solutions for building the next generation of critical applications.However, there is still quite a bit of confusion and hype around the real security guarantees this technology offers.This is especially due to the fact that for the vast majority of existing blockchain-based consensus protocols it is really hard to find sufficiently detailed documentation that fully captures their behavior.A number of recent papers have formalized the behavior of Bitcoin-like protocols in order to rigorously study the security and privacy properties of their underlying structure, but surprisingly very little work has been devoted to the formalization of distributed ledger systems using BFTlike approaches.In this work, we focus on XRP Ledger, better known as Ripple, and take the first steps towards the complete formalization of its consensus protocol.To this end, we have investigated all the existing documentation and analyzed its source code.We present a formal description of its consensus protocol for every step.Furthermore, we provide an accurate view of its security guarantees in terms of safety and liveness and show how to increase the desired tolerance by changing the value of specific protocol parameters.
With the emergence of decentralized cryptocurrencies such as Bitcoin, it has become very difficult for law enforcement to detect suspicious activities, identify users and obtain transaction records for criminals who utilize the pseudoanonymity provided by the cryptocurrency system. Address clustering aims to break such pseudoanonymity by linking addresses that are controlled by the same user based on the information available from the blockchain, such as transaction graphs. There are already two widely used heuristics for Bitcoin address clustering. One is based on the multiple input addresses of transactions. The other is based on one-time change addresses. By reconsidering the one-time change address-based heuristic from the perspective of address reuse, we propose a new heuristic that detects one-time change addresses by eliminating addresses that are reused later as non-change addresses. As a result, this heuristic works for transactions whose one-time change addresses cannot be identified by the previous two heuristics. The experimental results for different scales of Bitcoin transaction data show that the proposed heuristic has a 0.33% mean contribution to the ratio of address reduction in addition to the contribution of the multiple input addresses and one-time change address heuristics.
This paper describes a simulation study on security attacks over Distributed Ledger Technologies (DLTs). We specifically focus on attacks at the underlying peer-to-peer layer of these systems, that is in charge of disseminating messages containing data and transaction to be spread among all participants. In particular, we consider the Sybil attack, according to which a malicious node creates many Sybils that drop messages coming from a specific attacked node, or even all messages from honest nodes. Our study shows that the selection of the specific dissemination protocol, as well as the amount of connections each peer has, have an influence on the resistance to this attack.
Muhammad Anas Imtiaz, David Starobinski, Ari Trachtenberg
Orphan transactions are those whose parental income-sources are missing at the time that they are processed. These transactions are not propagated to other nodes until all of their missing parents are received, and they thus end up languishing in a local buffer until evicted or their parents are found. Although there has been little work in the literature on characterizing the nature and impact of such orphans, it is intuitive that they may affect throughput on the Bitcoin network. This work thus seeks to methodically research such effects through a measurement campaign of orphan transactions on live Bitcoin nodes. Our data show that, surprisingly, orphan transactions tend to have fewer parents on average than non-orphan transactions. Moreover, the salient features of their missing parents are a lower fee and larger size than their non-orphan counterparts, resulting in a lower transaction fee per byte. Finally, we note that the network overhead incurred by these orphan transactions can be significant, exceeding 17% when using the default orphan memory pool size (100 transactions). However, this overhead can be made negligible, without significant computational or memory demands, if the pool size is merely increased to 1000 transactions.
Consensus mechanism is the heart of any blockchain network. Many projects have proposed alternative protocols to improve restricted scalability of Proof of Work originated since Bitcoin. As an improvement of Delegated Proof of Stake, in this paper, we introduce a novel consensus, namely, Delegated Proof of Reputation, which is scalable, secure with an acceptable decentralization. Our innovative idea is replacing pure coinstaking by a reputation ranking system essentially based on ranking theories (PageRank, NCDawareRank and HodgeRank).
Vero Estrada-Galiñanes, Racin Nygaard, Viktor Trón, Rodrigo Q. Saramago · 6 authors
Blockchain is the driving force behind a myriad of decentralized applications (dapps) that promise to transform the Internet. The next generation Internet, or web3, introduces a "universal state layer" to store data in p2p networks. Swarm, a native layer of the Ethereum web3 stack, aims at providing redundant storage for dapp code, data, as well as, blockchain and state data. Based on a diploma verification dapp use case, we share insights on the role of redundancy strategies in designing a reliable storage layer. Our proof-of-concept improves Swarm's resilience to failures by balancing repairs and storage, with a slightly added latency.