Data mesh architecture is revolutionizing the field of data analytics, offering a fresh approach to how organizations manage and utilize data. Traditionally, centralized data warehouses and data lakes have dominated the landscape, but as the volume and complexity of data grow, these systems struggle to keep pace. Data mesh breaks away from the centralized model by promoting a decentralized and domain-oriented approach, where individual teams take ownership of their data. This shift enables organizations to treat data as a product, with each domain team responsible for managing and serving their data assets. The goal is to make data more accessible and usable across the organization while reducing bottlenecks that occur in centralized systems. Implementing data mesh architecture has profound implications for data management. It encourages better data governance, scalability, and flexibility, while fostering innovation and collaboration. However, it also introduces challenges, such as ensuring consistency, standardization, and proper integration across domains. The success of a data mesh strategy depends on a strong cultural shift, requiring both technical infrastructure and organizational alignment to support autonomous teams. Ultimately, data mesh offers the promise of unlocking the full potential of data in large organizations by making it more agile, democratized, and efficient. By embracing this architecture, businesses can better respond to the increasing demands of modern data management and gain a competitive edge in the digital landscape.
With the recent trend on blockchain, many users want to know more about the important players of the chain. In this study, we investigate and analyze the Ethereum blockchain network in order to identify the major entities across the transaction network. By leveraging the rich data available through Alethio's platform in the form of RDF triples we learn about the Hubs and Authorities of the Ethereum transaction network. Alethio uses SANSA for effcient reading and processing of such large-scale RDF data (transactions on Ethereum blockchain) in order to perform analytics e.g. finding top accounts, or typical behavior patterns of exchanges' deposit wallets and more.
Mohammed Almukaynizi, Vivin Paliath, Malay Shah, Malav Shah · 5 authors
With the recent prevalence of darkweb/deepweb (D2web) sites specializing in the trade of exploit kits and malware, malicious actors have easy-access to a wide-range of tools that can empower their offensive capability. In this study, we apply concepts from causal reasoning, itemset mining, and logic programming on historical cryptocurrency-related cyber incidents with intelligence collected from over 400 D2web hacker forums. Our goal was to find indicators of cyber threats targeting cryptocurrency traders and exchange platforms from hacker activity. Our approach found interesting activities that, when observed together in the D2web, subsequent cryptocurrency-related incidents are at least twice as likely to occur than they would if no activity was observed. We also present an algorithmic extension to a previously-introduced algorithm called APT-Extract that allows to model new semantic structures that are specific to our application.
In this paper, we revisit the fundamental question of Bitcoins security against selfish-mine attack introduced by I. Eyal and E. G. Sirer in We study the state machine of Bitcoin's network under the influence of one pool miner adopting the selfish mine strategy while the rest of the community following the standard protocol. We prove that the process following by the states of Bitcoin's system is a irreducible, positive-recurrent, aperiodic, and discrete Markov chain. We give an invariant (stationary) distribution for this Markov chain and deduce easily the rate of convergence towards the stationary equilibrium situation.
We consider natural ways to extend the notion of Zero-Knowledge (ZK) Proofs beyond decision problems. Specifically, we consider search problems, and define zero-knowledge proofs in this context as interactive protocols in which the prover can establish the correctness of a solution to a given instance without the verifier learning anything beyond the intended solution, even if it deviates from the protocol. The goal of this work is to initiate a study of Search Zero-Knowledge (search-ZK), the class of search problems for which such systems exist. This class trivially contains search problems where the validity of a solution can be efficiently verified (using a single message proof containing only the solution). A slightly less obvious, but still straightforward, way to obtain zero-knowledge proofs for search problems is to let the prover send a solution and prove in zero-knowledge that the instance-solution pair is valid. However, there may be other ways to obtain such zero-knowledge proofs, and they may be more advantageous. In fact, we prove that there are search problems for which the aforementioned approach fails, but still search zero-knowledge protocols exist. On the other hand, we show sufficient conditions for search problems under which some form of zero-knowledge can be obtained using the straightforward way.
Elvira Albert, Pablo Gordillo, Benjamin Livshits, Albert Rubio · 5 authors
Analyzing Ethereum bytecode, rather than the source code from which it was generated, is a necessity when: (1) the source code is not available (e.g., the blockchain only stores the bytecode), (2) the information to be gathered in the analysis is only visible at the level of bytecode (e.g., gas consumption is specified at the level of EVM instructions), (3) the analysis results may be affected by optimizations performed by the compiler (thus the analysis should be done ideally after compilation). This paper presents EthIR, a framework for analyzing Ethereum bytecode, which relies on (an extension of) OYENTE, a tool that generates CFGs; EthIR produces from the CFGs, a rule-based representation (RBR) of the bytecode that enables the application of (existing) high-level analyses to infer properties of EVM code.
Searching for information in distributed ledgers is currently not an easy task, as information relating to an entity may be scattered throughout the ledger with no index. As distributed ledger technologies become more established, they will increasingly be used to represent real world transactions involving many parties and the search requirements will grow. An index providing the ability to search using domain specific terms across multiple ledgers will greatly enhance to power, usability and scope of these systems.
Bitcoin is a rising digital currency and exemplifies the grow- ing need for systematically gathering and analyzing pub- lic transaction data sets such as the blockchain. However, the blockchain in its raw form is just a large ledger listing transfers of currency units between alphanumeric character strings, without revealing contextually relevant real-world information. In this demo, we present GraphSense, which is a solution that applies a graph-centric perspective on digital currency transactions. It allows users to explore transactions and follow the money ow, facilitates analytics by semantically enriching the transaction graph, supports path and graph pattern search, and guides analysts to anomalous data points. To deal with the growing volume and velocity of transaction data, we implemented our solution on a horizontally scalable data processing and analytics infrastructure. Given the ongoing digital transformation in financial services and technologies, we believe that our approach contributes to development of analytics solutions for digital currency ecosystems, which is relevant in fields such as financial analytics, law enforcement, or scientific research
For the past five years, the bitcoin network constantly experience a growth in its size as more communities turn to accept the currency for payment exchanges. Using Flat File and a LevelDB of indices to save blocks on disk, bitcoin users require more memory to save the history of transaction. We focus on issues of memory management and access time in the bitcoin protocol using SQLite DataBase. With all the advantages of SQLite DataBase, it would be efficient if it is fitted in this architecture. The SQLite comes with many flavors one of which is its ability to support sql queries. Thus, instead of parsing indices to search a block from the database, a more powerful query can do the job.
Narendra Kunapareddy, Parsa Mirhaji, David Richards, S. Ward Casscells
Although the decentralized and autonomous implementation of health information systems has made it possible to extend the reach of surveillance systems to a variety of contextually disparate domains, public health use of data from these systems is not primarily anticipated. The Semantic Web has been proposed to address both representational and semantic heterogeneity in distributed and collaborative environments. We introduce a semantic approach for the integration of health data using the Resource Definition Framework (RDF) and the Simple Knowledge Organization System (SKOS) developed by the Semantic Web community.
Summary A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
A proof is whatever convinces me. Shimon Even (1935–2004) The glory attached to the creativity involved in finding proofs makes us forget that it is the less glorified process of verification that gives proofs their value. Conceptually speaking, proofs are secondary to the verification process, whereas technically speaking, proof systems are defined in terms of their verification procedures. The notion of a verification procedure presumes the notion of computation and furthermore the notion of efficient computation. This implicit stipulation is made explicit in the definition of NP , where efficient computation is associated with deterministic polynomial-time algorithms. However, as argued next, we can gain a lot if we are willing to take a somewhat non-traditional step and allow probabilistic verification procedures. In this chapter, we shall study three types of probabilistic proof systems, called interactive proofs, zero-knowledge proofs , and probabilistic checkable proofs . In each of these three cases, we shall present fascinating results that cannot be obtained when considering the analogous deterministic proof systems. Summary: The association of efficient procedures with deterministic polynomial-time procedures is the basis for viewing NP-proof systems as the canonical formulation of proof systems (with efficient verification procedures). Allowing probabilistic verification procedures and, moreover, ruling by statistical evidence gives rise to various types of probabilistic proof systems. Indeed, these probabilistic proof systems carry a probability of error (which is explicitly bounded and can be reduced by successive applications of the proof system), yet they offer various advantages over the traditional (deterministic and errorless) proof systems. […]