Efficient Data and Indexing Structure for Blockchains in Enterprise Systems

Purpose Integrating Internet of Things (IoT) networks with distributed ledger technology (DLT) and artificial intelligence (AI) presents critical challenges, particularly related to latency, scalability, hardware constraints and data security. Efficient data ingestion and validation are essential to enable real-time AI processing. The main contribution of this paper is the proposal of the Energy consensus algorithm, designed to minimize both latency and energy consumption in such environments. Design/methodology/approach Energy is a consensus algorithm tailored for public directed acyclic graph-based DLTs in IoT contexts. It introduces a flexible transaction validation mechanism that reduces or bypasses Proof of Work requirements. The algorithm’s performance is experimentally compared with IOTA under varying payload conditions. Findings Results show that Energy significantly reduces latency and energy consumption, especially for small payloads, which are common in IoT applications. These findings demonstrate Energy’s ability to enhance transaction efficiency and support real-time AI model updates based on verified IoT data streams. Research limitations/implications Future work should investigate the scalability of Energy in larger and more heterogeneous IoT ecosystems, as well as its compatibility with different AI frameworks. Evaluating its performance under diverse network conditions and hardware setups would further strengthen the generalizability of the results. Practical implications The Energy algorithm enables continuous AI model updates while ensuring data integrity, traceability and low latency. Its adaptability makes it a suitable solution for large-scale IoT deployments requiring secure and efficient data processing. Originality/value This paper presents a novel consensus algorithm that bridges the requirements of IoT, DLT and AI, with a particular focus on improving latency and energy efficiency. Energy offers a robust approach for optimizing data flow and transaction processing in real-time, AI-driven IoT systems.

Log-structured merge-trees (LSM-trees) are widely used in key-value stores because of its excellent write performance. To reduce LSM-tree's read amplification due to overlapping sorted runs, each file (i.e., SSTable) in an LSM-tree is typically associated with a point or range filter to reduce unnecessary I/Os to the runs that do not contain the target key (range). However, as modern SSDs get faster, probing multiple in-memory filters per query often makes the system CPU bottlenecked, thus compromising the system's throughput. In this paper, we developed the Global Range Filter (GRF) for RocksDB that reduces the number of filter probes per query to one. We follow the pioneering Chucky's approach by storing the sorted run IDs within the filter. However, we identify two practical challenges in building a global range filter: correctness in multi-version concurrency control and efficiency in frequent updates. We solve both challenges by the novel Shape Encoding algorithm. With further optimizations, GRF achieves a dominating performance over the state-of-the-art filters under different workloads when integrated into RocksDB.

Scalable Blockchain Architecture using off-chain IPFS for Marks Card Validation

Database Management Systems (DBMS) need to handle large updatable datasets in on-line transaction processing (OLTP) workloads. Most modern DBMS provide snapshots of data in multi-version concurrency control (MVCC) transaction management scheme. Each transaction operates on a snapshot of the database, which is calculated from a set of tuple versions. High parallelism and resource-efficient append-only data placement on secondary storage is enabled. One major issue in indexing tuple versions on modern hardware technologies is the high write amplification for tree-indexes.

Sovereign Distributed Ledgers (SDL): Concept and Analysis

Since 1990, transaction processing in multilevel secure database management systems (DBMSs) has been receiving a great deal of attention from the database research community. Transaction processing in these systems requires modification of conventional scheduling algorithms and commit protocols. These modifications are necessary because preserving the usual transaction properties when transactions are executing at different security levels often conflicts with the enforcement of the security policy. Considerable effort has been devoted to the development of efficient, secure algorithms for the major types of secure DBMS architectures: kernelized, replicated, and distributed. An additional problem that arises uniquely in multilevel secure DBMSs is that of secure, correct execution when data at multiple security levels must be written within one transaction. Significant progress has been made in a number of these areas, and a few of the techniques have been incorporated into commercial trusted DBMS products. However, there are many open problems remain to be explored. This paper reviews the achievements to date in transaction processing for multilevel secure DBMSs. The paper provides an overview of transaction processing needs and solutions in conventional DBMSs as background, explains the constraints introduced by multilevel security, and then describes the results of research in multilevel secure transaction processing. Research results and limitations in concurrency control, multilevel transaction management, and secure commit protocols are summarized. Finally, important new areas are identified for secure transaction processing research.

EVMCSDLT: Electric vehicle mobile charging system using distributed ledger technology.

Blockchain is undoubtedly one of the most potentially attractive technologies for the organization of financial services. The significance of the Blockchain technology in a banking system can be determined by three main principles that is; Disintermediation, Transparency and Provenance. The DLT (distributed ledger technology) eliminates the need for trust enforcer in the banking management system. This is made possible by the tamper- proof data in the distributed data records and all the participants in the network have the same version of data record with them at all times and it is unalterable. Blockchain promotes a public database record of all the customer transactions and other data, ensuring a transparent and trustworthy system as the customers have a 24x7 real-time access to it. Blockchain keeps an immutable distributed data ledger of transactions and this result in maintaining a lifecycle of the assets and its ownership from its first transaction to the most recent one. It reduces the chances of occurrence of theft, insurance fraud and misselling of the high valued assets or intellectual properties. Blockchain can be implemented in the banking sector for various applications like maintenance of data confidentiality, cheque clearing system, real time money transfer system (digital currency), supply chain finance, insurance, trade finance, KYC (know your customer), cross-border payments/transactions system, monitoring of consortium accounts, auction system and digital asset management. Blockchain technology can hence enable a decentralized solution for the banking ecosystem. The proposed system enables one platform for both the lenders and the borrowers to initiate their money transaction for lending, borrowing and repayment of the loan money. The transactions made throughout, that is, from the start to the last repayment can be viewed easily on a blockchain network thus increasing the transparency and trust of the customers and it resolves any disputes that can arise in the loan system. Along with this, a KYC registry based on blockchain is also proposed which will help in maintaining the KYC details in one platform which can be accessed by various banks for identification and verification of the customer in an easy and faster manner. It will increase the customer satisfaction as there will be no need for the customer to perform a KYC check every time he/she creates a bank account in any bank as the bank can easily access their KYC details from this system.

Blockchain network (BCN)-based Self-Sovereign Identity (SSI) has emerged lately as an identity and access management framework that is based on Distributed Ledger Technology (DLT) and allows users to control their own data. Federated Learning (FL), on the other hand, provides a collaborative framework to update Machine Learning (ML) models without relying explicitly on data exchange between the users. This paper investigates identity management and authentication for vehicle users in the context of FL. We propose a novel approach based on blockchain-based SSI, which focuses on maintaining the authenticity and integrity of vehicle users’ identities and data exchanged between the users and the aggregation server during the execution of the FL iterations. A primary objective of this paper is to achieve shorter durations for credential operations in an FL setting as the system size scales out. Integrating BCN-based SSI into the FL framework addresses several critical FL challenges, ensuring enhanced system security and operational integrity. This synergy of BCN-based SSI with federated learning enables robust identity verification providing a solution to fundamental trustworthiness issues in FL without sacrificing the benefits of decentralized data control, improving both the performance and reliability of the FL system. Experimental results suggest that the proposed FL-based system, together with credential management on a blockchain platform, has the potential to significantly improve data integrity and ensure the authentication of users. More specifically, the results of the FL system demonstrate that it takes longer (on the order of a hundred seconds) as the number of rounds and clients increase, while the implemented Decentralized Identifier (DID) system relying on BCN-based SSI has dramatically shorter dedicated time for completing credential operations.

Blockchain is a decentralized, distributed ledger technology that securely records transactions across multiple nodes, ensuring transparency and immutability. It has the potential to significantly reduce costs and time while minimizing risks across various applications. This study presents an AI-enhanced approach to strengthen blockchain security, with a focus on transaction monitoring and anomaly detection. Challenges in transactions include fraudulent activities, double-spending, and unauthorized access, while anomalies often signify errors, potential hacking attempts, or irregular patterns that may undermine the integrity and trust of blockchain systems. By implementing a self-triggering mechanism that utilizes AI-computed features, the system monitors transactional behaviour in real-time to detect and mitigate potential cyber-attacks. Using Isolation Forest algorithm for anomaly detection, the system effectively tracked and identified unusual patterns within a five-node star topology blockchain network. Upon detecting anomalies, the system autonomously removes compromised nodes to prevent further damage and maintain operational integrity. Simulated results show that the system effectively identified compromised nodes without disrupting business transactions, maintaining an average transaction amount of 27.50 units across six transactions. Using AI with blockchain offers a scalable solution that enhances both the security and efficiency of blockchain networks compared to traditional, rule-based or manual approaches.

The article is devoted to the consideration of current trends and development vectors of the payment space in the global aspect and the state of payment systems’ development of in Ukraine. Acceleration of the role of non-cash circulation in society and growth of the role of payments makes the payment systems’ development a dominant feature of economic growth, innovation and integration. A specialised element of almost all economic transactions that take place in the market economy, which concerns the transfer of monetary value in exchange for some goods, services or financial assets, is one of the approaches to the definition of the payment system in which it is necessary to add the payment infrastructure. The latter ensures smooth, reliable, prompt and efficient payment transfers. The last mentioned exactly that aspect that has now fuelled the growth of payment services’ digitalisation. Given the vectors of development of the payment industry, the payment systems can become a leader, in the sphere of financial services. Having considered the main directions of development in the international economy, we have highlighted the trend of globalisation of national payment systems into a common world payment space. However, this process is complex and requires working out many differences between different national payment systems and co-operation of states, regulators, enterprises and population (consumers). This approach to the development of payment systems promotes economic growth and job creation. However, the creation of a global world space is a complex task, which begins with the development and improvement of national payment systems to adapt to further integration into the global payment space. It is mentioned that there is a restructuring of the payment space, including the evolution of payment instruments (instant payments, payment cards, e-wallets, etc.) and revolutionary structural changes in the combination of classical payment technologies and technological innovations (cryptocurrencies, development of national e-money, distributed ledger technologies, blockchain networks that offer interoperability solutions, etc. The results of the analysis of existing trends, summarised by the above-mentioned scientists and experts, determine further directions for transforming the domestic payment space.

The blockchain technology attracted great scientific and applied interest in the last six–seven years. It successfully applies in different areas like fintech, smart cities, IoT, health care, banking, retail, oil industries, and many others. Regardless of the blockchain type (permissioned or permissionless), the data that must be stored in the blockchain network. The algorithm, which is used to “decide” whether to approve (confirm) or not storing the data in the network is the consensus algorithm. It is very important component of the proper blockchain functioning. The author is pursuing two goals with this research. The first one is to make a thorough retrieval of articles from different publishers, based on few keywords, and check if there are any specific trends of research interests in the recent years around these keywords. The second goal is to identify some classifications criteria—like types (public, private, hybrid, and federated), like layers (two layers and multi-layer), etc., and finally, to classify the existing Distributed Ledger Technology (DLT) consensus algorithms with focus on blockchain, based on the architecture and on the access type.KeywordsBlockchainDLTConsensus algorithmsPermissionedPermissionlessHybridFederatedPrivate sectorPublic sectorProof-basedVoting-based

A transaction processing (TP) application is a program that performs an administrative function by accessing a shared database on behalf of an on-line user. A TP system is an integrated set of products that supports TP applications. These products include both hardware, such as processors, memories, disks and communications controllers, and software such as operating systems (Oss), database management systems (DBMSs), computer networks and TP monitors. Much of the integration of these products is provided by TP monitors which coordinate the flow of transaction request between terminals that issue requests and TP applications that can process them. Today, TP represents over 25 percent of the computer systems market and is one of the growing segments of the computer business. TP applications appear in most sectors of large-scale enterprises such as airline reservation, electronic banking, securities trading, inventory and production control, communications switching, videotex, sales management, military command and control and government services.

Blockchain technology garners significant attention and recognition due to several key advantages it offers. Trust, reliability, speed, and transparency are among the prominent benefits that contribute to its growing prominence. The decentralized nature of blockchain allows for a high level of trust as transactions are recorded and verified by multiple participants across the network. This, in turn, enhances reliability as there is no single point of failure. Speed is also a notable advantage, particularly when compared to traditional systems that involve intermediaries and complex processes for verification. Blockchain enables faster and more efficient transaction processing, reducing delays and costs. This research paper aims to provide a comprehensive comparative analysis of two prominent distributed ledger technologies, namely blockchain and hashgraph. Both blockchain and hashgraph offer decentralized and secure systems for recording and validating transactions or information. It explores the underlying mechanisms, consensus algorithms, advantages, and limitations of these technologies. It also examines their potential applications and discusses the implications of their respective design choices. By understanding the nuances of blockchain and hashgraph, seeks to contribute to the ongoing discourse on distributed ledger technologies and aids in decision-making for their appropriate adoption in various domains and applications.

A database is a collection of information, such as facts about countries, statistics on demographics, a store’s inventory, and phone lists. A database system allows one to access, insert, delete, and modify information stored within a computer system. The term computer system is used as opposed to computer because external memory may be needed. Database systems often require large amounts of memory that greatly exceed the storage capacities of the computer’s main memory. The database management system (DBMS) performs operations on the information stored within a database. The DBMS is a program that contains a query language that allows database updates and retrievals. A DBMS can be viewed as a layer or abstraction built upon the computer system.