8,375 research outputs found

    Exploring Blockchain Data Analysis and Its Communications Architecture: Achievements, Challenges, and Future Directions: A Review Article

    Get PDF
    Blockchain technology is relatively young but has the potential to disrupt several industries. Since the emergence of Bitcoin, also known as Blockchain 1.0, there has been significant interest in this technology. The introduction of Ethereum, or Blockchain 2.0, has expanded the types of data that can be stored on blockchain networks. The increasing popularity of blockchain technology has given rise to new challenges, such as user privacy and illicit financial activities, but has also facilitated technical advancements. Blockchain technology utilizes cryptographic hashes of user input to record transactions. The public availability of blockchain data presents a unique opportunity for academics to analyze it and gain a better understanding of the challenges in blockchain communications. Researchers have never had access to such an opportunity before. Therefore, it is crucial to highlight the research problems, accomplishments, and potential trends and challenges in blockchain network data analysis and communications. This article aims to examine and summarize the field of blockchain data analysis and communications. The review encompasses the fundamental data types, analytical techniques, architecture, and operations related to blockchain networks. Seven research challenges are addressed: entity recognition, privacy, risk analysis, network visualization, network structure, market impact, and transaction pattern recognition. The latter half of this section discusses future research directions, opportunities, and challenges based on previous research limitations

    A Survey on Wireless Sensor Network Security

    Full text link
    Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Due to distributed nature of these networks and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. This problem is more critical if the network is deployed for some mission-critical applications such as in a tactical battlefield. Random failure of nodes is also very likely in real-life deployment scenarios. Due to resource constraints in the sensor nodes, traditional security mechanisms with large overhead of computation and communication are infeasible in WSNs. Security in sensor networks is, therefore, a particularly challenging task. This paper discusses the current state of the art in security mechanisms for WSNs. Various types of attacks are discussed and their countermeasures presented. A brief discussion on the future direction of research in WSN security is also included.Comment: 24 pages, 4 figures, 2 table

    An Empirical Analysis of Privacy in Cryptocurrencies

    Get PDF
    Cryptocurrencies have emerged as an important technology over the past decade and have, undoubtedly, become blockchain’s most popular application. Bitcoin has been by far the most popular out of the thousands of cryptocurrencies that have been created. Some of the features that made Bitcoin such a fascinating technology include its transactions being made publicly available and permanently stored, and the ability for anyone to have access. Despite this transparency, it was initially believed that Bitcoin provides anonymity to its users, since it allowed them to transact using a pseudonym instead of their real identity. However, a long line of research has shown that this initial belief was false and that, given the appropriate tools, Bitcoin transactions can indeed be traced back to the real-life entities performing them. In this thesis, we perform a survey to examine the anonymity aspect of cryptocurrencies. We start with early works that made first efforts on analysing how private this new technology was. We analyse both from the perspective of a passive observer with eyes only to the public immutable state of transactions, the blockchain, as well as from an observer who has access to network layer information. We then look into the projects that aimed to enhance the anonymity provided in cryptocurrencies and also analyse the evidence of how much they succeeded in practice. In the first part of our own contributions we present our own take on Bitcoin’s anonymity, inspired by the research already in place. We manage to extend existing heuristics and provide a novel methodology on measuring the confidence we have in our anonymity metrics, instead of looking into the issue from a binary perspective, as in previous research. In the second part we provide the first full-scale empirical work on measuring anonymity in a cryptocurrency that was built with privacy guarantees, based on a very well established cryptography, Zcash. We show that just building a tool which provides anonymity in theory is very different than the privacy offered in practice once users start to transact with it. Finally, we look into a technology that is not a cryptocurrency itself but is built on top of Bitcoin, thus providing a so-called layer 2 solution, the Lightning network. Again, our measurements showed some serious privacy concerns of this technology, some of which were novel and highly applicable

    Prevention and trust evaluation scheme based on interpersonal relationships for large-scale peer-to-peer networks

    Get PDF
    In recent years, the complex network as the frontier of complex system has received more and more attention. Peer-to-peer (P2P) networks with openness, anonymity, and dynamic nature are vulnerable and are easily attacked by peers with malicious behaviors. Building trusted relationships among peers in a large-scale distributed P2P system is a fundamental and challenging research topic. Based on interpersonal relationships among peers of large-scale P2P networks, we present prevention and trust evaluation scheme, called IRTrust. The framework incorporates a strategy of identity authentication and a global trust of peers to improve the ability of resisting the malicious behaviors. It uses the quality of service (QoS), quality of recommendation (QoR), and comprehensive risk factor to evaluate the trustworthiness of a peer, which is applicable for large-scale unstructured P2P networks. The proposed IRTrust can defend against several kinds of malicious attacks, such as simple malicious attacks, collusive attacks, strategic attacks, and sybil attacks. Our simulation results show that the proposed scheme provides greater accuracy and stronger resistance compared with existing global trust schemes. The proposed scheme has potential application in secure P2P network coding

    Off-chain Transaction Routing in Payment Channel Networks: A Machine Learning Approach

    Get PDF
    Blockchain is a foundational technology that has the potential to create new prospects for our economic and social systems. However, the scalability problem limits the capability to deliver a target throughput and latency, compared to the traditional financial systems, with increasing workload. Layer-two is a collective term for solutions designed to help solve the scalability by handling transactions off the main chain, also known as layer one. These solutions have the capability to achieve high throughput, fast settlement, and cost efficiency without sacrificing network security. For example, bidirectional payment channels are utilized to allow the execution of fast transactions between two parties, thus forming the so-called payment channel networks (PCNs). Consequently, an efficient routing protocol is needed to find the payment path from the sender to the receiver, with the lowest transaction fees. This routing protocol needs to consider, among other factors, the unexpected online/offline behavior of the constituent payment nodes as well as payment channel imbalance. This study proposes a novel machine learning-based routing technique for fully distributed and efficient off-chain transactions to be used within the PCNs. For this purpose, the effect of the offline nodes and channel imbalance on the payment channels network are modeled. The simulation results demonstrate a good tradeoff among success ratio, transaction fees, routing efficiency, transaction overhead, and transaction maintenance overhead as compared to other techniques that have been previously proposed for the same purpose

    OpenDSU: Digital Sovereignty in PharmaLedger

    Full text link
    Distributed ledger networks, chiefly those based on blockchain technologies, currently are heralding a next generation of computer systems that aims to suit modern users' demands. Over the recent years, several technologies for blockchains, off-chaining strategies, as well as decentralised and respectively self-sovereign identity systems have shot up so fast that standardisation of the protocols is lagging behind, severely hampering the interoperability of different approaches. Moreover, most of the currently available solutions for distributed ledgers focus on either home users or enterprise use case scenarios, failing to provide integrative solutions addressing the needs of both. Herein we introduce the OpenDSU platform that allows to interoperate generic blockchain technologies, organised - and possibly cascaded in a hierarchical fashion - in domains. To achieve this flexibility, we seamlessly integrated a set of well conceived OpenDSU components to orchestrate off-chain data with granularly resolved and cryptographically secure access levels that are nested with sovereign identities across the different domains. Employing our platform to PharmaLedger, an inter-European network for the standardisation of data handling in the pharmaceutical industry and in healthcare, we demonstrate that OpenDSU can cope with generic demands of heterogeneous use cases in both, performance and handling substantially different business policies. Importantly, whereas available solutions commonly require a pre-defined and fixed set of components, no such vendor lock-in restrictions on the blockchain technology or identity system exist in OpenDSU, making systems built on it flexibly adaptable to new standards evolving in the future.Comment: 18 pages, 8 figure

    Communities and emerging semantics in semantic link network:discovery and learning

    Get PDF
    The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the Semantic Link Network (SLN), a loosely coupled semantic data model that can semantically link resources and derive out implicit semantic links according to a set of relational reasoning rules. By studying the intrinsic relationship between semantic communities and the semantic space of SLN, approaches to discovering reasoning-constraint, rule-constraint, and classification-constraint semantic communities are proposed. Further, the approaches, principles, and strategies for discovering emerging semantics in dynamic SLNs are studied. The basic laws of the semantic link network motion are revealed for the first time. An e-learning environment incorporating the proposed approaches, principles, and strategies to support effective discovery and learning is suggested

    Supporting Online Social Networks

    No full text
    • 

    corecore