Follow blockchain research across journals, conferences, and preprint repositories.
1,600 results · page 51 of 67
Sivakamy Lakshminarayanan, P. N. Kumar, N. M. Dhanya
No abstract is available for this record.
Shiv Hari Tewari
No abstract is available for this record.
Dennis Eijkel, Ansgar Fehnker
No abstract is available for this record.
Arthur Carvalho, Chaitanya Sambhara, Patrick Young
Since Bitcoin’s meteoric rise, hundreds of cryptocurrencies that people now publicly trade have emerged. As such, the question naturally arises: how have cryptocurrencies evolved over time? Drawing on the theory of polycentric information commons and cryptocurrencies’ historical similarities with another popular information commons (namely, Linux), we make predictions regarding what cryptocurrencies may look like in the future. Specifically, we focus on four important historical similarities: 1) support from online hacker communities, 2) pursuit of freedom, 3) criticism about features and use, and 4) proliferation of forks. We then predict that: 1) cryptocurrencies will become more pragmatic rather than ideological, 2) cryptocurrencies will become more diverse in terms of not only the underlying technology but also the intended audience, and 3) the core technology behind cryptocurrencies, called blockchain, will be successfully used beyond cryptocurrencies.
Radosław Michalski, Daria Dziubałtowska, Piotr Macek
The term blockchain has its roots in cryptocurrencies. However, its applications are now more widespread, and in many areas, this technology has become the foundation of the distributed ledger. The blockchain protocol assumes that all the participants of the system are both contributors and safeguards of this ledger, since the lack of a trusted third party requires other security precautions in order to maintain the consistency of transactions. In this work, we investigate whether for the participants of a blockchain-based system that does not require revealing the character explicitly, it can be discovered by other means. In order to verify this, we built and publicly released a dataset of nearly 9,000 addresses of nodes in the most popular cryptocurrency - Bitcoin, and then labelled them. These labels represent the character the nodes have in the network, e.g. miners or exchanges. We then developed a set of features that quantify the behaviour of nodes in the network and used supervised machine learning algorithms to find out whether the character of nodes can be revealed based on these features. Our results demonstrate, due to the F-score reaching over 95% in the best-performing algorithms, that it is hard to hide the role the node has in a blockchain-based network. These results indicate that to build trustworthy blockchain-based systems that fully comply with original blockchain assumptions, specific countermeasures are needed in order to preserve the desired level of anonymity.
Changhoon Kang, Chaehyeon Lee, Kyungchan Ko, Jongsoo Woo · 5 authors
No abstract is available for this record.
Tin Tironsakkul, Manuel Maarek, Andrea Eross, Mike Just
Mixer services purportedly remove all connections between the input (deposited) Bitcoins and the output (withdrawn) mixed Bitcoins, seemingly rendering taint analysis tracking ineffectual. In this paper, we introduce and explore a novel tracking strategy, called \emph{Address Taint Analysis}, that adapts from existing transaction-based taint analysis techniques for tracking Bitcoins that have passed through a mixer service. We also investigate the potential of combining address taint analysis with address clustering and backward tainting. We further introduce a set of filtering criteria that reduce the number of false-positive results based on the characteristics of withdrawn transactions and evaluate our solution with verifiable mixing transactions of nine mixer services from previous reverse-engineering studies. Our finding shows that it is possible to track the mixed Bitcoins from the deposited Bitcoins using address taint analysis and the number of potential transaction outputs can be significantly reduced with the filtering criteria.
Chaehyeon Lee, Sajan Maharjan, Kyungchan Ko, Jongsoo Woo · 5 authors
No abstract is available for this record.
Jie Yin, Xiang Cui, Chaoge Liu, Qixu Liu · 6 authors
No abstract is available for this record.
Naoki Hiramoto, Yoichi Tsuchiya
No abstract is available for this record.
Jinhua Ma, Shih-Ya Lin, Xin Chen, Hung–Min Sun · 6 authors
In recent years, blockchain has received increasing attention and numerous applications have emerged from this technology. A renowned Blockchain application is the cryptocurrency Bitcoin, that has not only been effectively solving the double-spending problem but also it can confirm the legitimacy of transactional records without relying on a centralized system to do so. Therefore, any application using Blockchain technology as the base architecture ensures that the contents of its data are tamper-proof. This paper uses the decentralized Blockchain technology approach to ensure that consumers do not fully rely on the merchants to determine if products are genuine. We describe a decentralized Blockchain system with products anti-counterfeiting, in that way manufacturers can use this system to provide genuine products without having to manage direct-operated stores, which can significantly reduce the cost of product quality assurance.
Pavlos Papadopoulos, Nikolaos Pitropakis, William J. Buchanan, Owen Lo · 5 authors
The Domain Name System (DNS) was created to resolve the IP addresses of the web servers to easily remembered names. When it was initially created, security was not a major concern; nowadays, this lack of inherent security and trust has exposed the global DNS infrastructure to malicious actors. The passive DNS data collection process creates a database containing various DNS data elements, some of which are personal and need to be protected to preserve the privacy of the end users. To this end, we propose the use of distributed ledger technology. We use Hyperledger Fabric to create a permissioned blockchain, which only authorized entities can access. The proposed solution supports queries for storing and retrieving data from the blockchain ledger, allowing the use of the passive DNS database for further analysis, e.g. for the identification of malicious domain names. Additionally, it effectively protects the DNS personal data from unauthorized entities, including the administrators that can act as potential malicious insiders, and allows only the data owners to perform queries over these data. We evaluated our proposed solution by creating a proof-of-concept experimental setup that passively collects DNS data from a network and then uses the distributed ledger technology to store the data in an immutable ledger, thus providing a full historical overview of all the records.
Kristin Weber, Andreas E. Schütz, Tobias Fertig, Nicholas H. Müller
No abstract is available for this record.
Yu Wang, Zhenzhen Li, Gaopeng Gou, Gang Xiong · 6 authors
No abstract is available for this record.
Peng Qian, Zhenguang Liu, Qinming He, Roger Zimmermann · 5 authors
In the last decade, smart contract security issues lead to tremendous losses, which has attracted increasing public attention both in industry and in academia. Researchers have embarked on efforts with logic rules, symbolic analysis, and formal analysis to achieve encouraging results in smart contract vulnerability detection tasks. However, the existing detection tools are far from satisfactory. In this paper, we attempt to utilize the deep learning-based approach, namely bidirectional long-short term memory with attention mechanism (BLSTM-ATT), aiming to precisely detect reentrancy bugs. Furthermore, we propose contract snippet representations for smart contracts, which contributes to capturing essential semantic information and control flow dependencies. Our extensive experimental studies on over 42,000 real-world smart contracts show that our proposed model and contract snippet representations significantly outperform state-of-the-art methods. In addition, this work proves that it is practical to apply deep learning-based technology on smart contract vulnerability detection, which is able to promote future research towards this area.
Leonardo Nizzoli, Serena Tardelli, Marco Avvenuti, Stefano Cresci · 6 authors
Cryptocurrencies represent one of the most attractive markets for financial speculation. As a consequence, they have attracted unprecedented attention on social media. Besides genuine discussions and legitimate investment initiatives, several deceptive activities have flourished. In this work, we chart the online cryptocurrency landscape across multiple platforms. To reach our goal, we collected a large dataset, composed of more than 50M messages published by almost 7M users on Twitter, Telegram and Discord, over three months. We performed bot detection on Twitter accounts sharing invite links to Telegram and Discord channels, and we discovered that more than 56% of them were bots or suspended accounts. Then, we applied topic modeling techniques to Telegram and Discord messages, unveiling two different deception schemes - “pump-and-dump” and “Ponzi” - and identifying the channels involved in these frauds. Whereas on Discord we found a negligible level of deception, on Telegram we retrieved 296 channels involved in pump-and-dump and 432 involved in Ponzi schemes, accounting for a striking 20% of the total. Moreover, we observed that 93% of the invite links shared by Twitter bots point to Telegram pump-and-dump channels, shedding light on a little-known social bot activity. Charting the landscape of online cryptocurrency manipulation can inform actionable policies to fight such abuse.
Bishwas C Gupta, Nitesh Kumar, Anand Handa, Sandeep K. Shukla
No abstract is available for this record.
Santeri Paavolainen, Christopher Carr
Ethereum is a decentralized blockchain, known as being the second most popular public blockchain after Bitcoin. Since Ethereum is decentralised the canonical state is determined by the Ethereum network participants via a consensus mechanism without a centralized coordinator. The network participants are required to evaluate every transaction starting from the genesis block, which requires a large amount of network, computing, and storage resources. This is impractical for many devices with either limited computing resources or intermittent network connectivity. To overcome this drawback Ethereum defines a light client protocol where the light client fetches the blockchain state from a node operating as a light protocol server. Light clients are unable to maintain blockchain state internally, and as a consequence can only perform partial validation on blocks. Thus they rely on the light server for full block validation and to provide the updated blockchain state. Light clients connect to multiple light servers to mitigate the risk of relying on a single potentially dishonest server. Ethereum light clients are known to suffer from a probabilistic security model, but they are widely assumed to be secure under normal operating conditions. In fact, the implicit security assumptions of light clients have not been formally characterised in the literature. We present and analyse the probabilistic security guarantees under three different adversarial scenarios. The results show that for any adversary that is able to manipulate the network, the security assurances provided by the light protocol are severely impacted, and in some cases entirely lost. These results clearly demonstrate that the assumption of normal operating conditions is insufficient to justify the security assumptions of light clients. Our work also provides insight to the security of light clients under different security parameters, allowing light client implementers to more accurately understand the potential security trade-offs.
Zihao Yuan, Qi Yuan, Jiajing Wu
No abstract is available for this record.
Nitesh Kumar, Ajay Singh, Anand Handa, Sandeep K. Shukla
No abstract is available for this record.
Friedhelm Victor
No abstract is available for this record.
Michał Kędziora, Patryk Kozłowski, Piotr Jóźwiak
No abstract is available for this record.
Muhammad Saad, Jeffrey Spaulding, Laurent Njilla, Charles Kamhoua · 7 authors
In this paper, we systematically explore the attack surface of the Blockchain technology, with an emphasis on public Blockchains. Towards this goal, we attribute attack viability in the attack surface to 1) the Blockchain cryptographic constructs, 2) the distributed architecture of the systems using Blockchain, and 3) the Blockchain application context. To each of those contributing factors, we outline several attacks, including selfish mining, the 51% attack, DNS attacks, distributed denial-of-service (DDoS) attacks, consensus delay (due to selfish behavior or distributed denial-of-service attacks), Blockchain forks, orphaned and stale blocks, block ingestion, wallet thefts, smart contract attacks, and privacy attacks. We also explore the causal relationships between these attacks to demonstrate how various attack vectors are connected to one another. A secondary contribution of this work is outlining effective defense measures taken by the Blockchain technology or proposed by researchers to mitigate the effects of these attacks and patch associated vulnerabilities.
Samer Shorman, Mohammad Allaymoun
Social networking pages authenticate by blockchain technology, through authenticating personal information and profile pages in the form of block and then distributing them with Blockchain to become a trusted reference point. To identified and verified social network accounts. This research proposed an effective and easy technical mechanism to authenticate the personal pages on social networks. Using this mechanism, anyone can authenticate any account on social networks, as well as increasing the possibility of making sure of the real individual behind social networking accounts. Moreover, this technique will show the fake accounts in order to reach a more confident and secure social network environment. Blockchain technique requires only a simple update to the characteristics of its platforms by developers, which is only a participatory mechanism between Blockchain and personal information. It is then combined with personal pages, to indicate that these pages contain the real personal information of the account holder, which is stored in an encrypted block that is difficult to modify, copy, or steal.