A bitcoin node needs to download the full block contents of the entire blockchain, before actually being able to send and receive transactions on bitcoin broadcast network, except simple payment verification clients which require only block headers and bloom filters to sync with others peers available on the network. Transactions/Blocks pass through a complex process at sender and receiver than it apparently looks to be. During transmission transactions/blocks are broken down into smaller chunks of data so that they can be carried on the wire. These chunks are given appropriate headers, encapsulated and then passed through several layers to reach the destination. In this paper we captured Bitcoin packets using Wireshark and deeply investigated and analyzed them. We investigated how bitcoin transaction/block messages work and what values and parameters are considered during this whole process.
Thanks to the new global order established after the Second World War and the communication networks that have become widespread. Due to this, the electronic payment systems that have started to be used since the second half of the 20th century in the world and the credit cards called plastic money have started to be widely used in our country since the 80 '. From the beginning of 2000's, it is observed that cash-based transactions are lagging e-money-based transactions. Since the beginning of the 90's the Internet and social media emerged with new media technologies and after 2004, it has become a dominant idea that these environments provide freedom and even create disorder. In the last 5-6 years we have seen the trade of crypto currencies like Bitcoin. Bitcoin is a method of payment that people use for their purchases based on mutual trust, without an authority issuing it. It works independently of the state authority and the banking system. From this point of view, it is seen as the reflection of freedom originally envisaged for the internet environment. In this context, the question of how bitcoin systems are perceived, and the level of entrepreneurship are issues that needs to be investigated. In this study, a survey was conducted to measure the level of entrepreneurship of bitcoin miners, buyers and sellers. Twitter users were selected for the sample. The research is designed to examine the impact of entrepreneurship motivated by investors' interest in entering the arena that is said to be quite new and risky, and which sub-factors may dominate, which deals with bitcoin and similar crypto currencies. The findings show that users who are interested in mining, buying-selling and trading have very high level of entrepreneurial points.
James Tapsell, Raja Naeem Akram, Konstantinos Markantonakis
Bitcoin is a decentralised digital currency that relies on cryptography rather than trusted third parties such as central banks for its security. Underpinning the operation of the currency is a peer-to-peer (P2P) network that facilitates the execution of transactions by end users, as well as the transaction confirmation process known as bitcoin mining. The security of this P2P network is vital for the currency to function and subversion of the underlying network can lead to attacks on bitcoin users including theft of bitcoins, manipulation of the mining process and denial of service (DoS). As part of this paper the network protocol and bitcoin core software are analysed, with three bitcoin message exchanges (the connection handshake, GETHEADERS/HEADERS and MEMPOOL/INV) found to be potentially vulnerable to spoofing and use in distributed denial of service (DDoS) attacks. Possible solutions to the identified weaknesses and vulnerabilities are evaluated, such as the introduction of random nonces into network messages exchanges.
The past decade has witnessed the rapid evolution in blockchain technologies, which has attracted tremendous interests from both the research communities and industries. The blockchain network was originated from the Internet financial sector as a decentralized, immutable ledger system for transactional data ordering. Nowadays, it is envisioned as a powerful backbone/framework for decentralized data processing and data-driven self-organization in flat, open-access networks. In particular, the plausible characteristics of decentralization, immutability, and self-organization are primarily owing to the unique decentralized consensus mechanisms introduced by blockchain networks. This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks. In this paper, we provide a systematic vision of the organization of blockchain networks. By emphasizing the unique characteristics of decentralized consensus in blockchain networks, our in-depth review of the state-of-the-art consensus protocols is focused on both the perspective of distributed consensus system design and the perspective of incentive mechanism design. From a game-theoretic point of view, we also provide a thorough review of the strategy adopted for self-organization by the individual nodes in the blockchain backbone networks. Consequently, we provide a comprehensive survey of the emerging applications of blockchain networks in a broad area of telecommunication. We highlight our special interest in how the consensus mechanisms impact these applications. Finally, we discuss several open issues in the protocol design for blockchain consensus and the related potential research directions.
Muhammad Saad, Aziz Mohaisen, Charles Kamhoua, Kevin Kwait · 5 authors
In this paper, we look at the use of hash-based, one-time signatures in the context of the Blockchain systems and demonstrate how the replacement of currently utilized schemes into a one-time signature can help deter double-spending. Towards this goal, we make the following contributions. 1) We introduce a notion of double- spending deterrence, a form of malleability that does not require pre-authorization from the signer to create a signature on an arbitrary message using two previously signed messages. It is used as a penalty to deter double-spending and disincentivize forgery. 2) We study features of various one-time signature schemes, and we demonstrate their effectiveness in thwarting double-spending. 3) We explore the design space of applying our methodology to the Blockchain system with a clear example and design options to deter double-spending. The results reported in this paper are promising, and open several new directions.
Ransomware is a type of malware that encrypts the files of infected hosts and demands payment, often in a crypto-currency like Bitcoin. In this paper, we create a measurement framework that we use to perform a large-scale, two-year, end-to-end measurement of ransomware payments, victims, and operators. By combining an array of data sources, including ransomware binaries, seed ransom payments, victim telemetry from infections, and a large database of bitcoin addresses annotated with their owners, we sketch the outlines of this burgeoning ecosystem and associated third-party infrastructure. In particular, we are able to trace the financial transactions, from the acquisition of bitcoins by victims, through the payment of ransoms, to the cash out of bitcoins by the ransomware operators. We find that many ransomware operators cashed out using BTC-e, a now-defunct Bitcoin exchange. In total we are able to track over $16 million USD in likely ransom payments made by 19,750 potential victims during a two-year period. While our study focuses on ransomware, our methods are potentially applicable to other cybercriminal operations that have similarly adopted Bitcoin as their payment channel.
Nguyen B. Truong, TaiâWon Um, Bo Zhou, Gyu Myoung Lee
In recent years, Blockchain has been expected to create a secure mechanism for exchanging not only for cryptocurrency but also for other types of assets without the need for a powerful and trusted third-party. This could enable a new era of the Internet usage called the Internet of Value (IoV) in which any types of assets such as intellectual and digital properties, equity and wealth can be digitized and transferred in an automated, secure, and convenient manner. In the IoV, Blockchain is used to guarantee security of transactions that the transactions are nearly impossible to be altered; thus it is impractical to retract once a transaction is confirmed. Therefore, to strengthen the IoV, before making any transactions it is crucial to evaluate trust between participants for reducing the risk of dealing with malicious peers. In this article, we clarify the concept of IoV and propose a trust-based IoV model including a system architecture, components and features. Then, we present a trust platform in the IoV considering two concepts, Experience and Reputation, originated from Social Networks for evaluating trust between two any peers in the IoV. The Experience and Reputation are characterized and calculated using mathematical models with analysis and simulation in the IoV environment. We believe this paper consolidates the understandings about IoV technologies and demonstrates how trust is evaluated and used to strengthen the IoV. It also opens important research directions on both IoV and trust in the future.
The use of technology has become important at this point in helping to meet human needs.Due to the increasing use of technology, new challenges are brought in the process of democracy as most people today donât trust their governments, making elections is very important in modern democracy . Elections have a great importance in determining who will rule a nation or an organization or it can be said as it is an event that decides the fate of any nation. In modern democracy, elections are very important but large sections of society around the world do not trust their election system which is a major concern for democracy. Even the worldâs largest democracies like India, United States, still suffer from a flawed electoral system. Vote rigging, hacking of EVM (Electronic voting machine), election manipulation, and polling booth capturing are the major issues in the current voting system The blockchain is said as emerging, decentralized, and distributed technology that promises to enhance different aspects of many industries. Expanding e-voting into blockchain technology could be the solution to eliminate the present concerns in e-voting system There is no doubt that the ever changing concept of the blockchain, which is the backbone of the famous cryptocurrency Bitcoin has triggered the start of a new era in the Internet and the online services. While most people focus only on bitcoin and other cryptocurrencies; there are in fact, many operations, both administrative and fintech that can only be done online/offline can now safely be moved to the Internet as online services because of immutability of blockchain. What makes blockchain a powerful tool is its smarts contracts and many features which overcomes traditional systems. Smart contracts are meaningful pieces of codes, to be integrated in the blockchain and executed as scheduled in every step of blockchain updates. E-votin, is another trending, yet critical, topic related to the online services. The blockchain with the smart contracts, emerges as a good candidate to use in developments of safer, cheaper, more secure, more transparent, and easier-to-use e-voting systems.Due to its consistency, widespread use, and provision of smart contracts logic, Ethereum and its network is one of the most suitable ones. An e-voting system must be secure, as it should not allow duplicated votes and be fully transparent, while protecting the privacy of the attendees. In this project, we have implemented and tested an e-voting application as a smart contract for the Ethereum network using the Ethereum and the Solidity language.
Objective: There is broad agreement in the literature on the transformative potential of drug cryptomarkets that allow sourcing on a global market and consequently the circumvention of existing supply chains between producer and end user. We examine whether the transformative potential of drug cryptomarkets has been realized in two ways: Are cryptomarket drug sellers found in production and transit countries? and Do we see the increased use of shipping across international borders over time? Method: Using data collected by the DATACRYPTO software tool between 2013 and 2016, we characterize cryptomarket buyer behavior through the product reviews (i.e., sales transactions) posted on 15 cryptomarkets. Findings: Cryptomarket drug sellers are predominantly based in countries of Europe, North America, and Oceania. For both cannabis resin and cocaine sold on cryptomarkets, we find that known production and transit countries are not the primary sources of supplied drugs but rather key countries of consumption. In the case of 3,4-methylenedioxymethamphetamine, we observe that the Netherlands, a known production country, is the largest supplier. We further observe tendencies over time toward increased localization of cryptomarkets with regard to product destinations. Discussion: Though cryptomarkets offer a potentially global platform for drug distribution, they do not tend to be used as such. We explain our results with reference to buyersâ preferences regarding safety, risk, and convenience, alongside structural limitations for cryptomarket use such as bitcoin availability.
Online portals include an increasing amount of user feedback in form of ratings and reviews. Recent research highlighted the importance of this feedback and confirmed that positive feedback improves product sales figures and thus its success. However, online portals' operators act as central authorities throughout the overall review process. In the worst case, operators can exclude users from submitting reviews, modify existing reviews, and introduce fake reviews by fictional consumers. This paper presents ReviewChain, a decentralized review approach. Our approach avoids central authorities by using blockchain technologies, decentralized apps and storage. Thereby, we enable users to submit and retrieve untampered reviews. We highlight the implementation challenges encountered when realizing our approach on the public Ethereum blockchain. For each implementation challange, we discuss possible design alternatives and their trade-offs regarding costs, security, and trustworthiness. Finally, we analyze which design decision should be chosen to support specific trade-offs and present resulting combinations of decentralized blockchain technologies, also with conventional centralized technologies.
Soon after its introduction in 2009, Bitcoin has been adopted by cyber-criminals, which rely on its pseudonymity to implement virtually untraceable scams. One of the typical scams that operate on Bitcoin are the so-called Ponzi schemes. These are fraudulent investments which repay users with the funds invested by new users that join the scheme, and implode when it is no longer possible to find new investments. Despite being illegal in many countries, Ponzi schemes are now proliferating on Bitcoin, and they keep alluring new victims, who are plundered of millions of dollars. We apply data mining techniques to detect Bitcoin addresses related to Ponzi schemes. Our starting point is a dataset of features of real-world Ponzi schemes, that we construct by analysing, on the Bitcoin blockchain, the transactions used to perform the scams. We use this dataset to experiment with various machine learning algorithms, and we assess their effectiveness through standard validation protocols and performance metrics. The best of the classifiers we have experimented can identify most of the Ponzi schemes in the dataset, with a low number of false positives.
Husam Al Jawaheri, Mashael Al Sabah, Yazan Boshmaf, Aiman Erbad
With the rapid increase of threats on the Internet, people are continuously seeking privacy and anonymity. Services such as Bitcoin and Tor were introduced to provide anonymity for online transactions and Web browsing. Due to its pseudonymity model, Bitcoin lacks retroactive operational security, which means historical pieces of information could be used to identify a certain user. We investigate the feasibility of deanonymizing users of Tor hidden services who rely on Bitcoin as a payment method by exploiting public information leaked from online social networks, the Blockchain, and onion websites. This, for example, allows an adversary to link a user with @alice Twitter address to a Tor hidden service with private.onion address by finding at least one past transaction in the Blockchain that involves their publicly declared Bitcoin addresses.
To demonstrate the feasibility of this deanonymization attack, we carried out a real-world experiment simulating a passive, limited adversary. We crawled 1.5K hidden services and collected 88 unique Bitcoin addresses. We then crawled 5B tweets and 1M BitcoinTalk forum pages and collected 4.2K and 41K unique Bitcoin addresses, respectively. Each user address was associated with an online identity along with its public profile information. By analyzing the transactions in the Blockchain, we were able to link 125 unique users to 20 Tor hidden services, including sensitive ones, such as The Pirate Bay and Silk Road. We also analyzed two case studies in detail to demonstrate the implications of the resulting information leakage on user anonymity. In particular, we confirm that Bitcoin addresses should always be considered exploitable, as they can be used to deanonymize users retroactively. This is especially important for Tor hidden service users who actively seek and expect privacy and anonymity.
Husam Al Jawaheri, Mashael Al Sabah, Yazan Boshmaf, Aiman Erbad
With the rapid increase of threats on the Internet, people are continuously seeking privacy and anonymity. Services such as Bitcoin and Tor were introduced to provide anonymity for online transactions and Web browsing. Due to its pseudonymity model, Bitcoin lacks retroactive operational security, which means historical pieces of information could be used to identify a certain user. We investigate the feasibility of deanonymizing users of Tor hidden services who rely on Bitcoin as a payment method by exploiting public information leaked from online social networks, the Blockchain, and onion websites. This, for example, allows an adversary to link a user with @alice Twitter address to a Tor hidden service with private.onion address by finding at least one past transaction in the Blockchain that involves their publicly declared Bitcoin addresses. To demonstrate the feasibility of this deanonymization attack, we carried out a real-world experiment simulating a passive, limited adversary. We crawled 1.5K hidden services and collected 88 unique Bitcoin addresses. We then crawled 5B tweets and 1M BitcoinTalk forum pages and collected 4.2K and 41K unique Bitcoin addresses, respectively. Each user address was associated with an online identity along with its public profile information. By analyzing the transactions in the Blockchain, we were able to link 125 unique users to 20 Tor hidden services, including sensitive ones, such as The Pirate Bay and Silk Road. We also analyzed two case studies in detail to demonstrate the implications of the resulting information leakage on user anonymity. In particular, we confirm that Bitcoin addresses should always be considered exploitable, as they can be used to deanonymize users retroactively. This is especially important for Tor hidden service users who actively seek and expect privacy and anonymity.
This paper presents the implementation of an interactive Zero Knowledge Password authentication scheme for commercial Web sites. In this scheme, a legitimate prover (client) can exchange a secret code (password) with a remote skeptic (server), in order to reveal his/her identification. Based on the validity of the secret code the skeptic then allows the prover to login to the site and access the web services. This paper introduces a protocol that integrates the concepts of Discrete Logarithm Problem (DLP) and Zero-Knowledge Proofs (ZKP). The protocol consists of three entities, namely, the prover, the skeptic, and the facilitator who interact with one another to generate the secret code. When tested, the time to carry out various operations related to this protocol was reasonably small (under 4 seconds). Our scheme is resistant to man-in-the-middle attack and discourages replaying previously intercepted secret codes. We also propose two modifications to our basic scheme to make it resistant against the attack on Integrity and Denial of Service attack (DOS).
Large-scale rumor spreading could pose severe social and economic damages. The emergence of online social networks along with the new media can even make rumor spreading more severe. Effective control of rumor spreading is of theoretical and practical significance. This paper takes the first step to understand how the blockchain technology can help limit the spread of rumors. Specifically, we develop a new paradigm for social networks embedded with the blockchain technology, which employs decentralized contracts to motivate trust networks as well as secure information exchange contract. We design a blockchain-based sequential algorithm which utilizes virtual information credits for each peer-to-peer information exchange. We validate the effectiveness of the blockchain-enabled social network on limiting the rumor spreading. Simulation results validate our algorithm design in avoiding rapid and intense rumor spreading, and motivate better mechanism design for trusted social networks.
Many cryptocurrencies rely on Blockchain for its operation. Blockchain serves as a public ledger where all the completed transactions can be looked up. To place transactions in the Blockchain, a mining operation must be performed. However, due to a limited mining capacity, the transaction confirmation time is increasing. To mitigate this problem many ideas have been proposed, but they all come with own challenges. We propose a novel parallel mining method that can adjust the mining capacity dynamically depending on the congestion level. It does not require an increase in the block size or a reduction of the block confirmation time. The proposed scheme can increase the number of parallel blockchains when the mining congestion is experienced, which is especially effective under DDoS attack situation. We describe how and when the Blockchain is split or merged, how to solve the imbalanced mining problem, and how to adjust the difficulty levels and rewards. We then show the simulation results comparing the performance of binary blockchain and the traditional single blockchain.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Bitcoin is the most popular cryptocurrency on the planet. It relies on strong cryptography and peer-to-peer network. Bitcoin is gaining more and more popularity in criminal society. That is why Bitcoin is often used as money laundering tool or payment method for illegal products and services. In this paper we explore various methods for Bitcoin users deanonimization, which is an important task in anti-money laundering process and cybercrime investigation.
Blockchain technologies have the potential to establish novel financial service infrastructures and reshape numerous fields. A blockchain is essentially a distributed ledger maintained by a set of peers (i.e., trading nodes) that do not fully trust each other. A key challenge that blockchain faces is to precisely classify the blockchain peers into categories with respect to their behavior patterns, which will not only enable deeper insights into the blockchain network but also facilitate more effective maintenance of the various peers (in private chains). In this paper, we introduce and formulate the problem of behavior pattern classification in blockchain networks and propose a novel deep-learning-based method, termedPeerClassifier, to address the problem. To the best of our knowledge, we are the first to formally define the problem of peer behavior classification in blockchain networks. Moreover, we conduct extensive experiments to evaluate our proposed approach. Experimental results demonstrate thatPeerClassifieris significantly more effective than the existing conventional methods.
There are many existing voting solutions which have different benefits and issues. The most significant ones are lack of transparency and auditability. Recently developed blockchain technology may be a solution to these issues. The paper describes the use of intelligent agents and multi-agent system concept for Auditable Blockchain Voting System (ABVS), which integrates e-voting process with blockchain technology into one supervised non-remote internet voting system which is end-to-end verifiable.
Savva Shanaev, Arina Shuraeva, Mikhail Vasenin, Maksim Kuznetsov
In this article, an event studies approach is utilized to assess the influence of 51% attacks on proof-of-work (PoW) cryptocurrency prices. The study uses an exhaustive sample of 14 individual attacks on 13 cryptocurrencies. Across multiple event studies techniques, majority attacks on blockchains are consistently shown to immediately decrease corresponding coin prices by 12% to 15%. Significantly negative price response is robust in various event windows. Coin prices do not recover to pre-attack levels one week after the event. There is evidence of pump-and-dump schemes prior to the 51% attack, however the market demonstrates high efficiency after the attacks. 51% attacks are suggested to be a fundamental risk factor for cryptocurrency investments, primarily characteristic of small PoW coins with low hash rates. <b>TOPICS:</b>Currency, risk management, financial crises and financial market history <b>Key Findings</b> âą 51% attacks on Proof-of-Work cryptocurrencies decrease their market prices by 12.60% on average. âą The effect is robust to different measurement techniques and in various event windows. âą There is evidence of insider trading and âpump-and-dumpâ schemes prior to the attacks.
Jingjing Gu, Binglin Sun, Xiaojiang Du, Jun Wang · 6 authors
To address the problem of detecting malicious codes in malware and extracting the corresponding evidences in mobile devices, we construct a consortium blockchain framework, which is composed of a detecting consortium chain shared by test members and a public chain shared by users. Specifically, in view of different malware families in Android-based system, we perform feature modeling by utilizing statistical analysis method, so as to extract malware family features, including software package feature, permission and application feature, and function call feature. Moreover, for reducing false-positive rate and improving the detecting ability of malware variants, we design a multi-feature detection method of Android-based system for detecting and classifying malware. In addition, we establish a fact-base of distributed Android malicious codes by blockchain technology. The experimental results show that, compared with the previously published algorithms, the new proposed method can achieve higher detection accuracy in limited time with lower false-positive and false-negative rates.
Blockchain technology becomes increasingly popular. It also attracts scams, for example, Ponzi scheme, a classic fraud, has been found making a notable amount of money on Blockchain, which has a very negative impact. To help dealing with this issue, this paper proposes an approach to detect Ponzi schemes on blockchain by using data mining and machine learning methods. By verifying smart contracts on Ethereum, we first extract features from user accounts and operation codes of the smart contracts and then build a classification model to detect latent Ponzi schemes implemented as smart contracts. The experimental results show that the proposed approach can achieve high accuracy for practical use. More importantly, the approach can be used to detect Ponzi schemes even at the moment of its creation. By using the proposed approach, we estimate that there are more than 400 Ponzi schemes running on Ethereum. Based on these results, we propose to build a uniform platform to evaluate and monitor every created smart contract for early warning of scams.
Jan 1, 2018·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Mikkel Alexander Harlev, Haohua Sun Yin, Klaus Christian Langenheldt, Raghava Rao Mukkamala · 5 authors
Bitcoin is a cryptocurrency whose transactions are recorded on a distributed, openly accessible ledger. On the Bitcoin Blockchain, an entityâs real-world identity is hidden behind a pseudonym, a so-called address. Therefore, Bitcoin is widely assumed to provide a high degree of anonymity, which is a driver for its frequent use for illicit activities. This paper presents a novel approach for reducing the anonymity of the Bitcoin Blockchain by using Supervised Machine Learning to predict the type of yet-unidentified entities. We utilised a sample of 434 entities (with ~ 200 million transactions), whose identity and type had been revealed, as training set data and built classifiers differentiating among 10 categories. Our main finding is that we can indeed predict the type of a yet-unidentified entity. Using the Gradient Boosting algorithm, we achieve an accuracy of 77% and F1-score of ~ 0.75. We discuss our novel approach of Supervised Machine Learning for uncovering Bitcoin Blockchain anonymity and its potential applications to forensics and financial compliance and its societal implications, outline study limitations and propose future research directions.
In blockchain networks adopting the proof-of-work schemes, the monetary incentive is introduced by the Nakamoto consensus protocol to guide the behaviors of the full nodes (i.e., block miners) in the process of maintaining the consensus about the blockchain state. The block miners have to devote their computation power measured in hash rate in a crypto-puzzle solving competition to win the reward of publishing (a.k.a., mining) new blocks. Due to the exponentially increasing difficulty of the crypto-puzzle, individual block miners tends to join mining pools, i.e., the coalitions of miners, in order to reduce the income variance and earn stable profits. In this paper, we study the dynamics of mining pool selection in a blockchain network, where mining pools may choose arbitrary block mining strategies. We identify the hash rate and the block propagation delay as two major factors determining the outcomes of mining competition, and then model the strategy evolution of the individual miners as an evolutionary game. We provide the theoretical analysis of the evolutionary stability for the pool selection dynamics in a case study of two mining pools. The numerical simulations provide the evidence to support our theoretical discoveries as well as demonstrating the stability in the evolution of miners' strategies in a general case.