Blockchain Papers

Ren Zhang, Bart Preneel

No abstract is available for this record.

Massimo Bartoletti, Salvatore Carta, Tiziana Cimoli, Roberto Saia

Ponzi schemes are financial frauds which lure users under the promise of high\nprofits. Actually, users are repaid only with the investments of new users\njoining the scheme: consequently, a Ponzi scheme implodes soon after users stop\njoining it. Originated in the offline world 150 years ago, Ponzi schemes have\nsince then migrated to the digital world, approaching first the Web, and more\nrecently hanging over cryptocurrencies like Bitcoin. Smart contract platforms\nlike Ethereum have provided a new opportunity for scammers, who have now the\npossibility of creating "trustworthy" frauds that still make users lose money,\nbut at least are guaranteed to execute "correctly". We present a comprehensive\nsurvey of Ponzi schemes on Ethereum, analysing their behaviour and their impact\nfrom various viewpoints.\n

Luis Ibáñez, Elena Simperl, Fabien Gandon, Henry Story

The web was originally conceived as decentralized and universal, but during its popularization, its big value was built on centralized servers and nonuniversal access. A key element to redecentralize the web is to be able to generate trustable, secure, and accountable updates among autonomous participants without a central server. The authors believe that the marriage between distributed ledgers and linked data can provide this functionality and unlock the web's true potential. As a first step toward it, the authors propose a minimal vocabulary to describe and link distributed ledgers.

Majid Amjad Hussain, Sadia Khalil, Shahzad Saleem

With the increase in the use of virtual currencies across the globe, the security of Bitcoin wallets has become a serious concern for the Bitcoin community. The developers are trying to implement concrete security solutions in Bitcoin wallets to ensure that no vulnerability gets exploited. However, a large number of known, as well as zero-day attacks, are launched on the Bitcoin wallets on a daily basis, resulting in a loss of bitcoins. In this regard, this paper presents a security analysis of existing Android wallets. We demonstrate how the implemented security practices can be bypassed by malicious entities, causing financial loss to Bitcoin users. As a countermeasure, we present a smart card based authentication scheme which will protect the users from all of the identified attacks.

Gail‐Joon Ahn, Adam Doupé, Ziming Zhao, Kevin Liao

Introduction In 1989, the digital world was introduced to the PC Cyborg trojan horse (also known as the “AIDS” trojan), an impending game-changer in the cybercrime landscape. What later became known as a class of malware called ransomware, PC Cyborg was created by a biologist, Dr. Joseph Popp, who provided HIV/AIDS patients with infected floppy disks labeled “AIDS Information – Introductory Diskettes” (Kassner, 2010; Smith, 2002). Whenever PC Cyborg entered a system, it tracked the number of system boots until a threshold was met (typically 90 times), at which point it would hide and encrypt the names of all files and directories in the local drive of the infected system. PC Cyborg then prompted victims, whose computers were no longer operational, to send $189 to the PC Cyborg Corporation in order for the files to be decrypted and the computer to be reverted back to its working state.

Andres Baravalle, Mauro Sanchez Lopez, Sin Wee Lee

In the last years, governmental bodies have been futilely trying to fight against dark web marketplaces. Shortly after the closing of "The Silk Road" by the FBI and Europol in 2013, new successors have been established. Through the combination of cryptocurrencies and nonstandard communication protocols and tools, agents can anonymously trade in a marketplace for illegal items without leaving any record. This paper presents a research carried out to gain insights on the products and services sold within one of the larger marketplaces for drugs, fake ids and weapons on the Internet, Agora. Our work sheds a light on the nature of the market, there is a clear preponderance of drugs, which accounts for nearly 80% of the total items on sale. The ready availability of counterfeit documents, while they make up for a much smaller percentage of the market, raises worries. Finally, the role of organized crime within Agora is discussed and presented.

Ujan Mukhopadhyay, Anthony Skjellum, Oluwakemi Hambolu, Jon Oakley · 6 authors

Cryptocurrencies have emerged as important financial software systems. They rely on a secure distributed ledger data structure; mining is an integral part of such systems. Mining adds records of past transactions to the distributed ledger known as Blockchain, allowing users to reach secure, robust consensus for each transaction. Mining also introduces wealth in the form of new units of currency. Cryptocurrencies lack a central authority to mediate transactions because they were designed as peer-to-peer systems. They rely on miners to validate transactions. Cryptocurrencies require strong, secure mining algorithms. In this paper we survey and compare and contrast current mining techniques as used by major Cryptocurrencies. We evaluate the strengths, weaknesses, and possible threats to each mining strategy. Overall, a perspective on how Cryptocurrencies mine, where they have comparable performance and assurance, and where they have unique threats and strengths are outlined.

Ning Shi

Bitcoin system, when more than 51% computing power is controlled by a single node, the block chain can be distorted maliciously. This is called 51% attack which is a well-known potential risk that could destroy the Bitcoin system. The paper proves that under the current proof-of-work mechanism, computing power eventually will be centralized at a single node if miners are rational enough. The paper propose a new proof-of-work mechanism that improves decentralization and reduces the risk of 51% attack without increasing the risk of Sybil attack. This new mechanism introduces a series of principles such as Career open to all talents, without distinction of birth, Distribution according to labor and All Men are created equal.

Carlos Pinzón, Camilo Rocha

Bitcoin is a digital currency in which the need for a trusted third party is avoided. Instead, this digital currency is based on the concept of ‘proof of work’ allowing users to execute payments by digitally signing their transactions. Since electronic files can be duplicated, fraudulent transactions in the form of double-spend attacks – where users spend the same money at least twice – can happen. This paper is about attack models that can assign possible time advantage to attacker agents in the Bitcoin network. In particular, this paper presents: (i) two attack models in which partial advancement towards block production can be influenced by time and not only by the hashpower used to produce blocks of hashes, and (ii) algorithmic experimentation comparing these models against existing well-known hashrate-based attack models that do not consider time advantage. As a conclusion, this paper presents evidence on the fact that advantages are not negligible for cases in which an attacker has had enough time for secretly mining fraudulent blocks or significant control over the network. Also, the models presented in this paper help in supporting previous claims in the literature about how to correctly model and detect double-spend attacks in the Bitcoin network.

Yuanfeng Cai, Dan Zhu

The reputation system has been designed as an effective mechanism to reduce risks associated with online shopping for customers. However, it is vulnerable to rating fraud. Some raters may inject unfairly high or low ratings to the system so as to promote their own products or demote their competitors. This study explores the rating fraud by differentiating the subjective fraud from objective fraud. Then it discusses the effectiveness of blockchain technology in objective fraud and its limitation in subjective fraud, especially the rating fraud. Lastly, it systematically analyzes the robustness of blockchain-based reputation systems in each type of rating fraud. The detection of fraudulent raters is not easy since they can behave strategically to camouflage themselves. We explore the potential strengths and limitations of blockchain-based reputation systems under two attack goals: ballot-stuffing and bad-mouthing, and various attack models including constant attack, camouflage attack, whitewashing attack and sybil attack. Blockchain-based reputation systems are more robust against bad-mouthing than ballot-stuffing fraud. Blockchain technology provides new opportunities for redesigning the reputation system. Blockchain systems are very effective in preventing objective information fraud, such as loan application fraud, where fraudulent information is fact-based. However, their effectiveness is limited in subjective information fraud, such as rating fraud, where the ground-truth is not easily validated. Blockchain systems are effective in preventing bad mouthing and whitewashing attack, but they are limited in detecting ballot-stuffing under sybil attack, constant attacks and camouflage attack.

Jennifer Xu

In recent years, blockchain technology has attracted considerable attention. It records cryptographic transactions in a public ledger that is difficult to alter and compromise because of the distributed consensus. As a result, blockchain is believed to resist fraud and hacking. This work explores the types of fraud and malicious activities that can be prevented by blockchain technology and identifies attacks to which blockchain remains vulnerable. This study recommends appropriate defensive measures and calls for further research into the techniques for fighting malicious activities related to blockchains.

Tao-Hung Chang, Davor Svetinović

Financial transaction networks are some of the largest networks in existence. A relatively new type of financial networks is the digital (crypto) currency network, e.g., Bitcoin. Namecoin is an alternative crypto currency, based on Bitcoin, with additional features such as DNS. Namecoin network has more than 2 million nodes and almost 17 million edges. The analysis of such a crypto currency network can help us model or predict the future growth of the transaction networks. In order to analyze the transaction network graph over time, we analyzed the Namecoin blockchain data in 7 six months intervals. Our findings suggest different user behavior and developing pattern compared to Bitcoin.

Melissa Chase, Sarah Meiklejohn

In this paper, we initiate a formal study of transparency, which in recent years has become an increasingly critical requirement for the systems in which people place trust. We present the abstract concept of a transparency overlay, which can be used in conjunction with any system to give it provable transparency guarantees, and then apply the overlay to two settings: Certificate Transparency and Bitcoin. In the latter setting, we show that the usage of our transparency overlay eliminates the need to engage in mining and allows users to store a single small value rather than the entire blockchain. Our transparency overlay is generically constructed from a signature scheme and a new primitive we call a dynamic list commitment, which in practice can be instantiated using a collision-resistant hash function.

Roman Matzutt, Oliver Hohlfeld, Martin Henze, Robin Rawiel · 6 authors

As transaction fees skyrocket today, blockchains become increasingly expensive, hurting their adoption in broader applications. This work tackles the saving of transaction fees for economic blockchain applications. The key insight is that other than the existing "default'' mode to execute application logic fully on-chain, i.e., in smart contracts, and in fine granularity, i.e., user request per transaction, there are alternative execution modes with advantages in cost-effectiveness. On Ethereum, we propose a holistic middleware platform supporting flexible and secure transaction executions, including off-chain states and batching of user requests. Furthermore, we propose control-plane schemes to adapt the execution mode to the current workload for optimal runtime cost. We present a case study on the institutional accounts (e.g., coinbase.com) intensively sending Ether on Ethereum blockchains. By collecting real-life transactions, we construct workload benchmarks and show that our work saves 18%\sim 47%18%-47% per invocation than the default baseline while introducing 1.81%\sim 16.59%1.81%-16.59% blocks delay.

Youngbin Kim, Jun Gi Kim, Wook Kim, Jae Ho Im · 7 authors

This paper proposes a method to predict fluctuations in the prices of cryptocurrencies, which are increasingly used for online transactions worldwide. Little research has been conducted on predicting fluctuations in the price and number of transactions of a variety of cryptocurrencies. Moreover, the few methods proposed to predict fluctuation in currency prices are inefficient because they fail to take into account the differences in attributes between real currencies and cryptocurrencies. This paper analyzes user comments in online cryptocurrency communities to predict fluctuations in the prices of cryptocurrencies and the number of transactions. By focusing on three cryptocurrencies, each with a large market size and user base, this paper attempts to predict such fluctuations by using a simple and efficient method.

Jeong Kyu Lee, Seo Yeon Moon, Jong Hyuk Park

No abstract is available for this record.

Pallaw Singh, Anchit Bijalwan

No abstract is available for this record.

Affan Yasin, Lin Liu

In today's online environment, people attend various kinds of activities, exhibit different digital presence, build personal digital reputations, issuing and receiving feedbacks from online communities being involved with. These diverse information sources once aggregated can provide a valuablefuture reference for personal online digital identity and credits check. The primary objective of this paper is to propose a systematic framework for aggregating online identity and reputation information, to provide a holistic approach to personal online behavioral ratings. Major contributions include: An identity aggregation mechanism based on social dependency network is proposed, a smart contract management framework referring to personal online ratings based on the aggregated digital identity, an experiment implementation based on blockchain technology, with illustrative examples and theoretical evaluations to the proposed approach.

Richa Kaushal

Bitcoin is the latest addition to the online payment transaction systems. It is a digital currency also known as cryptocurrency. Bitcoin system is the first transaction payment system that deviated from the conventional approach of processing and clearing transactions though the trusted third parties and allowed direct transactions between parties. Thus making the whole system decentralized. It is a pure peer to peer network system which facilitates every party on the network to keep track of all the transactions that are taking place on the network. It uses Cryptography for its implementation and to deal with the internet security threats. This papers aims to explore the need of the decentralized system, technology used for its implementation and also the key features of bitcoin system that makes it so unique as compared to the conventional currency. It also throws the light on the benefits of bitcoin system and its shortcomings.

Upadhyaya Rhyme, Aruna Jain

Future wars will be cyber wars and the attacks will be a sturdy amalgamation of cryptography along with malware to distort information systems and its security. The explosive Internet growth facilitates cyber-attacks. Web threats include risks, that of loss of confidential data and erosion of consumer confidence in e-commerce. The emergence of cyber hack jacking threat in the new form in cyberspace is known as ransomware or crypto virus. The locker bot waits for specific triggering events, to become active. It blocks the task manager, command prompt and other cardinal executable files, a thread checks for their existence every few milliseconds, killing them if present. Imposing serious threats to the digital generation, ransomware pawns the Internet users by hijacking their system and encrypting entire system utility files and folders, and then demanding ransom in exchange for the decryption key it provides for release of the encrypted resources to its original form. We present in this research, the anatomical study of a ransomware family that recently picked up quite a rage and is called CTB locker, and go on to the hard money it makes per user, and its source C&C server, which lies with the Internet's greatest incognito mode-The Dark Net. Cryptolocker Ransomware or the CTB Locker makes a Bitcoin wallet per victim and payment mode is in the form of digital bitcoins which utilizes the anonymity network or Tor gateway. CTB Locker is the deadliest malware the world ever encountered.

Ahmad Karim, Rosli Salleh, Muhammad Khurram Khan

Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks' back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps' detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies.

Jing Li, Qin Qin, Yu Zhang

This document established the main factors of bitcoin risk perception based on the explorative factor analysis, then studied them using structural equation model and conducted one-order and second-order confirmatory factor analysis. The results show that the bitcoin perceived risk mainly includes four aspects: bitcoin technology and security risk, national policy and legal risks, social risks, bitcoin market and transaction risk, the risk perception has correlation on each other. Based on the model, the author put forward the corresponding policy recommendations.

Martina Matta, Maria Ilaria Lunesu, Michele Marchesi

No abstract is available for this record.

Judyta Przyłuska-Schmitt

No abstract is available for this record.