Cryptocurrencies are getting massive momentum in the last few years. Cryptocurrencies depend upon a secure distributed ledger called blockchain which stores blocks in a secure and chronological order. Although a large cryptocurrencies wallet management scheme has been proposed but they suffer from weak security. Thus effective cryptocurrency key management has become a much needed requirement for modern cryptocurrencies. In this paper, we propose a more effective, usable and secure cryptocurrency key management system named rashi that provides security enhanced storage, no password authentication. The performance analysis shows that our proposed system requires minimal additional overhead and has low time delays, enhanced security and efficient real -world deployment.
Abstract Web-based cryptocurrency mining attacks, also known as cryptojacking, become increasingly popular. A large number of diverse platforms (e.g., Windows, Linux, Android, and iOS) and devices (e.g., PC, smartphones, tablets, and even critical infrastructures) are widely impacted. Although a variety of detection approaches were recently proposed, it is challenging to apply these approaches to attack prevention directly. Instead, in this paper, we present a novel generic and accurate defense solution, called “MinerGate”, against cryptojacking attacks. To achieve the goal, MinerGate is designed as an extension of network gateways or proxies to protect all devices behind it. When attacks are identified, MinerGate can enforce security rules on victim devices, such as stopping the execution of related JavaScript code and alerting victims. Compared to prior approaches, MinerGate does not require any modification of browsers or apps to collect the runtime features. Instead, MinerGate focuses on the semantics of mining payloads (usually written in WebAssembly/asm.js), and semantic-based features. In our evaluation, we first verify the correctness of MinerGate by testing MinerGate in a real environment. Then, we check MinerGate’s performance and confirm MinerGate introduces relatively low overhead. Last, we verify the accuracy of MinerGate. For this purpose, we collect the largest WebAssembly/asm.js related code with ground truth to build our experiment dataset. By comparing prior approaches and MinerGate on the dataset, we find MinerGate achieves better accuracy and coverage (i.e., 99% accuracy and 98% recall). Our dataset will be available online, which should be helpful for more solid understanding of cryptojacking attacks.
Blockchain systems are designed to produce blocks at a constant average rate. The most popular systems currently employ a Proof of Work (PoW) algorithm as a means of creating these blocks. An unfortunate limitation of all deployed PoW blockchain systems is that the time between blocks has high variance. For example, Bitcoin produces, on average, one block every 10 minutes. However, 5% of the time, Bitcoin's inter-block time is at least 30 minutes.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Jan 1, 2020·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Vikram Kanth, Ashley McaAbee, Murali Tummala, John McEachen
As the threat of cyber attack grows ever larger, new approaches to security are required. While there are several different types of intrusion detection systems (IDS), collaborative IDS (CIDS) offers particular promise in identifying distributed, coordinated attacks that might otherwise elude detection. Even for CIDS, there are unresolved issues associated with trusting participants and aggregating data. Blockchain technology appears capable of addressing those issues if practical implementation strategies can be developed. To that end, we implement an Ethereum blockchain-based CIDS leveraging pluggable authentication modules. Our system is specifically crafted to detect doorknob rattling attacks by immutably recording login activity in a blockchain-protected ledger.
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.
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.
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.
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.
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.
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.
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.
The pool-hopping attack casts down the expected profits of both the mining pool and honest miners in Blockchain. The mainstream countermeasures, namely PPS (pay-per-share) and PPLNS (pay-per-last-N-share), can hedge pool hopping, but pose a risk to the pool as well as the cost to miners. In this study, we apply the zero-determinant (ZD) theory to design a novel pooled mining which offers an incentive mechanism for motivating non-memorial and memorial evolutionary miners not to switch in pools strategically. In short, our hopping-proof pooled mining has three unique features: 1) fee-free. No fee is charged if the miner does not hop. 2) wide applicability. It can be employed in both prepaid and postpaid mechanisms. 3) fairness. Even the pool can dominate the game with any miner, he has to cooperate when the miner does not hop among pools. The fairness of our scheme makes it have long-term sustainability. To the best of our knowledge, we are the first to propose a hopping-proof pooled mining with the above three natures simultaneously. Both theoretical and experimental analyses demonstrate the effectiveness of our scheme.
Jaehong Ahn, Mingyu Park, Hyungsik Shin, Jeongyeup Paek
E-commerce has become a crucial part of our life allowing us to buy products, request services, and transfer money easily with a press of a button. As such, establishing immutable trust and reputation of entities that are resilient to manipulation by the malicious are critical in today’s online systems. In this work, we propose a model for calculating trust and reputation using the values stored on blockchain ledger. The model is applied to blockchain-based online payment systems which have a characteristic of immutability by preventing data manipulation. The model normalizes user evaluations based on each user’s personal evaluation criteria that changes over time. In addition, the model derives reputation of, and trust between, users by applying psychological factors. We evaluate our model using not only simulated transaction data but also on real Bitcoin transaction-based dataset to show that our model is able to derive stable values from immutable transactions on blockchain-based online payment systems. Our model has been built into a live commercial blockchain service platform, and new application developments are underway.
The proliferation of unreliable and biased information is a significant\nproblem on the Internet. To assess the credibility of the information retrieved\nfrom news websites and other sources, users often resort to social platforms\nlooking for confirmation with trustworthy parties. However, users may be faced\nwith considerable obstacles posed by the platform provider, who can prevent\naccess to certain content. This paper presents DClaims, a system that provides\na censorship-resistant distributed service for the exchange of information over\nthe Internet using web annotations. DClaims' fully decentralized architecture\nrelies on Inter-Planetary File System (IPFS) and Ethereum blockchain, both of\nwhich offer desirable censorship resistant properties. DClaims is implemented\nas a web annotations browser extension which allows for the classification of\nnews articles, on news websites. From our evaluation of the system, we conclude\nthat a large scale implementation of the system is practical and economically\nviable.\n
A U Mentsiev, V S Magomadov, M Z Ashakhanova, A U Mentsiev · 5 authors
Abstract This research gives a brief insight into one of the most widely used technologies known as Blockchain. The paper lays the groundwork of how Blockchain functions and how it has quickly become a network with millions of users throughout the world. This study discusses the most important use of Blockchain technology, which is the enhancement of the cyber-security industry. Blockchain has revolutionized the cyber-security industry by introducing a system which is not bound to any four walls and is widely distributed all around the world, seeking refuge on millions of user servers. This decentralized system helps Blockchain defend cyber networks against security threats and attacks such as malware, phishing attacks, and DDoS.
Temidayo Abayomi-Zannu, Isaac Odun-Ayo, T. F. Barka
Abstract Voting is fundamental to any consensus-based society and is one of the most critical functions of democracy. Mobile voting (m-voting) was utilized as a means for voters to easily and conveniently cast their votes using their mobile devices which have been the most adopted means of communication but has a major problem which is safely securing the casted votes and avoiding any form of tampering. In this paper, we propose an m-voting framework that utilizes blockchain technology to securely store the casted votes and multi-factor authentication to authenticate the voters before they cast their votes while also providing an easily accessible, secure and transparent m-voting system.
Abstract The paper proposes the exploration, identification and development of a Java solution for extracting the sentiment related to the cryptocurrencies phenomenon, from the content of the posts of certain popular social networks. Detecting the positive, neutral or negative character of the sentiment is adopted as a relevant method of establishing the nature of the human perception on the topical issue defined by cryptocurrencies.
Executing, verifying and enforcing credible transactions on permissionless blockchains is done using smart contracts. A key challenge with smart contracts is ensuring their correctness and security. To address this challenge, we present a fully automated technique, SolAnalyser, for vulnerability detection over Solidity smart contracts that uses both static and dynamic analysis. Analysis techniques in the literature rely on static analysis with a high rate of false positives or lack support for vulnerabilities like out of gas, unchecked send, timestamp dependency. Our tool, SolAnalyser, supports automated detection of 8 different vulnerability types that currently lack wide support in existing tools, and can easily be extended to support other types. We also implemented a fault seeding tool that injects different types of vulnerabilities in smart contracts. We use the mutated contracts for assessing the effectiveness of different analysis tools. Our experiment uses 1838 real contracts from which we generate 12866 mutated contracts by artificially seeding 8 different vulnerability types. We evaluate the effectiveness of our technique in revealing the seeded vulnerabilities and compare against five existing popular analysis tools - Oyente, Securify, Maian, SmartCheck and Mythril. This is the first large scale evaluation of existing tools that compares their effectiveness by running them on a common set of contracts. We find that our technique outperforms all five existing tools in supporting detection of all 8 vulnerability types and in achieving higher precision and recall rate. SolAnalyser was also faster in analysing the different vulnerabilities than any of the existing tools in our experiment.
Abeer ElBahrawy, Laura Alessandretti, Leonid Rusnac, Daniel Goldsmith · 6 authors
Dark markets are commercial websites that use Bitcoin to sell or broker transactions involving\ndrugs, weapons, and other illicit goods. Being illegal, they do not offer any user protection, and\nseveral police raids and scams have caused large losses to both customers and vendors over the past\nyears. However, this uncertainty has not prevented a steady growth of the dark market phenomenon\nand a proliferation of new markets. The origin of this resilience have remained unclear so far, also due\nto the difficulty of identifying relevant Bitcoin transaction data. Here, we investigate how the dark\nmarket ecosystem re-organises following the disappearance of a market, due to factors including raids\nand scams. To do so, we analyse 24 episodes of unexpected market closure through a novel datasets\nof 133 million Bitcoin transactions involving 31 dark markets and their users, totalling 4 billion USD.\nWe show that coordinated user migration from the closed market to coexisting markets guarantees\noverall systemic resilience beyond the intrinsic fragility of individual markets. The migration is\nswift, efficient and common to all market closures. We find that migrants are on average more active\nusers in comparison to non-migrants and move preferentially towards the coexisting market with\nthe highest trading volume. Our findings shed light on the resilience of the dark market ecosystem\nand we anticipate that they may inform future research on the self-organisation of emerging online\nmarkets.