Lei Wu, Yufeng Hu, Yajin Zhou, Haoyu Wang · 8 authors
One reason for the popularity of Bitcoin is due to its anonymity. Although several heuristics have been used to break the anonymity, new approaches are proposed to enhance its anonymity at the same time. One of them is the mixing service. Unfortunately, mixing services have been abused to facilitate criminal activities, e.g., money laundering. As such, there is an urgent need to systematically understand Bitcoin mixing services. In this paper, we take the first step to understand state-of-the-art Bitcoin mixing services. Specifically, we propose a generic abstraction model for mixing services and observe that there are two mixing mechanisms in the wild, i.e. {swapping} and {obfuscating}. Based on this model, we conduct a transaction-based analysis and successfully reveal the mixing mechanisms of four representative services. Besides, we propose a method to identify mixing transactions that leverage the obfuscating mechanism. The proposed approach is able to identify over $92$\% of the mixing transactions. Based on identified transactions, we then estimate the profit of mixing services and provide a case study of tracing the money flow of stolen Bitcoins.
Inspired from the iForest algorithmic scheme, we propose an iForest-based blockchain social media anomaly behavior detection method via the improved tree algorithm, for the purpose of isolating the anomalous behaviors as an outlier. The model is integrated with the smart contract structure of blockchain. In the overall system, the user data is sent to the intelligent contract for a period of time. After the identification of the abnormal behavior of social media users, the abnormal behavior in blockchain is marked and stored in the abnormal chain. To a certain extent, the scheme protects users' privacy, improves the efficiency and accuracy of iForest anomaly detection, and is more suitable for multi-dimensional heterogenous data-centric social media user behavior detection.
Suhani Jattan, Vineeth Kumar, R Akhilesh, Rachith R Naik · 5 authors
In today's world, more importance is given on the availability of the applications and various websites available in the digital market. People will manage their daily work on time, precisely, very fast, and with satisfaction. So various technologies are used to fulfil daily work. In India, there is no direct and efficient way of communication between the government and the public, for solving a problem i.e for getting a problem solved at any place, people may have to wait for three months, but it can probably be solved sooner. Nowadays, the scenario has changed. Many applications are available, which allow users to register their complaints. But there are some problems related to its transparency. This paper proposes an Ethereum blockchain application that will help people to register their complaints and get updates about the complaint. Adoption of blockchain technology makes the application more secure, transparent and immutable.
Social media networks (SMNs) have acquired rapid development in recent years as they can provide better channel for fast information spreading. However, some false information and rumor released or propagated in SMNs have become a series social problem. Therefore, a novel rumor prevention model based on blockchain is proposed in this paper. In the model, rumor detection system and voting rule are used to judge the kind of the message released in SMNs, social media runner and some specific nodes with important influence can undertake the work of validation of information and writing to the blockchain. Once the message is judged to be rumor, it is forbidden relaying by other users. The proposed private blockchain and its consensus mechanism can guarantee the rapid processing of transactions; the relayed information from news the resources can be verified through IP address visiting. The person often releases false information can be exposed between different SMNs, this can effectively prevent the spreading of rumor. Some analyses and discussions on the strength of the proposed model are given to show the better feasibility and scalability of the proposed model.
Smart contract-enabled blockchains allow building decentralized applications in which mutually-distrusted parties can work together. Recently, oracle services emerged to provide these applications with real-world data feeds. Unfortunately, these capabilities have been used for malicious purposes under what is called criminal smart contracts. A few works explored this dark side and showed a variety of such attacks. However, none of them considered collaborative attacks against targets that reside outside the blockchain ecosystem. In this paper, we bridge this gap and introduce a smart contract-based framework that allows a sponsor to orchestrate a collaborative attack among (pseudo)anonymous attackers and reward them for that. While all previous works required a technique to quantify an attacker's individual contribution, which could be infeasible with respect to real-world targets, our framework avoids that. This is done by developing a novel scheme for trustless collaboration through betting. That is, attackers bet on an event (i.e., the attack takes place) and then work on making that event happen (i.e., perform the attack). By taking DDoS as a usecase, we formulate attackers' interaction as a game, and formally prove that these attackers will collaborate in proportion to the amount of their bets in the game's unique equilibrium. We also model our framework and its reward function as an incentive mechanism and prove that it is a strategy proof and budget-balanced one. Finally, we conduct numerical simulations to demonstrate the equilibrium behavior of our framework.
Social networks such as Twitter contain billions of data of users, and in every second, a large number of tweets trade through Twitter. Sentiment analysis is the way toward deciding the emotional tone behind a series of words that users utilize to understand the attitudes, thoughts, and emotions that are enunciated in online references on Twitter. This chapter aims to determine the user preference of Bitcoin and Ethereum, which are the two most popular cryptocurrencies in the world by using the Twitter sentiment analysis. It proposes a powerful and fundamental approach to identify emotions on Twitter by considering the tweets of these two distinctive cryptocurrencies. One hundred twenty thousand (120,000) tweets were extracted separately from Twitter for each keyword Bitcoin/BTC and Bitcoin/ETC between the period from 12/09/2018 to 22/09/2018 (10 days).
Prashansa Agrawal, Parwat Singh Anjana, Sathya Peri
The surge in the spread of misleading information, lies, propaganda, and false facts, frequently known as fake news, raised questions concerning social media's influence in today's fast-moving democratic society. The widespread and rapid dissemination of fake news cost us in many ways. For example, individual or societal costs by hampering elections integrity, significant economic losses by impacting stock markets, or increases the risk to national security. It is challenging to overcome the spreading of fake news problems in traditional centralized systems. However, Blockchain-- a distributed decentralized technology that ensures data provenance, authenticity, and traceability by providing a transparent, immutable, and verifiable transaction records can help in detecting and contending fake news. This paper proposes a novel hybrid model DeHiDe: Deep Learning-based Hybrid Model to Detect Fake News using Blockchain. The DeHiDe is a blockchain-based framework for legitimate news sharing by filtering out the fake news. It combines the benefit of blockchain with an intelligent deep learning model to reinforce robustness and accuracy in combating fake news's hurdle. It also compares the proposed method to existing state-of-the-art methods. The DeHiDe is expected to outperform state-of-the-art approaches in terms of services, features, and performance.
Ikra Afzal Chesti, Mamoona Humayun, Najm Us Sama, N. Z. Jhanjhi
Tremendous growth of ransom malware demands valuable security methods to protect individuals and organizations. Ransomware or ransom malware is a type of malware that restricts users from accessing their files or system and demands a ransom payment to get back access to files. The hacked files are encrypted and asked for payment to decrypt and redeliver the files back to the user. To regain access back to hacked files one has to make digital payment. Ransomware of this type is dangerous as it hacks all the files and fails all the security methods available on the system also the possibility for retrieving your file is zero percent. Even if the payment is done still one cannot be sure that files will be delivered back to the user. The earliest ransomware came into existence in 1980, at that time one has to pay through snail mail. Ransomware is considered as the most widespread malware since 1989 and had caused global financial losses both to individuals and big organizations. Every year this loss is increasing. Therefore, protection of our data from ransomware is necessary. Today, originators of ransomware demand for payment via bitcoins or cryptocurrency. This paper provides the detailed overview about ransomware, its evolution, the reasons for paying or not paying a ransom, the existing approaches to avoid this problem, and the recovery techniques in case of infection.
It is widely accepted that Ethereum mining is highly centralized.\nNonetheless, centralization has been mostly characterized by exclusively\nlooking at the influence that independent miners or mining pools can have over\nthe network. Moreover, models of mining behavior assume that miners are either\nunrelated or only relate via mining pools under highly structured and\ntransparent agreements. If these assumptions and the predictions they entail\nwere to be completely accurate, there would not be any evidence of on-chain\ntransactions between miners, other than the ones expected from mining pool\npayouts. By looking at on-chain transactions between miners in the Ethereum\nNetwork we find that aside from the payouts from mining pools to small miners,\nthere are also transactions that define relationships between mining pools,\nindependent miners and between independent miners and mining pools.\nFurthermore, by characterizing the topology of the network of miner\ntransactions, we find the emergence of highly connected clusters that control\nsignificant amounts of hashing power and exhibit relationships in the opposite\ndirection of what theoretical models predict. This more nuanced\ncharacterization of mining centralization can help identify network\nvulnerabilities and inform protocol redesigns.\n
This research is dedicated to the development of a prototype of open infrastructure for users' internet traffic filtering on a browser level. We described the advantages of a distributed approach in comparison with current centralized solutions. Besides, we suggested a solution to define the optimum size for a URL storage block in Ethereum network. This solution may be used for the development of infrastructure of DApps applications on Ethereum network in future. The efficiency of the suggested approach is supported by several experiments.
As blockchain solutions become widespread, identifying potential bugs in smart contracts written in Solidity language will be important for these solutions to work correctly. To accurately detect these bugs, the developer must use several state-of-the-art bug detection tools and investigate the potential bugs they report. In this study, we first show that one tool is not enough to detect all the bugs as our Static Analysis for Solidity tool (SA-Solidity) and the known SmartCheck and Securify tools identify different bugs in SmartEmbed's experimental set of smart contracts. Then, we develop Machine Learning-based Bug Predictor for Solidity (MLBP-Solidity) which predicts files that would be reported by all the previous bug detection tools. MLBP-Solidity eases the burden on the developer by allowing him/her to focus on a subset of files that are most probably buggy. Our experimental results show that MLBP-Solidity achieves 91-99% accuracy, depending on the type of predicted bug.
Yamuna Rosasooria, Abd Kadir Mahamad, Sharifah Saon, Mohd Anuar Mat Isa · 6 authors
Electronically voting process without paper and the ballot box, namely electronic voting (e-voting), required some improvement, especially in terms of security elements. This is against the anonymize properties of the e-voting system. Therefore, a blockchain e-voting system was proposed which have a secure and transparency features to deploy during the Student Representative Council (SRC) election in Universiti Tun Hussein Onn Malaysia (UTHM). Blockchain technology ensured all aspects such as transparency, security, and auditability were achieved without sacrificing the privacy of voters. In this study, e-voting using a blockchain system was developed to detect the fraud that occurs during the voting session using Solidity language. A total of 3 cases were analyzed and a questionnaire was done to evaluate the proposed system. Analysis of respondents gave positive perception with a mean value of 4.5, 4.6, and 4.9, for 1st, 2nd,and 3rdCase respectively. To sum up, the proposed system can shorter the time for the voting process and diminishes the expense because of no need to print out the ballot.
E-cash and cryptocurrency schemes have been a focus of applied cryptography for a long time. However, we acknowledge the continuing need for a cryptographic protocol that provides global scale, decentralized, secure, and fair delivery of donations. Such a protocol would replace central trusted entities (e.g., charity organizations) and guarantee the privacy of the involved parties (i.e., donors and recipients of the donations). In this work, we target this online donation problem and propose a practical solution for it. First, we propose a novel decentralized e-donation framework, along with its operational components and security definitions. Our framework relies on a public ledger that can be realized via a distributed blockchain. Second, we instantiate our e-donation framework with a practical scheme employing privacy-preserving cryptocurrencies and attributebased signatures. Third, we provide implementation results showing that our operations have feasible computation and communication costs. Finally, we prove the security of our e-donation scheme via formal reductions to the security of the underlying primitives.
With the increasing popularity of blockchain technology, it has also become a hotbed of various cybercrimes. As a traditional way of scam, the phishing scam has new means of scam in the blockchain scenario and swindles a lot of money from users. In order to create a safe environment for investors, an efficient method for phishing detection is urgently needed. In this paper, we propose a three steps framework to detect phishing scams on Ethereum by mining Ethereum transaction records. First, we obtain the labeled phishing accounts and corresponding transaction records from two authorized websites. According to the collected transaction records we build an Ethereum transaction network. Then, a network embedding method node2vec which can extract the latent features of accounts is used for subsequent phishing classification. Finally, to distinguish whether the account is a phishing account, we adopt the one-class support vector machine (SVM) to classify. The experimental result demonstrates that F-score of our phishing detection method can achieve 0.846, which verifies the validity of our model. To the best of our knowledge, this is the first work that investigates the phishing scams on Ethereum based on transaction records.
The blockchain is a distributed ledger technology that is growing in importance since inception. Besides cryptocurrencies, it has also crossed its boundary inspiring various organizations, enterprises, or business establishments to adopt this technology benefiting from the most innovative security features. The decentralized and immutable aspects have been the key points that endorse blockchain as one of the most secure technologies at the present time. However, in recent times such features seemed to be faded due to new attacking techniques. One of the biggest challenges remains within the consensus protocol itself, which is an essential component to bring all network participants to an agreed state. Cryptocurrencies adopt suitable consensus protocols based on their mining requirement, and Proof of Work (PoW) is the consensus protocol that is being predominated in major cryptocurrencies. Recent consensus protocol-based attacks, such as the 51% attack, Selfish Mining, Miner Bribe Attack, Zero Confirmation Attack, and One Confirmation Attack have been demonstrated feasible. To overcome these attacks, we propose Proof of Adjourn (PoAj), a novel consensus protocol that provides strong protection regardless of attackers hashing capability. After analyzing the 5 major attacks, and current protection techniques indicating the causes of their failure, we compared the PoAj against the most widely used PoW, showing that PoAj is not only able to mitigate the 5 attacks but also attacks relying on having a large amount of hashing power. In addition, the proposed PoAj showed to be an effective approach to mitigate the processing time issue of large-sized transactions. PoAj is not tailored to any particular attack; therefore, it is effective against malicious powerful players. The proposed approach provides a strong barrier not only to current and known attacks but also to future unknown attacks based on different strategies that rely on controlling the majority of the hashing power.
Franklin Tchakounté, Koudanbe Amadou Calvin, Ado Adamou Abba Ari, David Jaurès Fotsa-Mbogne
One of the main concerns of cybersecurity is the detection of hoaxes across social media. Hoaxers propagate such messages to mislead users and to promote violence. Several approaches exist in literature to address this issue. They are mainly limited to detect hoax activities by characterizing the message nature and detecting provenance of messages. However, unless hoaxes are detected, they continue to propagate across social media nodes. This work aims at reducing the dissemination of hoaxes across group of users. Relying on social graph structure, this research develops a mechanism based on smart contract logics to prevent a group to consume a fake post. To achieve this objective, we used a smart contract to exploit a trust index computed based on message characteristics and group features such as graph density, group status, group degree, group acceptability. Based on the value of trust index, the message is forwarded or blocked. Experiments realized on groups of different characteristics revealed that the proposed smart contract is even able to reactively block a fake post of the same nature than the group type. Results indicate that the proportion of targeted groups could be reduced even if their interests match with the message subject. This research is an important step forward to anti-promote hoaxes with the novelty of exploiting smart contract approach to contain their propagation.
In today's social media context, many criticalities have emerged, particularly concerning the security of users' personal data and the unbalanced redistribution of the value generated. This work, analyzing 40 emerging platforms, investigates how Blockchain technology is reshaping the social media scenario through transparency, value redistribution, ownership awareness, decentralization of data, and censorship resistance.
M S Bhargavi, Sushmitha M Katti, M Shilpa, Vaishnavi P Kulkarni · 5 authors
Ethereum is a blockchain based development platform for users to build and deploy decentralized applications and smart contracts. Transactions substituting money over Ethereum space are carried out using Ethereum's cryptocurrency `Ether'. Though the decentralization and public ledger recording of the transactions proves its limpidity, the anonymity of the users, hiding their true identity behind the addresses echoes the need for discerning the behavioural traits in transactions. The appalling nature of Ethereum transactions to have both, security and threat at a comparable level, demands analytics for inferring traits for better perspectives and insights. This research work focuses on characteristic analysis of Ethereum transaction space for inferring behavioural traits in supervised and unsupervised context. In an unsupervised environment, raw transaction data is extradited to a tabular transaction structure by selecting appropriate features. The data is further clustered and validated to form coherent groupings of similar patterns. The clusters are characteristically analyzed based on the features through Radar plots for inferring behavioural traits. In supervised context, labelled transactions are represented using histograms and feature-based characteristic analysis is performed to infer traits. Such analytics lay foundations for future deeper analysis that can be used to discover trends and patterns to understand the transaction network, enhancement of trading strategies, identification of bot activities, anomaly detection and several others.
The coronavirus disease 2019 (COVID-19) outbreak has created a great challenge for many industries, including healthcare systems, E-commerce, and transportation. Cryptocurrencies, such as Bitcoin (BTC), is an alternative class of digital assets primarily used as a medium of exchange. In the financial market, data collected from social media such as tweets, posts, and can assist in an early indication of market sentiment. This has frequently been conducted on Twitter data. In particular, this paper provides a corpus of tweet text for Bitcoin-related tweets during the summer of the COVID-19 era. This dataset is publicly available covering a considerable period of roughly three months, to allow people with a similar interest in Twitter, Bitcoin, sentiment analysis, and the financial sector to perform research unimpeded.
Mohamed Fartitchou, Khalid El Makkaoui, Nabil Kannouf, Zakaria El Allali
Block chain (BC) is a relatively new technology; which has attracted much attention recently. It has been developed rapidly and can be used in many applications of various domains such as decentralized approaches. Indeed, many companies, even worldwide governments, are now using BC technology to improve the security, scalability, and efficiency of their services. In this paper, we provide an overview of BC security. We start with the basics of BC technology. Next, we give the primary BC security attacks. Finally, we present the BC countermeasures.
Blockchain Technology Applications and Security
Spam and Phishing Detection
Advanced Steganography and Watermarking Techniques