Son yıllarda, bloglar, tweet’ler, forumlar, e-postalar gibi Web 2.0 hizmetleri iletişim kanalı olarak yaygın bir şekilde kullanılmaktadır. Ayrıca sosyal medya; gerek bilgi paylaşımı gerekse istek, şikayet ve dilekler gibi görüşleri belirtmenin en kolay ve en güncel yolu olarak düşünülmektedir. Sosyal medyanın, birçok alana olduğu gibi Bitcoin fiyatlarına olan etkisi de son yıllarda tartışılmaktadır. Bitcoin yıllardır üzerinde durulan ve popülerliği her geçen gün artan bir yatırım aracıdır. Merkezi olmayan bir elektronik para birimi sistemi olan Bitcoin, çok sayıda kullanıcının ilgisini çeken, finansal sistemlerdeki köklü bir değişikliği ifade etmektedir. Bu çalışmada sosyal medyanın, özellikle Twitter kanalından elde edilen tweet’ler bazında, Bitcoin fiyatı ile etkileşimi ortaya konulmuştur. Bunun için 06.10.2018-19.05.2019 tarihleri arasında Twitter kullanıcıları tarafından atılan toplam 2.819.784 tweet üzerinden makine öğrenmesi yöntemlerinden sınıflandırma algoritmaları kullanılarak çeşitli analizler gerçekleştirilmiştir. Bulgular değerlendirildiğinde metin sınıflandırmada %90 ile en yüksek doğruluk oranına sahip olan Yapay Sinir Ağları kullanılmıştır. Ayrıca Bitcoin fiyatları ve sınıflandırılmış olumlu/olumsuz tweet oranları ile ikili korelasyon yapılmıştır. Elde edilen 0,681 korelasyon katsayısı ile pozitif yönde orta üstü kuvvetli ilişki tespit edilmiştir.
Currently, there are hundreds of Bitcoin exchanges on the market, so choosing a reliable exchange is a critical issue for users. We know that the amount of Bitcoin holdings is an essential indicator for evaluating an exchange, but people have very few ways to access this information. Besides, many reports indicate that the trading volumes of most Bitcoin exchanges do not match their real situations, and the fake volume has become an unspoken rule of the whole industry. It causes the public to doubt the actual amount of Bitcoin owned by each exchange. To solve the problem of information asymmetry between users and exchanges, we propose a method for tagging Bitcoin addresses of exchanges. Through vertical, forward, and backward address mining, the method can utilize only one or several addresses of an exchange to find out all its addresses and distinguish different address types: deposit wallet, hot wallet, and cold wallet. Then the balance and transfers of the exchange can be further obtained through these addresses, helping users understand the real Bitcoin holdings of the exchange. Several experiments are conducted to evaluate the effectiveness of the proposed Bitcoin address tagging method. Our method has very little dependence on off-chain information. Only one address is needed for each exchange as a seed to find out all the other addresses. Such a seed address can be easily obtained by depositing some Bitcoin into the exchange or withdrawing some from it, which makes our method feasible for all exchanges.
Due to the decentralization, irreversibility, and traceability, blockchain has attracted significant attention and has been deployed in many critical industries such as banking and logistics. However, the micro-architecture characteristics of blockchain programs still remain unclear. What's worse, the large number of micro-architecture events make understanding the characteristics extremely difficult. We even lack a systematic approach to identify the important events to focus on. In this paper, we propose a novel benchmarking methodology dubbed BBS to characterize blockchain programs at micro-architecture level. The key is to leverage fuzzy set theory to identify important micro-architecture events after the significance of them is quantified by a machine learning based approach. The important events for single programs are employed to characterize the programs while the common important events for multiple programs form an importance vector which is used to measure the similarity between benchmarks. We leverage BBS to characterize seven and six benchmarks from Blockbench and Caliper, respectively. The results show that BBS can reveal interesting findings. Moreover, by leveraging the importance characterization results, we improve that the transaction throughput of Smallbank from Fabric by 70% while reduce the transaction latency by 55%. In addition, we find that three of seven and two of six benchmarks from Blockbench and Caliper are redundant, respectively.
Authenticating a person's identity has always been a challenge. While attempts are being made by government agencies to address this challenge, the citizens are being exposed to a new age problem of Identity management. The sharing of photocopies of identity cards in order to prove our identity is a common sight. From score-card to Aadhar-card, the details of our identity has reached many unauthorized hands during the years. In India the identity thefts accounts for 77% [1] of the fraud cases, and the threats are trending. Programs like e-Residency by Estonia[2], Bitnation using Ethereum[3] are being devised for an efficient Identity Management. Even the US Home Land Security is funding a research with an objective of “Design information security and privacy concepts on the Blockchain to support identity management capabilities that increase security and productivity while decreasing costs and security risks for the Homeland Security Enterprise (HSE).” [4] This paper will discuss the challenges specific to India around Identity Management, and the possible solution that the Distributed ledger, hashing algorithms and smart contracts can offer. The logic of hashing the personal data, and controlling the distribution of identity using public-private keys with Blockchain technology will be discussed in this paper.
Blockchain implementation brought several benefits to many areas. One of the usages of blockchain is in digital currencies. Digital currency (cryptocurrency) is a new era for the global financial system. Cryptocurrencies draw significant attention from researchers because of their advantages. Although there are several risks (e.g., speculation, 51% attack) related to cryptocurrency, billions of dollars are invested in them, because of their transparency, traceability, low transaction cost, and highly profitable potential. In December 2017, the most famous cryptocurrency, Bitcoin, has reached almost $20,000.00 per coin. Such short-term, high gain potential attracts many new small investors. However, speculative movements raise many questions related to the safety and privacy of investors, just to name a few. To understand public opinions about cryptocurrency and speculative movements to protect small investors financial interests, sentiment analysis can be done by using social media activities of individuals who are interested or investing in cryptocurrencies. It is also one of the essential steps in the analysis to understand the profiles of the users. Therefore, in this paper, we determine the attitudes of social network users by analyzing the positivity and negativity of the comments about six cryptocurrencies. Results show that the positivity is higher than negativity, and there exist relations between price changes and attitudes. However, relations vary according to currency types. The results and analysis, which are provided in this paper, help new investors and developers to obtain opinions of social network users who are interested or investing in cryptocurrency.
Ethereum Smart contracts use blockchain to transfer values among peers on networks without central agency. These programs are deployed on decentralized applications running on top of the blockchain consensus protocol to enable people to make agreements in a transparent and conflict-free environment. The security vulnerabilities within those smart contracts are a potential threat to the applications and have caused huge financial losses to their users. In this paper, we present a framework that combines static and dynamic analysis to detect Reentrancy vulnerabilities in Ethereum smart contracts. This framework generates an attacker contract based on the ABI specifications of smart contracts under test and analyzes the contract interaction to precisely report Reentrancy vulnerability. We conducted a preliminary evaluation of our proposed framework on 5 modified smart contracts from Etherscan and our framework was able to detect the Reentrancy vulnerability in all our modified contracts. Our framework analyzes smart contracts statically to identify potentially vulnerable functions and then uses dynamic analysis to precisely confirm Reentrancy vulnerability, thus achieving increased performance and reduced false positives.
Popular Blockchain-based cryptocurrencies, like Bitcoin, are increasingly being used maliciously for illegal trades. In order to trace and analyze suspected Bitcoin transactions and addresses, address clustering methods and Bitcoin flow analysis methods are gaining attention recently. However, existing methods only focus on Bitcoin addresses and flow, and neglect other important information, such as transaction structure and behavior features. In order to exploit all useful features of transactions, this paper proposes a Bitcoin transaction network analytic method for facilitating Blockchain forensic investigation based on an extended safe Petri Net. The structural features and dynamic semantics of Petri net are used in our proposed model to define the static and dynamic features of Bitcoin transactions. Nineteen features have been identified to define Bitcoin transaction patterns for analyzing and finding suspected addresses. Bitcoin gene has been embedded into the Petri net transitions to trace and analyze Bitcoin flow accurately. Finally, marginal distribution analysis of Bitcoin transaction features and data visualization techniques are used to eliminate some false positive samples further and to improve the accuracy of identifying suspected addresses. The proposed Bitcoin transaction network analytic method provides a reliable forensic investigation model along with a prototype platform which is beneficial for financial security. The efficiency of our proposed method is empirically verified based on a real-life case study analysis.
Blockchain technology gains more and more attention in the past decades and has been applied in many areas. The main bottleneck for the development and application of blockchain is its limited scalability. Blockchain with directed acyclic graph structure (BlockDAG) is proposed in order to alleviate the scalability problem. One of the key technical problems in BlockDAG is the identification of honest blocks which are very important for establishing a stable and invulnerable total order of all the blocks. The stability and security of BlockDAG largely depends on the precision of honest block identification. This paper presents a novel universal framework based on graph theory, called MaxCord, for identifying the honest blocks in BlockDAG. By introducing the concept of discord, the honest block identification is modelled as a generalized maximum independent set problem. Several algorithms are developed, including exact, greedy and iterative filtering algorithms. The extensive comparisons between proposed algorithms and the existing method were conducted on the simulated BlockDAG data to show that the proposed iterative filtering algorithm identifies the honest blocks both efficiently and effectively. The proposed MaxCord framework and algorithms can set the solid foundation for the BlockDAG technology.
In this competitive world, it is hard to get a job. It requires some specific qualifications and experience according to the post. If a person is not fulfilling these required entities, then not able to apply for that post. Therefore, some people, who are not eligible may use different forgery approaches like fake mark sheets, fake experience certificates, fake medical certificates, etc. However, despite being these fake certificates, some people may have a criminal background also. Therefore, large numbers of resources are required to verify the educational records, criminal background, and experience of a person. Therefore, the proposed system provides an efficient solution to these problems using blockchain technology. In the proposed work, we used three different modules like college, organisation, and police. The college is responsible for providing academic qualifications and the organisation is responsible for providing experience while police are responsible for proving and verification of the criminal record. The proposed system is implemented on the Ethereum blockchain platform and effectively can be used by the organisations for verifying the record of their employees.
Mahendra Kumar Shrivas, Thomas Yeboah, S. Selva Brunda
Computer and network security in the most interesting and challenging field in Computer Science. In Cyberspace, no one can guarantee the complete security of any computer system as technology is evolving day by day. Blockchain is an emerging technology and it is still evolving. The probability of a higher security threat rate has been seen in the case of immature technology. However, mature technologies are also not completely secure. One successful attack could cost millions of dollars to the victim organization and damage their public and financial reputation badly. A transaction can be performed anonymously in Blockchain. In many past reported security breaches, attackers are still unknown and untraceable. In this research article, researchers are proposing a more secure and reliable hybrid security framework for Blockchain platforms that can be used as a generalized reference model to counter various security threats in Blockchain platforms.The proposed hybrid security framework can be applied to secure any kind of Blockchain platform. This research could influence future research in the direction of security of Blockchain 1.0, Blockchain 2.0 and beyond.
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.