The field of blockchain and cryptocurrencies can be both difficult to grasp and improve upon, which makes aids that can assist in these tasks very useful. SpartanGold is a simplified blockchain-based cryptocurrency created at San Jose State University as a learning aid for blockchain and cryptocurrencies. In its current state, it closely resembles Bitcoin, and it is also easily expandable to implement other features. This project extends SpartanGold with a virtual machine resembling the Ethereum Virtual Machine. Implementing this feature results in SpartanGold having Ethereum- related features, which would allow the cryptocurrency to both be a helpful learning aid for Ethereum and be able to solve interesting blockchain problems associated with virtual machines and smart contracts. Using my virtual machine implementation, I was able to produce a simplified token that resembles Ethereum tokens and works with SpartanGold. This token demonstrates the SpartanGold Virtual Machine’s usefulness in simulating smart contracts of real world interest. Going forward, developers can experiment with the SpartanGold Virtual Machine to test out new ideas without dealing with the full complexity of the Ethereum Virtual Machine.
David Richter, David Kretzler, Pascal Weisenburger, Guido Salvaneschi · 6 authors
Decentralized applications (dApps) consist of smart contracts that run on blockchains and clients that model collaborating parties. dApps are used to model financial and legal business functionality. Today, contracts and clients are written as separate programs - in different programming languages - communicating via send and receive operations. This makes distributed program flow awkward to express and reason about, increasing the potential for mismatches in the client-contract interface, which can be exploited by malicious clients, potentially leading to huge financial losses. In this paper, we present Prisma, a language for tierless decentralized applications, where the contract and its clients are defined in one unit. Pairs of send and receive actions that "belong together" are encapsulated into a single direct-style operation, which is executed differently by sending and receiving parties. This enables expressing distributed program flow via standard control flow and renders mismatching communication impossible. We prove formally that our compiler preserves program behavior in presence of an attacker controlling the client code. We systematically compare Prisma with mainstream and advanced programming models for dApps and provide empirical evidence for its expressiveness and performance. The design space of dApp programming and other multi-party languages depends on one major choice: a local model versus a global model. In a local model, parties are defined in separate programs and their interactions are encoded via send and receive effects. In a global language, parties are defined within one shared program and interactions are encoded via combined send-and-receive operations with no effects visible to the outside world. The global model is followed by tierless [Christian Queinnec, 2000; Cooper et al., 2007; Choi and Chang, 2019; Fowler et al., 2019; Serrano et al., 2006; Serrano and Prunet, 2016; Radanne et al., 2016; Weisenburger et al., 2018] and choreographic [Kohei Honda et al., 2011; Fabrizio Montesi et al., 2014; Saverio Giallorenzo et al., 2020] languages. However, known approaches to dApp programming follow the local model, thus rely on explicitly specifying the client-contract interaction protocol. Moreover, the contract and clients are implemented in different languages, hence, developers have to master two technology stacks. The dominating approach in industry is Solidity [Mix, 2019] for the contract and JavaScript for clients. Solidity relies on expressing the protocol using assertions in the contract code, which are checked at run time [Solidity documentation - common patterns, 2020]. Failing to insert the correct assertions may give parties illegal access to monetary values to the detriment of others [Nikolić et al., 2018; Luu et al., 2016]. In research, contract languages [Ankush Das et al., 2019; Michael J. Coblenz, 2017; Franklin Schrans et al., 2018; Franklin Schrans et al., 2019; Michael J. Coblenz et al., 2019; Michael J. Coblenz et al., 2019; Reed Oei et al., 2020; Sam Blackshear et al., 2019] have been proposed that rely on advanced type systems such as session types, type states, and linear types. The global model has not been explored for dApp programming. This is unfortunate given the potential to get by with a standard typing discipline and to avoid intricacies and potential mismatches of a two-language stack. Our work fills this gap by proposing Prisma - the first language that features a global programming model for Ethereum dApps. While we focus on the Ethereum blockchain, we believe our techniques to be applicable to other smart contract platforms. Prisma enables interleaving contract and client logic within the same program and adopts a direct style (DS) notation for encoding send-and-receive operations (with our awaitCl language construct) akin to languages with async/await [Gavin M. Bierman et al., 2012; Scala async rfc]. DS addresses shortcomings with the currently dominant encoding of the protocol’s finite state machines (FSM) [Mix, 2019; Michael J. Coblenz, 2017; Franklin Schrans et al., 2018; Franklin Schrans et al., 2019; Michael J. Coblenz et al., 2019; Michael J. Coblenz et al., 2019]. We argue writing FSM style corresponds to a control-flow graph of basic blocks, which is low-level and more suited to be written by a compiler than by a human. With FSM style, the contract is a passive entity whose execution is driven by clients. whereas the DS encoding allows the contract to actively ask clients for input, fitting dApp execution where a dominant contract controls execution and diverts control to other parties when their input is needed. In the following Prisma snippet, the payout function is a function invoked by the contract when it is time to pay money to a client. In Prisma, variables, methods and classes are separated into two namespaces, one for the contract and one for the clients. The payout method is located on the contract via the annotation @co. The body of the method diverts the control to the client using awaitCl(...) { ... }, hence the contained readLine call is executed on the client. Note that no explicit send/receive operations are needed but the communication protocol is expressed through the program control flow. Only after the check client == toBePayed that the correct client replied, the current contact balance balance() is transferred to the client via transfer. @co def payout(toBePayed: Arr[Address]): Unit = { awaitCl(client => client == toBePayed) { readLine("Press enter for payout") } toBePayed.transfer(balance()) } Overall, Prisma relieves the developer from the responsibility of correctly managing distributed, asynchronous program flows and the heterogeneous technology stack. Instead, the burden is put on the compiler, which distributes the program flow by means of selective continuation-passing-style (CPS) translation and defunctionalisation and inserts guards against malicious client interactions. We needed to develop a CPS translation for the code that runs on the Ethereum Virtual Machine (EVM) since the EVM has no built-in support for concurrency primitives which could be used for asynchronous communication. While CPS translations are well-known, we cannot use them out-of-the-box because the control flow is interwoven with distribution in our case. A CPS translation that does not take distribution into account would allow malicious clients to force the contract to deviate from the intended control flow by sending a spoofed continuation. Thus, it was imperative to prove correctness of our distributed CPS translation to ensure control-flow integrity of the contract.
Phuc Nguyen Trong, Hong Khanh Vo, Huong Hoang Luong, Khiem Huynh Gia · 13 authors
YouTube connects people with each other through an online video sharing service platform. With the great devel-opment of the entertainment industry, content on YouTube is accessible to many people of different ages. However, verifying the content posted on YouTube is clean or not is a difficult problem. Dirty content is violent, pornographic and vulgar content that causes serious psychological harm to the segment of users under the age of 18, i.e., especially those of an age who are not yet aware of the harmful effects of content. Toxic will bring to the child’s behavior. Agree that Google (i.e., YouTube) has developed a YouTube Kid application where the videos are only for children under the age of 13. However, cultural and educational differences between regions strongly influence the choice of children. Select content for children. Therefore, the content restrictions on the YouTube Kid application have not yet met all the requirements of parents around the world. There have been many development directions to identify videos containing malicious content based on deep learning. However, there is no method to build a tool to support parents of children to share and identify videos with objectionable content (e.g., violence, pornography, obscene words) on the YouTube platform. In this research paper, we introduce YVC, a YouTube-verified content platform by applying blockchain’s distributed, public validation. This tool helps parents validate YouTube content and issue a report to reduce dirty content on YouTube. To demonstrate the effectiveness of our approach, we implement the proof-of-concept in the three most popular EVM platforms: Ethereum, Fantom, and the Binance smart chain. Compared to the YouTube Kids (i.e., the most common shared video platform for the under 13-year-old kid), our approach is able to capture the video preferences of the parents covering the difference areas/countries.
Using existing resources to create teaching materials can save effort and achieve the desired quality easily. Yet while some resources can be used freely for educational purposes, others such as textbooks or online course materials cannot. This is a particular problem during a pandemic when much teaching has gone online and the risk of teachers violating copyright is even higher. Therefore, a solution that facilitates the usage of copyright-restricted resources for generating teaching materials with royalty sharing is needed. Our work exploits the advantage of blockchain technology and proposes a system to bond participants with a smart contract; it securely registers records of multiple authorships and contribution distribution of a teaching material that reuses in part, existing resources. Such records can be used as authorship evidence to claim economic benefits when a material is used. We implement TMchain on Ethereum-Remix IDE with a core smart contract. To lower the cost of using blockchain, the material files are stored off-chain and tied to the word processing system for the final authorship and contribution share determination when a material is completed. Furthermore, we test TMchain with teaching material creation scenarios to demonstrate its effective and practical potential.
Isfenti Sadalia, Nisrul Irawati, Rico Nur Ilham, Abdul Nasser Hasibuan · 6 authors
This research type is quantitative version with population, particularly 5 cash of cryptocurremcies with the largest market caps in Indonesia, specifically Bitcoin, Ethereum, Ripple, Bitcoin cash, Litecoin in Indonesia. Varians data in this examine is time series facts taken from January 2017 to December 2020 by using conducting a documentation look at carried out at the ebook of monthly digital assets transaction reports, in order that the target population is 240 (four years x 12 months x five cash) monthly report information sampels. The evaluation approach of records on this take a look at makes use of mild Regression analysis (MRA) model regression and information analysis the usage of e-views statistical software. Cryptocurrency is an funding commodity which could generate returns and already has a license to be traded in trade trading through the Indonesian Commodity Futures trading Regulatory organisation. This studies is added a brand new idea of motion crypto asset that we called it pace. on this second we use velocity Token approach that adapted from the monetary Equation of change via economists known as the quantity principle of money, and its model might be large motion with the aid of token costs. in line with this approach , low speed method that crypto assets last longer within the pockets , that means that traders who to begin with attempted to invest on asset purchases speedy are actually turning to holders, or individuals who keep crypto for the long time. Many quite a variety of crypto virtual belongings traded in Indonesia through the trading corporation Indodax. The effects of records analysis within the examine show that coal price efeect has a advantageous however no longer good sized on virtual assets returns in order that it could be justified as a effective hazard evaluation model. pace of cryptocurrency does not moderate the have an impact on of coal rate on digital belongings returns.
Cryptocurrency networks that provide a new way of securing financial transactions have gained a surge of interest in recent years. However, recent studies reveal that blockchain networks are rampant with frauds and are prone to several privacy and security issues. The public availability of cryptocurrency transaction records provides an unprecedented opportunity for researchers to analyze cryptocurrency transactions. In particular, anomaly detection techniques are promising avenues for fighting illicit activities such as money laundering, terrorist financing, drug trafficking, scams, frauds, and many more.In this dissertation, we address the challenges of detecting anomalous entities on cryptocurrency networks. Firstly, we introduce effective techniques for generating features for network entities that are directly devised from raw data and highlight the utility of those features in detecting illicit accounts on the Ethereum network. Next, we enrich the proposed method by expanding the feature set through the incorporation of graph-based features that embed the relational information of networks. This also enables us to generalize our methods to instances of cryptocurrency networks with different architectural models. Based on the success of our method in anomaly detection in cryptocurrency networks, we further generalize our model to encompass a generic temporal weighted multidigraph and show the state-of-the-art results for anomaly detection in other common domains including rating and social networks. In doing so, we also investigate the challenges of employing node classification techniques for anomaly detection, which is a common practice. Here, we discuss the importance of performance metrics and evaluation settings when interpreting the efficiency of different methods and tasks, which is often overlooked by the community. Finally, we shift our focus to examining the inherent challenges of learning on dynamic networks, which is an important emerging research field with applications in drug discovery, computational finance, social networks, etc. Here, we propose solutions for providing a more robust evaluation setup for dynamic graph learning methods. The key contributions of this dissertation are twofold: First, we describe efficient techniques for detecting anomalies on cryptocurrency networks and generalize them to other real-world complex networks. Second, we focus on the temporal aspect of these networks and investigate how the dynamism of networks affects the downstream tasks and evaluation settings
Yangqun Li, Jin Qi, Lijuan Min, Hongzhi Yang · 6 authors
Web of Things (WoT) resources are not only numerous, but also have a wide range of applications and deployments. The centralized WoT resource sharing mechanism lacks flexibility and scalability, and hence cannot satisfy requirement of distributed resource sharing in large-scale environment. In response to this problem, a trusted and secure mechanism for WoT resources sharing based on context and blockchain (CWoT-Share) was proposed. Firstly, the mechanism can respond quickly to the changes of the application environment by dynamically determining resource access control rules according to the context. Then, the flexible resource charging strategies, which reduced the fees paid by the users who shared more resources and increased the fees paid by users who frequently used resources maliciously, were used to fulfill efficient sharing of WoT resources. Meanwhile, the charging strategies also achieve load balancing by dynamic selection of WoT resources. Finally, the open source blockchain platform Ethereum was used for the simulation and the simulation results show that CWoT-Share can flexibly adapt to the application environment and dynamically adjust strategies of resource access control and resource charging.
D. N. Rao, G. Vidhya, M. Rajesh, Vipin Jain · 7 authors
The new IoT apps will not be able to inspire people to utilize them and may ultimately lose all their potential if an interoperable and trustworthy ecosystem is not provided. IoT has its extra security difficulties such as information storage, administration, privacy concerns, and authentication. The presently deployed IoT apps have encountered various security and privacy assaults globally. Due to being less secure and low powered, the IoT devices present a simple entryway to the adversaries to obtain access to the corporate networks, leading to giving easy control over all of the data of the users. The objective of this doctorate proposed work will be to solve the security associated difficulties in multiple IoT domains like the e‐commerce, vehicular ad hoc networks (VANET), mobile ad hoc networks (MANET), and Internet of Drones (IoD). The proposed study focuses on the development of a distributed framework for IoT based on blockchain. The framework includes the usage of Ethereum‐based smart contracts and auction models to increase the income and QoS for both the seller and the buyer and the development of a DAG chain‐based distributed framework for parking lot allocation in a network of automobiles. The suggested model includes the requirement of obtaining agreement among the nodes with probability one in such a circumstance. The suggested model demonstrates to be predictable as typical voting‐based consensus protocols like Practical Byzantine Fault Tolerance (PBFT) and at the same time can accommodate a high number of nodes even in an asynchronous setting. Research on Byzantine fault‐tolerant systems has been ongoing for more than four decades, and although the solutions were shown to be feasible early on, they remained unworkable for a long time. With PBFT, the first feasible solution was provided in 1999, and this sparked fresh research that has resulted in unique applications that are still being developed today employing this technology. Despite the fact that the safety and liveness properties of PBFT‐type protocols have been thoroughly investigated, when it comes to practical performance, only empirical results—often obtained in artificial environments—are known, and imperfections in the communication channels are not explicitly considered. It is our goal in this paper to propose the first performance model for PBFT that takes into account the effect of unreliable channels as well as the usage of alternative transport protocols across those channels. We also performed a large number of simulations to test the model and acquire a better understanding of the influence of different deployment factors on the total transaction timeframe.
A kriptovaluták piacának dinamikus fejlődésével párhuzamosan fontos pénzügyi és közgazdasági kérdések merülnek fel. A jelen kutatás fő fókusza a kriptovaluták árfolyamának alakulására irányul. A szakirodalmi bázis feltárása nyomán kiemelt figyelmet kapott a kriptopiac más eszközosztályok (arany, részvény, deviza) piacával való összehasonlítása, a kapcsolódási pontok azonosítása. Ezt követően a cikk a 2020 utáni időszakra fókuszálva, eseményelemzés (event study) segítségével igyekszik feltárni, hogy a két legnagyobb piaci kapitalizációval rendelkező kriptovaluta (a bitcoin és az ethereum) hogyan reagált néhány választott eseményre. Ez elsősorban a kriptovaluták működésének alapját képező rendszerek elleni hackertámadásokat jelenti, illetve a szabályozásukhoz, az alkalmazásukhoz kapcsolódó egyes lépéseket. Összességében megállapítottuk, hogy a hackertámadások nem hatottak szignifikánsan a két vizsgált kriptovaluta árfolyamára. A szabályozói lépések hatásai az árfolyamokra vegyesek, ám a szignifikáns hatások is rövid lefolyásúnak tekinthetők.
When Bitcoin became one of the world's most popular investment options, the cryptocurrency industry has showed potential development, and it had a similar influence on the Indian financial sector too. Aside from Bitcoin, other altcoins are gaining popularity and dominating the cryptocurrency market. As a result, the goal of this research is to identify at the macroeconomic factors that influence Bitcoin prices, such as the USD/INR exchange rate, gold prices, crude oil prices, the New York Stock Exchange Dow Jones (NYSE) price, NIFTY price, and Sensex price, as well as the prices of nine alternative cryptocurrencies in the cryptocurrency market: Binance coin, Bitcoin Cash, Bitcoin SV, Ether, Ethereum, Litecoin, Monero, Tether, and ripple. Bitcoin volume and market capitalization are additional factors, undertaken in the study, that are potential influencers of cryptocurrency pricing. The time series data, which comprises of bi-weekly data for all variables, will be used from 2015 to 2020. The OLS (ordinary least square) regression model in EVIEWS will be used in this study to conduct an empirical analysis.
Jan 1, 2022·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Hamza Sellak, Mohan Baruwal Chhetri, Zijin Huang, Marthie Grobler
Medical decision-making is moving away from the traditional one-off dyadic encounter between the patient and physician, and transitioning towards a more inclusive, shared decision-making process that also considers the inputs from other stakeholders. This ensures that a patient's decision is not only based on a medical opinion, but also includes other considerations such as impact on family members, legal and financial implications, and experiences of patients in similar situations. However, given the sensitive nature of health data and decisions, there are several challenges associated with safeguarding the privacy, security and consent of all contributors and assuring the integrity of the process. We propose a collaborative medical decision-making platform that uses a consensus building mechanism implemented using Blockchain-based Smart Contracts to address some of the above challenges, thereby giving the participants confidence that both the decision-making process and the outcome(s) can be trusted. We also present a proof-of-concept implementation using the private Ethereum Blockchain to demonstrate practicability.
This study uses the DCC-GARCH model to compare the correlation between two types of cryptocurrencies in two different fields.In the context of the popularity of NFTs and the metaverse, new cryptocurrencies based on the metaverse have been favored by investors.Through empirical analysis of mana cryptocurrencies in the NFT market, we find that the new cryptocurrencies in the NFT market have high volatility to Bitcoin, Ethereum, and traditional cryptocurrencies in the past year.Therefore, we conclude that new cryptocurrencies are more likely to be one of the factors for portfolio diversification.
Cryptocurrencies are deemed to be highly influenced and driven by investors' sentiments flowing across social media platforms. Consequently, researchers are attracted to investigate investors' behavioral biases in investing in cryptocurrencies. The existing related research majorly focuses on the investigation with the implementation of questionnaires and surveys. However, to what extent the feedbacks to these questionnaires or surveys truthfully reflect the investors' actual practices in investing in cryptocurrencies is uncertain and dubious. Therefore, in this study, we inspect and appraise the behavioral biases and portfolio properties of cryptocurrency investors by utilizing the on-blockchain (on-chain) information of wallet records directly from the Ethereum network. By retrieving and analyzing the unique wallet addresses and related transactions, we have obtained three behavioral bias proxies of the investors behind the wallets and five different properties of the wallets. Furthermore, we distinguish and analyze the wallets of human investors and trading bots. The results of statistical tests indicate the significant differences between human investors and trading bots on most behavioral biases and wallet properties.
Md. Tayeen Khan, Md. Nozib Ud Dowla, Fardin Ahmed Niloy
The popularity of renewable energy is increasing due to its cost effectiveness. However, not everyone can generate and fulfill their energy demand, so energy trading is necessary. Current solutions are centralised and charged at a high fee for energy trading as they have a monopoly in the market. Energy trading requires the storage, verification, and sharing of data related to the trade while keeping records tamper-proof. Traditional database solutions are centralised and susceptible to data tempering. In our proposed scheme, we aim to solve those problems with the help of blockchain technology by storing data on blockchain and verifying transactions with the PoA consensus algorithm for faster processing. We tested our scheme against the Ethereum network and found that our scheme has a significant improvement in cost and processing. In the future, with the help of machine learning, pricing for each transaction can be optimised.
Wenjun Fan, Shubham Kumar, Sang‐Yoon Chang, Younghee Park
Abstract Collaborative intrusion detection approach uses the shared detection signature between the collaborative participants to facilitate coordinated defense. In the context of collaborative intrusion detection system (CIDS), however, there is no research focusing on the efficiency of the shared detection signature. The inefficient detection signature costs not only the IDS resource but also the process of the peer-to-peer (P2P) network. In this paper, we therefore propose a blockchain-based retribution mechanism, which aims to incentivize the participants to contribute to verifying the efficiency of the detection signature in terms of certain distributed consensus. We implement a prototype using Ethereum blockchain, which instantiates a token-based retribution mechanism and a smart contract-enabled voting-based distributed consensus. We conduct a number of experiments built on the prototype, and the experimental results demonstrate the effectiveness of the proposed approach.
In the world there no country, market or economy which is separated, and interconnection is becoming a fundamental feature of almost all social and economic systems. In the case of digital assets, such as cryptocurrencies, the impact of the relationship on their performance and price trajectory increases. The investigation of these phenomena is important for understanding the processes that govern cryptocurrencies. The objective of this paper is to assess the tightness of the relationship between the world's leading cryptocurrencies. In order to achieve this goal, the concepts of «cryptocurrency» and «blockchain», their history and features are considered. The principles of the first cryptocurrency – Bitcoin – are studied and the dynamics of changes in its price from 2015 to 2021 are analyzed. The price of Ethereum, XRP and major financial assets is compared. The best 20 cryptocurrencies at a certain time are identified with their price, capitalization and value changes over the last day and week. Based on the data from the Hackernoon website, research by Larry Chermak and the cryptocurrency publication The Block, it is determined that the strongest cryptocurrencies are interdependent or follow the most important cryptocurrency – bitcoin. Pearson's coefficient is considered. On its basis the correlation strength between eleven leading cryptocurrencies is determined, the part of the data are presented as a confidence interval. It is found that Ethereum and Litecoin have the strongest association with Bitcoin. Coin, Tron, Cardano, Bitcoin Cash, however, have low (negative) correlation between Tether or USDC. The main factors influencing the price of cryptocurrency are identified. It is also determined that alternative cryptocurrencies have lower correlation with bitcoin during periods of price growth, although the differences are not large, and during price decline the strength of bitcoin's correlation with other cryptocurrencies increases significantly, in most cases it reaches even very strong connection. The influence of social networks such as Google+ and Twitter on the price of cryptocurrency is determined as well. The proposed analysis makes it possible to understand the dynamics of cryptocurrency markets and the various processes that affect their efficiency.
Adeeba Naaz, T. V. Pavan Kumar B, Maria Francis, Kotaro Kataoka
Authentication while maintaining anonymity when availing a service over the internet is a significant privacy challenge. Anonymous credentials (AC) address this by providing the user with a credential issued by a trusted entity that convinces the service provider (SP) that the user is authenticated but reveals no other information. The existing AC schemes assume a single trusted authority (certifier) that validates all the user attributes. In practice, however, a user may require different attributes to be attested by different certifiers. This means that the user has to get multiple credentials, increasing the burden on theSPwho has to verify each one of them. Moreover, complete anonymity can be misused. We propose adecentralized threshold revocable anonymous credential (DTRAC)scheme over blockchains that supports – a) attestation of attributes by multiple certifiers, and b) anonymity revocation through a set of distributed openers, by integrating threshold opening to the state-of-the-art threshold anonymous credential issuance scheme, Coconut [34]. DTRAC generates a single credential on attributes that are attested by multiple certifiers, freeing the SP from the hassle of verifying multiple credentials. We analyze the security of DTRAC formally in the universal composability (UC) framework. We also implement a prototype on Ethereum using smart contracts and give a detailed analysis of its performance.We compare the verification time for credentials with attributes attested by multiple certifiers in both DTRAC and Coconut and see that in terms of execution time and gas consumption, DTRAC performs significantly better than Coconut. It also scales better, with the performance gain of DTRAC over Coconut increasing linearly with the number of certifiers.
Oliver Stengele, Christina Westermeyer, Hannes Hartenstein
Software can be described, like human users and other objects, through attributes. For this work, we define software attributes as humanly verifiable, falsifiable, or judgeable statements regarding characteristics of said software. Much like attributes in general, software attributes require robust identities for their source but also for their target, meaning a software in general or a binary in particular. As software can be of critical importance, performing an independent review of attribute claims appears beneficial. We posit that decentralized platforms that were developed and refined over the past decade can bridge the gap between existing tools and methods for software review and their open, transparent, and accountable use for the benefit of users. In this work, we explore the feasibility and implications of decentralizing an independent review of software attribute claims. We envision the decentralization of a review process from initialization and execution to the persistent recording of results. We sketch the available design space by decomposing the overall process into a modular design and describe how each component covers overarching objectives. To illustrate practical implications and trade-offs, we present ETHDPR, a proof of concept implementation based on Ethereum and IPFS. Through a quantitative and qualitative evaluation, we show that a decentralized software review is practically feasible. We illustrate the flexibility of the proposed approach using a toy example of a software component in automotive systems. Lastly, we provide a discussion on fundamental limits and open issues of facilitating independent reviews via technological means.
With regards to the COVID-19 pandemic, the fast carry out of an antibody and the execution of an overall vaccination crusade is basic, yet its prosperity will rely upon the accessibility of a functional and straightforward circulation chain that can be evaluated by all applicable partners. In this paper, we examine how blockchain innovation can help in a few parts of COVID-19 inoculation conspire. We present a framework in which blockchain innovation is utilized to surety information honesty and permanence of recipient enlistment for immunization, keeping away from character burglaries and pantomimes. Smart contracts are characterized to screen and track the legitimate antibody dissemination conditions against the protected dealing with rules characterized by antibody makers empowering the familiarity with all organization peers. For immunization organizations, a straightforward and sealed answer for aftereffects self-detailing is given by thinking about the recipient, what's more, administrated antibody affiliation. A model was executed utilizing the Ethereum test organization, Ropsten, considering the COVID-19 immunization dissemination conditions. The outcomes acquired for each on-chain activity can be checked and approved on the Etherscan. Regarding throughput and versatility, the proposed blockchain framework shows promising outcomes while the assessed cost concerning gas for inoculation situation in view of genuine information stays inside sensible cutoff points.
Creating digital content and distributing them has become much easier and convenient nowadays, where the digital content creator can create the content and also distribute their work to others from anywhere with the help of internet. This also has the risk as the content is distributed using internet, the risk being copyright infringement and illegal distribution of the content. To avoid these types of risks the content creators are opting towards the help of digital rights management. The digital rights management team provides help and support to the content creators in cases where their work is illegally copied or distributed. To get the digital content copyrighted is also not an easy task as it consumes time and money. The proposed model overcomes these issues by integrating digital signature, structure similarity index measurement (SSIM) and blockchain technology in the digital rights management life cycle. The digital signature is used to uniquely identify the user and the related information can be traced back to the user using digital signature, and the copyright is provided using the SSIM method. The SSIM value can be in the range of -1 to 1 where 1 denotes that both the media files are identical and the system updates this information so that all the participant can view this information. If the SSIM value after comparing both the media files is -1 then the both images are unique and authentic, then the copyright is provided for the media file and this information is updated in the system as well as Ethereum blockchain. This makes the system more secure, robust and transparent.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Cryptocurrencies show some properties that differ from typical financial instruments. For example, dynamic volatility, larger price jumps, and other market participants and their associated characteristics can be observed (Pardalos, Kotsireas, Guo, & Knottenbelt, 2020). Especially high tail risk (Sun, Dedahanov, Shin, & Li, 2021; Corbet, Meegan, Larkin, Lucey, & Yarovaya, 2018; Borri, 2019) leads to the question of whether the methods and procedures established in risk management are suitable for measuring the resulting market risks of cryptos appropriately. Therefore, we examine the risk measurement of Bitcoin, Ethereum, and Litecoin. In addition to the classic methods of market risk measurement, historical simulation, and the variance-covariance approach, we also use the extreme value theory to measure risk. Only the extreme value theory with the peaks-over-threshold method delivers satisfactory backtesting results at a confidence level of 99.9%. In the context of our analysis, the highly volatile market phase from January 2021 was crucial. In this, extreme deflections that have never been observed before in the time series have significantly influenced backtesting. Our paper underlines that critical market phases could not be sufficiently observed from the short time series, leading to adequate backtesting results under the standard market risk measurement. At the same time, the strength of the extreme value theory comes into play here and generates a preferable risk measurement.