Aiming at the poor encryption effect existing in the data encryption algorithm of e-commerce platform, and the data lost and distorted easily after encrypting, a data encryption algorithm based on blockchain technology is proposed in this paper. By analyzing the symmetric key algorithm and the public key algorithm, the DES encryption algorithm is described in detail. The two related technologies of digital envelopes and message authentication are analyzed to ensure the accuracy of the data and the one time encryption of the data. Based on this, in order to ensure the effectiveness of encryption, the process of asymmetric encryption algorithm based on chaotic sequence of neural network and asymmetric encryption algorithm based on neural network chaotic attractor are analyzed, and the security is tested. While ensuring the accuracy of data, it improves the effect of data encryption and realizes the encryption of e-commerce platform data, which is to realize data encryption algorithm based on blockchain technology. Experimental results show that the~proposed algorithm can encrypt the data of e-commerce platform, and the encryption process is relatively simple, the encryption effect is better, and the accuracy of the encrypted data is relatively high, which provides a theoretical basis for further research of the subject.
Open access
Chaos-based Image/Signal Encryption
Advanced Steganography and Watermarking Techniques
Since the considerable ascent in the estimation of the digital money Bitcoin, which utilizes a blockchain for bookkeeping, there has been a huge enthusiasm for blockchain innovation. A blockchain is a transparent distributed ledger which is revolutionising the financial services industry by legimatizing millions across the globe to authenticate and transact immediately, without the involvement of expensive third-parties.Blockchain innovation is named as the 'Fifth Evolution' of processing. Till date, Bitcoin is the most generally utilized application utilizing blockchain innovation. But now days it is applied in almost every field, like finance, agriculture geospatial areas, gaming etc. The paper is emphasizing on different kinds of blockchains and the applications.
Hans‐Arno Jacobsen, Mohammad Sadoghi, Mohammad Hossein Tabatabaei, Roman Vitenberg · 5 authors
Known for powering cryptocurrencies such as Bitcoin and Ethereum, blockchain is seen as a disruptive technology capable of revolutionizing a wide variety of domains, ranging from finance to governance, by offering superior security, reliability, and transparency founded upon a decentralized and democratic computational model. In this tutorial, we first present the original Bitcoin design, along with Ethereum and Hyperledger, and reflect on their design choices through the academic lens. We further provide an overview of potential applications and associated research challenges, as well as a survey of ongoing research directions related to byzantine fault-tolerance consensus protocols. We highlight the new opportunities blockchain creates for building the next generation of secure middleware platforms and explore the possible interplay between AI and blockchains, or more specifically, how blockchain technology can enable the notion of "decentralized intelligence." We conclude with a walkthrough demonstrating the process of developing a decentralized application using a popular Smart Contract language (Solidity) over the Ethereum platform
The gaming industry has evolved into a multi-functional smart city that combines integrated casinos and entertainment (ICE). ICE logistics involve supply chains with various stages in geographically-distributed locations and with limited and complex storage and warehouses. Challenges are to leverage demands, traffic, and storage allocation in ICE logistics. The decentralized structure of blockchain technology allows all parties to participate in ICE logistics. Its cryptography-based, immutable nature gives the assurance of security. This research deals with the design and application of blockchains in ICE logistics. We first adopt a Concentric Value Circles (CVC) model to identify the requirements and business opportunities that use blockchain technology in ICE logistics. We develop an open, automated, and transparent platform, TransICE, which utilizes the feature of smart contracts in blockchain technology and adopts a decentralized model, Hawk, where no financial transactions are stored on the blockchain to hold privacy of transactions publicly. Two cases, (1) the Shipment Pricing and Scheduling process and (2) the Pickup, Shipping and Delivery process in TransICE, are studied to illustrate the applications and feasibility of the proposed TransICE platform and the developed smart contracts of the Hawk model.
The cryptocurrency is attracting more and more attention because of the blockchain technology. Ethereum is gaining a significant popularity in blockchain community, mainly due to the fact that it is designed in a way that enables developers to write smart contracts and decentralized applications (Dapps). There are many kinds of cryptocurrency information on the social network. The risks and fraud problems behind it have pushed many countries including the United States, South Korea, and China to make warnings and set up corresponding regulations. However, the security of Ethereum smart contracts has not gained much attention. Through the Deep Learning approach, we propose a method of sentiment analysis for Ethereum's community comments. In this research, we first collected the users' cryptocurrency comments from the social network and then fed to our LSTM + CNN model for training. Then we made prediction through sentiment analysis. With our research result, we have demonstrated that both the precision and the recall of sentiment analysis can achieve 0.80+. More importantly, we deploy our sentiment analysis1 on RatingToken and Coin Master (mobile application of Cheetah Mobile Blockchain Security Center23). We can effectively provide detail information to resolve the risks of being fake and fraud problems.
The blockchain is a safe, reliable and innovative mechanism for managing numerous vehicles seeking connectivity. However, following the principles of the blockchain, the number of transactions required to update ledgers pose serious issues for vehicles as these may consume the maximum available energy. To resolve this, an efficient model is presented in this letter which is capable of handling the energy demands of the blockchain-enabled Internet of Vehicles (IoV) by optimally controlling the number of transactions through distributed clustering. Numerical results suggest that the proposed approach is 40.16% better in terms of energy conservation and 82.06% better in terms of the number of transactions required to share the entire blockchain-data compared with the traditional blockchain.
Luca Becchetti, Andrea Clementi, Emanuele Natale, Francesco Pasquale · 5 authors
It follows from the Marcus-Spielman-Srivastava proof of the Kadison-Singer conjecture that if $G=(V,E)$ is a $Δ$-regular dense expander then there is an edge-induced subgraph $H=(V,E_H)$ of $G$ of constant maximum degree which is also an expander. As with other consequences of the MSS theorem, it is not clear how one would explicitly construct such a subgraph. We show that such a subgraph (although with quantitatively weaker expansion and near-regularity properties than those predicted by MSS) can be constructed with high probability in linear time, via a simple algorithm. Our algorithm allows a distributed implementation that runs in $\mathcal O(\log n)$ rounds and does $\mathcal O(n)$ total work with high probability. The analysis of the algorithm is complicated by the complex dependencies that arise between edges and between choices made in different rounds. We sidestep these difficulties by following the combinatorial approach of counting the number of possible random choices of the algorithm which lead to failure. We do so by a compression argument showing that such random choices can be encoded with a non-trivial compression. Our algorithm bears some similarity to the way agents construct a communication graph in a peer-to-peer network, and, in the bipartite case, to the way agents select servers in blockchain protocols.
The problem of transparency in donation systems has long been a topic for discussion. However, the emphasis on transparency raises privacy concerns for donors and recipients, with some people attempting to hide donations or the receipt of money. Therefore, a donation system that guarantees transparency and privacy is required to avoid negative side effects. In this study, we developed a system that protects personal information by using a one-time account address system based on a blockchain while emphasizing transparency. The developed system could contribute to the creation of a sustainable and safe donation environment and culture.
Blockchain technology has seen significant growth, hype, and potential new developments over the past few years. In this article additional insights into how blockchain can add value to a business process relationship is detailed. Specifically an engineering contract workflow use application pilot including various high level system architectural aspects are presented. This application shows the integration of blockchain technology with existing legacy systems. Some management and technology issues are also overviewed for the reader.
La revolucion digital ha traido cambios en todas las dimensiones sociales. Desde el surgimiento del internet y su adopcion global como herramienta de informacion ha cambiado el viejo orden mundial. Bitcoin trae consigo el internet de valor, en donde la criptografia brinda soporte y garantia. El paso a una economia global cada vez mas dinamica y competitiva, es el escenario ideal para modelos de negocios distribuidos, seguros y sostenibles. De esta manera, el Blockchain se convierte en el metodo de distribucion de valor en internet. En Colombia existe un sector tecnologico rezagado, pero con un potencial de adaptacion interesante gracias al tamano de su mercado; no obstante, el analisis de algunos aspectos culturales da muestra de los retos y sesgos presentes en la percepcion de los habitantes. El esfuerzo formativo de frente al cambio generacional que se vive globalmente es una tarea que implica la cohesion de varios agentes: Las instituciones de gobierno, los centros educativos y el sector privado.
Session Description: Over the past years many companies and pundits have discussed the adoption of distributed ledger technologies, aka blockchain for healthcare applications. This panel will discuss the juxtaposition of the so-called Health IT industry and the myriad of applications that would positively reduce friction between the provider and consumer. This improved interaction will also reduce costs and bring true transparency to all transactions in healthcare. Many believe that the Health IT industry is completely homeostatic for any type of true disruption. Why does the industry trumpet disruption when their actions speak louder than words? We address these concerns with leaders on the cutting edge of technology.
Suppose that a supplier of goods or services and a consumer enter into a contract for goods or services. If the terms and conditions of the contract are prefixed by the supplier unilaterally and the choice of the consumer is just to accept or decline, it is very easy to implement an automatic contracting process for them. Everyday, we experience such simple and automated contracting processes when we ride on the subway and buses using IC cards. / However, in many cases, the terms that each of the parties to a contract deems acceptable in advance are very abstract and have some flexibility. Such anticipated terms may include the conditions most preferred by a party to those least preferred. There is no guarantee that the resulting contract will satisfy both parties. The terms and conditions of the contract to be executed are likely to have multiple alternatives. The finally decided terms just represent one of many possible alternatives. It would be difficult for such terms to completely satisfy both parties. In order to make smart contracts widely implemented in our society, a system that automatically matches the terms and conditions of both parties to a contract (hereinafter, referred to as a smart contract platform) must be able to establish a contract with fair and reasonable terms and conditions that can satisfy both parties in such complex situation. The currently spreading use of Artificial Intelligence (A.I.) using deep learning is likely to make such a smart contract platform realistic. / However, suppose that both parties to a contract could have gone through a human to human negotiation, and that the final terms are not preferable or disadvantageous to one of the parties. Possibly, such disadvantaged parties would try to persuade themselves that such undesirable or disadvantageous results were caused by their or their agent’s incompetence. However, if such undesirable or disadvantageous terms are caused automatically by a smart contract platform, the disadvantaged party may feel great frustration because they can hardly find a reason to blame themselves. Also, it is possible for a smart contract platform to manipulate the terms of a contract by utilizing the very wide scope of acceptable terms prefixed by the consumer, thereby, giving an advantage to the supplier. Such manipulation will be deemed unfair, even though it does not necessarily constitute fraud. Moreover, if a smart contract platform is provided exclusively by one or a very limited number of companies, the platform may be programmed to be advantageous or disadvantageous to specific or specific categories of suppliers. For example, a smart contract platform used to enable electricity supply companies and consumers who want to quickly charge their electric vehicles (EVs) to contract automatically may be programmed to increase the probability that established and conventional electricity supply companies can contract with consumers within the scope of the terms prefixed by the consumers. It is also probable that a smart contract platform will apply different terms and conditions, such as by giving priority to contracts with consumers of certain electricity supply companies, and give advantages to some of them, and cause disadvantages to others. The implementation of smart legal tools in the society is likely to require us to design legal tools such as the obligatory disclosure of an automatic contracting process, auditing or monitoring by a third party, and competition among multiple smart contract platform providers, to ensure a fair smart contracting process, and also to prevent misappropriation of smart contract platforms for unfair purposes. However, designing such legal tools is likely to cause another problem. A law must be enforced based on the evidence required by the law itself. If a smart contract platform is organized and operated by a fixed algorithm that does not change and update itself automatically, it would be plausible to prove that the platform was programmed by ab human to cause unfair results. However, suppose that an A.I. implemented in a smart contract platform keeps learning and constantly and incrementally updates itself. It is improbable that lawyers could prove that a smart contract platform producing unfair results was really programmed by a human to cause such results. To tackle such problems would also be the duty of lawyers.
Yunhui Long, Tanmay Gangwani, Haris Mughees, Carl A. Gunter
Privacy preserving multi-party computation has many applications in areas such as medicine and online advertisements. In this work, we propose a framework for distributed, secure machine learning among untrusted individuals. The framework consists of two parts: a two-step training protocol based on homomorphic addition and a zero knowledge proof for data validity. By combining these two techniques, our framework provides privacy of per-user data, prevents against a malicious user contributing corrupted data to the shared pool, enables each user to self-compute the results of the algorithm without relying on external trusted third parties, and requires no private channels between groups of users. We show how different ML algorithms such as Latent Dirichlet Allocation, Naive Bayes, Decision Trees etc. fit our framework for distributed, secure computing.
Tom Savel, Katherine Kuzmeskas, Chrissa McFarlane, Mihaela Ulieru
Session Description: Tokenization is a fundamental and transformation feature enabled via a blockchain. Tokenization is the digital representation of a real-world or digital asset of value (e.g., health data, real estate, music, insurance, advertising, art). Once tokenized, assets can be easily and securely exchanged. Within the healthcare ecosystem, these digital assets can be used for many different purposes (incentivizing positive health behaviors, reward data sharing, facilitate communication, assuring data quality, etc.). This session will discuss the transformational impact tokenization can have within the healthcare ecosystem. Topics will also include the use of next generation, non-fungible tokens (e.g., ERC-721, “CryptoKitties”). As every technology has its challenges, concerns and pitfalls around tokenization and the internet of value will be discussed.
Abstract Blockchain technology has been considered a vehicle to foster development in poor countries by promoting applications such as secure delivery of humanitarian aid, digital identity services, and proof of provenance. This article examines whether (and if so, how) blockchain technology can enhance the effectiveness and efficiency of foreign aid governance, thereby moving beyond completely anonymous contexts. Foreign aid governance is plagued by lack of credible commitments among states, which are further exacerbated by information asymmetries and which often undermine aid effectiveness. In this context, blockchain technology holds two promises. First, through the guaranteed execution of smart contracts, it can strengthen the credibility of state commitments, for example collective burden-sharing rules among a group of donors or recipient country compliance with policy conditionality in return for aid. Second, through leveraging prediction markets, blockchain technology can allay information problems related to the verification of real-world events along the entire aid delivery chain.
Auction is an effective way to allocate goods or services to bidders who value them the most. The rapid growth of e-auctions facilitates online transactions but poses new and distinctive challenges. It is difficult to establish trust among sellers, buyers, and auctioneers without centralized auction websites or platforms (the auctioneer) which collect bids and derive the auction results. However, these third parties may be untrustworthy, and malicious sellers or buyers may refuse to deliver the goods or payment according to the protocol. Moreover, the open and anonymous online environment may stimulate auction participants to form collusion coalitions to rig the auction and reap unfair profit. Many auction designs have been proposed to address these concerns, but they fall short of simultaneously achieving decentralization (i.e., held without a trusted third utility), strong consensus (i.e., the establishment of trust), collusion resistance, and practical implementation. We present CReam, the first decentralized collusion-resistant e-auction system that is implemented with smart contract on the blockchain. With the carefully designed smart auction contract, mutually distrustful and rational sellers and buyers are stimulated to operate properly, hence transact safely without trusted third parties. The auction mechanism in the smart contract can effectively prevent bidder collusion and realize economic robustness, i.e., truthfulness. We implement a fully functional CReam on the Ethereum network. Extensive experimental results confirm that CReam can greatly reduce the probability of collusion and achieve an approximate optimal revenue at a low cost of contract execution.
Pump-and-dump schemes are fraudulent price manipulations through the spread of misinformation and have been around in economic settings since at least the 1700s. With new technologies around cryptocurrency trading, the problem has intensified to a shorter time scale and broader scope. The scientific literature on cryptocurrency pump-and-dump schemes is scarce, and government regulation has not yet caught up, leaving cryptocurrencies particularly vulnerable to this type of market manipulation. This paper examines existing information on pump-and-dump schemes from classical economic literature, synthesises this with cryptocurrencies, and proposes criteria that can be used to define a cryptocurrency pump-and-dump. These pump-and-dump patterns exhibit anomalous behaviour; thus, techniques from anomaly detection research are utilised to locate points of anomalous trading activity in order to flag potential pump-and-dump activity. The findings suggest that there are some signals in the trading data that might help detect pump-and-dump schemes, and we demonstrate these in our detection system by examining several real-world cases. Moreover, we found that fraudulent activity clusters on specific cryptocurrency exchanges and coins. The approach, data, and findings of this paper might form a basis for further research into this emerging fraud problem and could ultimately inform crime prevention.
Muhammad Saad, Laurent Njilla, Charles Kamhoua, Aziz Mohaisen
Selfish mining is a well known vulnerability in blockchains exploited by miners to steal block rewards. In this paper, we explore a new form of selfish mining attack that guarantees high rewards with low cost. We show the feasibility of this attack facilitated by recent developments in blockchain technology opening new attack avenues. By outlining the limitations of existing countermeasures, we highlight a need for new defense strategies to counter this attack, and leverage key system parameters in blockchain applications to propose an algorithm that enforces fair mining. We use the expected transaction confirmation height and block publishing height to detect selfish mining behavior and develop a network-wide defense mechanism to disincentivize selfish miners. Our design involves a simple modifications to transactions' data structure in order to obtain a “truth state” used to catch the selfish miners and prevent honest miners from losing block rewards.
While pump-and-dump schemes have attracted the attention of cryptocurrency observers and regulators alike, this paper represents the first detailed empirical query of pump-and-dump activities in cryptocurrency markets. We present a case study of a recent pump-and-dump event, investigate 412 pump-and-dump activities organized in Telegram channels from June 17, 2018 to February 26, 2019, and discover patterns in crypto-markets associated with pump-and-dump schemes. We then build a model that predicts the pump likelihood of all coins listed in a crypto-exchange prior to a pump. The model exhibits high precision as well as robustness, and can be used to create a simple, yet very effective trading strategy, which we empirically demonstrate can generate a return as high as 60% on small retail investments within a span of two and half months. The study provides a proof of concept for strategic crypto-trading and sheds light on the application of machine learning for crime detection.
Muhammad Shayan, Clement Fung, Chris J. M. Yoon, Ivan Beschastnikh
Federated Learning is the current state of the art in supporting secure multi-party machine learning (ML): data is maintained on the owner's device and the updates to the model are aggregated through a secure protocol. However, this process assumes a trusted centralized infrastructure for coordination, and clients must trust that the central service does not use the byproducts of client data. In addition to this, a group of malicious clients could also harm the performance of the model by carrying out a poisoning attack. As a response, we propose Biscotti: a fully decentralized peer to peer (P2P) approach to multi-party ML, which uses blockchain and cryptographic primitives to coordinate a privacy-preserving ML process between peering clients. Our evaluation demonstrates that Biscotti is scalable, fault tolerant, and defends against known attacks. For example, Biscotti is able to protect the privacy of an individual client's update and the performance of the global model at scale when 30% of adversaries are trying to poison the model. The implementation can be found at: https://github.com/DistributedML/Biscotti