The Internet of Things (IoT) is gradually becoming mature and has already entered our daily life, which interconnects more machines and makes communication more convenient and more intelligent. Massive IoT devices produce innumerable data which need to be analyzed in joint cloud computation (JointCloud) with diversified services. However, due to the weak security of IoT devices, the existing JointCloud architecture hardly provides a secure trusted trade environment for users, which affects severely the application in the IoT network. In this article, we propose a hierarchical trust networking architecture based on permissioned blockchain to implement JointCloud (HTJC). The proposed Hyperledger fabric-based architecture has a better performance than those based on Ethereum in latency. By introducing the credit bonus-penalty strategy (CBPS), HTJC can solve the trust problem and provide users with a secure trusted trade environment. The availability of the proposed architecture is evaluated and compared to the existing models. The numerical results show that the HTJC can defend distributed denial-of-service (DDoS) attacks and provide users with a trusted and effective trade platform.
Guntur Dharma Putra, Volkan Dedeoglu, Salil S. Kanhere, Raja Jurdak
Heterogeneous and dynamic IoT environments require a lightweight, scalable, and trustworthy access control system for protection from unauthorized access and for automated detection of compromised nodes. Recent proposals in IoT access control systems have incorporated blockchain to overcome inherent issues in conventional access control schemes. However, the dynamic interaction of IoT networks remains uncaptured. Here, we develop a blockchain based Trust and Reputation System (TRS) for IoT access control, which progressively evaluates and calculates the trust and reputation score of each participating node to achieve a self-adaptive and trustworthy access control system. Trust and reputation are explicitly incorporated in the attribute-based access control policy, so that different nodes can be assigned to different access right levels, resulting in dynamic access control policies. We implement our proposed architecture in a private Ethereum blockchain comprised of a Docker container network. We benchmark our solution using various performance metrics to highlight its applicability for IoT contexts.
Data analytics has captured attention of both researchers as well as business organizations, since a long time now, as the knowledge or information getting analyzed and evolved is priceless in upbringing the business. Blockchain is the latest technology which is getting adopted at a faster rate due to its unique properties. This paper focuses mainly on data models, and some tools used for data analytics being used in blockchain environment. Public blockchain is an open ledger platform which allows to perform data analytics.
This paper presents the design and implementation of a smart home system in the context of Internet of Things (IoT) with Ethereum private Blockchain, Raspberry Pi, Blynk platform, DHT11 temperature and humidity sensors. By Raspberry Pi, it collects real-time room humidity and temperature information by DHT11. The data is then uploaded to the Blynk App, which is stored on the smart contract deployed with the Ethereum private Blockchain. When the real-time humidity or temperature value exceeds a predefined threshold value, warnings are given by turning on LEDs. The system functions as a proof-of-concept prototype, showing the feasibility of applying blockchain in smart homes with IoT functionalities.
Nowadays smart contracts apply in management, bank system, insurance, estate, IoT, and others, because they perform credible and trackable irreversible transactions without third parties. The proposed paper presents a solution for the creation of a decentralized token for the implementation of a smart contract based on Ethereum block-chain. A web based interface has been created for Initial Coin Offering (ICO). In the experimental environment the research was carried out for various scenarios. The results are presented.
Roben Castagna Lunardi, Henry Cabral Nunes, Vinicius da Silva Branco, Bruno Hugentobler Lipper · 6 authors
Blockchain emerged as a solution for data integrity, non-repudiation, and availability in different applications. Data sensitive scenarios, such as Health Care, can also benefit from these blockchain properties. Consequently, different research proposed the adoption of blockchain in Health Care applications. However, few are discussed about incentive methods to attract new users, as well as to motivate the system or application usage by existing end-users. Also, little is discussed about performance during code execution in blockchains. In order to tackle these issues, this work presents the preliminary evaluation of TokenHealth, an application for collaborative health practice monitoring with gamification and token-based incentives. The proposed solution is implemented through smart contracts using Solidity in the Ethereum blockchain. We evaluated the performance of both in Ropsten test network and in a Private instance. The preliminary results show that the execution of smart contracts takes less than a minute for a full cycle of different smart contracts. Also, we present a discussion about costs for using a Private instance and the public Ethereum main network.
Yi Zhong, Anmin Zhou, Lei Zhang, Jing Fan · 5 authors
As the root cause of illegal cyber activities, botnets are evolving continuously over the last two decades. Current researches on botnet command and control mechanism based on blockchain network suffer from high economic cost, single point of failure, and limited scalability. In this paper, we present DUSTBot, a novel P2P botnet model based on Bitcoin transactions to prepare for new cyber threats. Specifically, a covert, duplex, and low-cost command and control (C&C) channel in the Bitcoin network is presented in our work. DUSTBot uses the Bitcoin main network as the downstream channel while using the Bitcoin testnet as the upstream channel. Furthermore, the peer list exchange algorithm based on the Ethereum block hash proposed in this paper is effective against routing table poisoning attack and P2P botnet crawling. The robustness of DUSTBot against node removal is studied through constructing the botnet with a P2P simulator. We deploy the implementation of DUSTBot on cloud platforms to test its feasibility and performance. Moreover, the stealthiness of DUSTBot and the effectiveness of the proposed peer list exchange algorithm are evaluated. The results demonstrate the feasibility, performance, stealthiness, and robustness of DUSTBot. In the end, possible countermeasures are discussed to mitigate similar threats in the future.
Blockchain software development is becoming more and more important for any modern software developer and IT startup. Nonetheless, blockchain software production still lacks a disciplined, organized and mature development process, as demonstrated by the many and (in)famous failures and frauds occurred in recent years. In this paper we present ABCDE, a complete method addressing blockchain software development. The method considers the software integration among the blockchain components—smart contracts, libraries, data structures—and the out-of-chain components, such as web or mobile applications, which all together constitute a complete DApp system. We advocate for ABCDE the use of agile practices, because these are suited to develop systems whose requirements are not completely understood since the beginning, or tend to change, as it is the case of most blockchain-based applications. ABCDE is based on Scrum, and is therefore iterative and incremental. From Scrum, we kept the requirement gathering with user stories, the iterative-incremental approach, the key roles, and the meetings. The main difference with Scrum is the separation of development activities in two flows—one for smart contracts and the other for out-of-chain software interacting with the blockchain—each performed iteratively, with integration activities every 2–3 iterations. ABCDE makes explicit the activities that must be performed to design, develop, test and integrate smart contracts and out-of-chain software, and documents the smart contracts using formal diagrams to help development, security assessment, and maintenance. A diagram derived from UML class diagram helps to effectively model the data structure of smart contracts, whereas the exchange of messages between the entities of the system is modeled using a modified UML sequence diagram. The proposed method has also specific activities for security assessment and gas optimization, through systematic use of patterns and checklists. ABCDE focuses on Ethereum blockchain and its Solidity language, but preserves generality and with proper modifications might be applied to any blockchain software project. ABCDE method is described in detail, and an example is given to show how to concretely implement the various development steps.
Abstract When bitcoin was released by the mysterious Satoshi Nakamoto in 2008, few could have predicted that it would attract as much attention as it has today. It has spawned a veritable host of other cryptocurrencies, including ether on the upstart Ethereum network, which boasts smart contract functionality. The underlying blockchain technology has also attracted attention, with some within the blockchain community suggesting that it can solve such diverse problems as secured digital voting to tracking food provenance. In the legal context, blockchains have been envisaged as capable of revolutionising registries for assets ranging from land to intellectual property, modernising clearing and settlement, and even fundamentally transforming the contracting process. This article critically evaluates the popular claims surrounding the potential of blockchain technologies to disrupt the legal system by separating hype from fact.
Since the world’s first virtual currency was issued on the Bitcoin blockchain network in 2009, there has been a proliferation of various other private digital token offerings on blockchain networks—in particular, on the Ethereum blockchain. Milkau and Bott (2018) report that several governments are considering implementing digital currencies as a “complement to cash.” Blockchain technology holds great promise for innovative applications capable of facilitating any number of business operations, and several large companies including IBM, American Express, Toyota, JP Morgan Chase, Goldman Sachs, Walt Disney, Oracle, and Facebook have already invested heavily in the emerging technology. Crowdfunding is also a popular application of blockchain technology. Tech entrepreneurs have issued digital tokens for virtual currency as a means of circumventing the tedious regulations of the SEC governing the raising of capital. The regulatory status of these digital tokens and their associated trading platforms has been approached with a certain degree of ambiguity and controversy. This paper explores and explains the regulatory issues of fintech regarding digital tokens, making a valuable addition to the scarce literature on this topic.
This paper proposes SilentDelivery, a secure, scalable and cost-efficient protocol for implementing timed information delivery service in a decentralized blockchain network. SilentDelivery employs a novel combination of threshold secret sharing and decentralized smart contracts. The protocol maintains shares of the decryption key of the private information of an information sender using a group of mailmen recruited in a blockchain network before the specified future time-frame and restores the information to the information recipient at the required time-frame. To tackle the key challenges that limit the security and scalability of the protocol, SilentDelivery incorporates two novel countermeasure strategies. The first strategy, namely silent recruitment, enables a mailman to get recruited by a sender silently without the knowledge of any third party. The second strategy, namely dual-mode execution, makes the protocol run in a lightweight mode by default, where the cost of running smart contracts is significantly reduced. We rigorously analyze the security of SilentDelivery and implement the protocol over the Ethereum official test network. The results demonstrate that SilentDelivery is more secure and scalable compared to the state of the art and reduces the cost of running smart contracts by 85%.
Abstract Background With the advent of precision medicine, pharmacogenomics data is becoming increasingly critical to patient care. These data describe the relationship between a particular variant in the genome and the response to a drug by the patient. As utilizing this kind of data becomes more integral to medical treatment decisions, appropriate storage and sharing of this data will be critical. A potential way of securely storing and sharing pharmacogenomics data is a smart contract with the Ethereum blockchain. This is an open-source blockchain platform for decentralized applications. A transaction-based, state machine, the “world” of Ethereum maintains user accounts and storage in a network state. Immutable pieces of code called “smart contracts” may be deployed to the Ethereum network and run on the Ethereum Virtual Machine when called by a user or other contract. The 2019 iDASH (Integrating Data for Analysis, Anonymization, and Sharing) competition for Secure Genome Analysis challenged participants to develop time- and space-efficient smart contracts to log and query gene-drug relationship data on the Ethereum blockchain. Methods We designed a smart contract to store and query pharmacogenomics data (gene-drug interaction data) in Ethereum using an index-based, multi-mapping approach allowing for time and space efficient storage and query. Our solution to the IDASH competition ranked in the top three at a workshop held in Bloomington, IN in October 2019. Although our solution performed well in the challenge, we wanted to improve its scalability and query efficiency. To that end, we developed an alternate “fastQuery” solution that stores pooled rather than raw data, allowing for significantly improved query time for 0-AND queries, and constant query time for 1- and 2-AND queries. Results We tested the performance of both of our solutions in Truffle (v5.0.31) using datasets ranging from 100 to 1000 entries, and inserting data at 25, 50, 100, and 200 observations at a time. On a private, proof-of-authority test network, our challenge solution requires approximately 70 seconds, 500 MB of memory, and 80 MB of disk space to insert 1000 entries (200 at a time); and 400 ms and 5 MB of memory to query a two-AND query from 1000 entries. This solution exhibits constant memory for insertion and querying, and linear query time. Our alternate fastQuery solution requires approximately 60 seconds, 500 MB of memory, and 80 MB of disk space to insert 1000 entries (200 at a time); and 83 ms and 5 MB of memory to query a two-AND query from 1000 entries. This solution exhibits constant memory for insertion and querying, linear query time for 0-AND queries, and constant query time for 1- and 2-AND queries in a database of up to 1000 entries. Conclusion In this study we showed that pharmacogenomics data can be stored and queried efficiently on the Ethereum blockchain. Our approach has the potential to be useful for a wide range of datasets in biomedical research; while we focused on gene-drug interaction data, our solution designs could be used to store a range of clinical trial data. Moreover, our solutions could be adapted to store and query data in any field where high-integrity data storage and efficient access is required.
Οι τεχνολογικές εξελίξεις μεταμορφώνονται και συνεχώς αναπτύσσονται με τόσο γρήγορο ρυθμό, ώστε όλοι να πρέπει να παραμείνουν σε εγρήγορση για να μπορούν να τις παρακολουθήσουν. Το Blockchain είναι το νέο κύμα καινοτομίας που έχει ήδη αρχίσει να επανασχεδιάζει τον τρόπο εργασίας, τις κοινωνικές και πολιτικές αλληλεπιδράσεις και τους παραδοσιακούς τρόπους ανταλλαγής. Ωστόσο δεν είναι μόνο μια απλή αλλαγή, αλλά ένα ραγδαίως αναπτυσσόμενο φαινόμενο που ήδη βρίσκεται σε εξέλιξη. Κατά τη συγγραφή αυτή, περισσότερα από 40 κορυφαία χρηματοπιστωτικά ιδρύματα και πολλές διαφορετικές επιχειρήσεις σε διάφορες βιομηχανίες, άρχισαν να διερευνούν τις δυνατότητες του blockchain με σκοπό να μειώσουν το κόστος των συναλλαγών, να επιταχύνουν το χρόνο περάτωσής τους, να μειώσουν τον κίνδυνο απάτης και να εξαλείψουν τους μεσάζοντες ή τις υπηρεσίες διαμεσολάβησης. Η τεχνολογική ιδέα πίσω από το Blockchain είναι πολύ πανομοιότυπη με αυτή μιας βάσης δεδομένων και μέσα από αυτήν την προσέγγιση, γίνεται η χρήση του στην ανάπτυξη της voting εφαρμογής, αποδεικνύοντας με ρεαλιστικό τρόπο ότι η αλυσίδα του Ethereum μπορεί να αναλάβει ηγετικό ρόλο στη νέα εποχή, που σκοπό έχει τη δημιουργία αποκεντρωμένων εφαρμογών.
Anton Hasselgren, Katina Kralevska, Danilo Gligoroski, Sindre Andre Pedersen · 5 authors
BACKGROUND: Blockchain can be described as an immutable ledger, logging data entries in a decentralized manner. This new technology has been suggested to disrupt a wide range of data-driven domains, including the health domain. OBJECTIVE: The purpose of this study was to systematically review, assess and synthesize peer-reviewed publications utilizing/proposing to utilize blockchain to improve processes and services in healthcare, health sciences and health education. METHOD: A structured literature search on the topic was conducted in October 2018 relevant bibliographic databases. RESULT: 39 publications fulfilled the inclusion criteria. The result indicates that Electronic Health Records and Personal Health Records are the most targeted areas using blockchain technology. Access control, interoperability, provenance and data integrity are all issues that are meant to be improved by blockchain technology in this field. Ethereum and Hyperledger fabric seem to be the most used platforms/frameworks in this domain. CONCLUSION: This study shows that the endeavors of using blockchain technology in the health domain are increasing exponentially. There are areas within the health domain that potentially could be highly impacted by blockchain technology.
Smart contracts are immutable, verifiable, and autonomous pieces of code that can be deployed and ran on blockchain networks like Ethereum. Due to the immutability nature of blockchain, no change is possible on a deployed smart contract or a verified transaction. On the other hand, there are millions of dollars carried by smart contracts in Ethereum blockchain, and hence, a faulty smart contract can lead to a huge monetary loss. Therefore, it is important for smart contract developers to fully test and check the correctness of their code before deploying it on the blockchain. In this paper, we propose a testing mechanism for smart contracts in Solidity language, based on mutation testing. We analyzed a comprehensive list of known bugs in Solidity smart contracts, and designed 10 classes of mutation operators inspired by the real faults. Our experimental results show that our proposed mutation operators can regenerate 10 of 15 famous faulty smart contracts, which have resulted in millions of dollars loss. The results show the effectiveness of our proposed mutation operators in detecting real faults in Solidity smart contracts. We have also extended {\em Universal Mutator } tool with our mutation operators, so that it can automatically generate mutants for smart contracts written in Solidity.
Jiaming Ye, Mingliang Ma, Yun Lin, Lei Ma · 6 authors
Recent years have seen smart contracts are getting increasingly popular in building trustworthy decentralized applications. Previous research has proposed static and dynamic techniques to detect vulnerabilities in smart contracts. These tools check vulnerable contracts against several predefined rules. However, the emerging new vulnerable types and programming skills to prevent possible vulnerabilities emerging lead to a large number of false positive and false negative reports of tools. To address this, we propose Vulpedia, which mines expressive vulnerability signatures from contracts. Vulpedia is based on the relaxed assumption that the owner of contract is not malicious. Specifically, we extract structural program features from vulnerable and benign contracts as vulnerability signatures, and construct a systematic detection method based on detection rules composed of vulnerability signatures. Compared with the rules defined by state-of-the-arts, our approach can extract more expressive rules to achieve better completeness (i.e., detection recall) and soundness (i.e., precision). We further evaluate Vulpedia with four baselines (i.e., Slither, Securify, SmartCheck and Oyente) on the testing dataset consisting of 17,770 contracts. The experiment results show that Vulpedia achieves best performance of precision on 4 types of vulnerabilities and leading recall on 3 types of vulnerabilities meanwhile exhibiting the great efficiency performance.
It is increasingly popular to leverage the wisdom of crowd for knowledge discovery and monetization. Among others, crowdsensing with truth discovery has emerged as a promising way for leveraging the crowd wisdom, which can mine reliable knowledge from the generally unreliable sensory data contributed collected from diverse sources. Building a knowledge marketplace based on crowdsensing with truth discovery for knowledge discovery and monetization, however, is non-trivial and has to overcome several challenges. First, the sensory data should be protected as they may carry sensitive information. Second, many real crowdsensing applications usually yield sensory data in a streaming fashion, posing the demand that truth discovery should be conducted over data streams to continuously mine reliable knowledge in each data collection epoch. Third, knowledge monetization should be well treated, fully addressing the practical needs of parties in the monetization ecosystem. In this article, we take the first research attempt and propose a new full-fledged framework for building a secure knowledge marketplace over crowdsensed data streams. Our marketplace supports secure monetization of reliable knowledge mined privately from data streams in crowdsensing applications. Our framework leverages lightweight cryptographic techniques like additive secret sharing to enable privacy-preserving streaming truth discovery, continuously producing reliable knowledge over data streams. For monetization of the learned truth, i.e., knowledge, we resort to the emerging blockchain technology and deliver a tailored and full-fledged design, which promises monetization fairness, knowledge confidentiality, and streamlined processing. Extensive experiments on Amazon cloud and Ethereum blockchain demonstrate the practically affordable performance of our design.
For the modern world where data is becoming one of the most valuable assets,\nrobust data privacy policies rooted in the fundamental infrastructure of\nnetworks and applications are becoming an even bigger necessity to secure\nsensitive user data. In due course with the ever-evolving nature of newer\nstatistical techniques infringing user privacy, machine learning models with\nalgorithms built with respect for user privacy can offer a dynamically adaptive\nsolution to preserve user privacy against the exponentially increasing\nmultidimensional relationships that datasets create. Using these privacy aware\nML Models at the core of a Federated Learning Ecosystem can enable the entire\nnetwork to learn from data in a decentralized manner. By harnessing the\never-increasing computational power of mobile devices, increasing network\nreliability and IoT devices revolutionizing the smart devices industry, and\ncombining it with a secure and scalable, global learning session backed by a\nblockchain network with the ability to ensure on-device privacy, we allow any\nInternet enabled device to participate and contribute data to a global privacy\npreserving, data sharing network with blockchain technology even allowing the\nnetwork to reward quality work. This network architecture can also be built on\ntop of existing blockchain networks like Ethereum and Hyperledger, this lets\neven small startups build enterprise ready decentralized solutions allowing\nanyone to learn from data across different departments of a company, all the\nway to thousands of devices participating in a global synchronized learning\nnetwork.\n
Muqaddas Naz, Fahad Ahmed Al-Zahrani, Rabiya Khalid, Nadeem Javaid · 7 authors
In a research community, data sharing is an essential step to gain maximum knowledge from the prior work. Existing data sharing platforms depend on trusted third party (TTP). Due to the involvement of TTP, such systems lack trust, transparency, security, and immutability. To overcome these issues, this paper proposed a blockchain-based secure data sharing platform by leveraging the benefits of interplanetary file system (IPFS). A meta data is uploaded to IPFS server by owner and then divided into n secret shares. The proposed scheme achieves security and access control by executing the access roles written in smart contract by owner. Users are first authenticated through RSA signatures and then submit the requested amount as a price of digital content. After the successful delivery of data, the user is encouraged to register the reviews about data. These reviews are validated through Watson analyzer to filter out the fake reviews. The customers registering valid reviews are given incentives. In this way, maximum reviews are submitted against every file. In this scenario, decentralized storage, Ethereum blockchain, encryption, and incentive mechanism are combined. To implement the proposed scenario, smart contracts are written in solidity and deployed on local Ethereum test network. The proposed scheme achieves transparency, security, access control, authenticity of owner, and quality of data. In simulation results, an analysis is performed on gas consumption and actual cost required in terms of USD, so that a good price estimate can be done while deploying the implemented scenario in real set-up. Moreover, computational time for different encryption schemes are plotted to represent the performance of implemented scheme, which is shamir secret sharing (SSS). Results show that SSS shows the least computational time as compared to advanced encryption standard (AES) 128 and 256.