A. Sasikumar, Logesh Ravi, Ketan Kotecha, Jatinderkumar R. Saini · 6 authors
In recent years, the Internet of Things (IoT) has been industrializing in various real-world applications, including smart industry and smart grids, to make human existence more reliable. An overwhelming volume of sensing data is produced from numerous sensor devices as the Industrial IoT (IIoT) becomes more industrialized. Artificial Intelligence (AI) plays a vital part in big data analyses as a powerful analytic tool that provides flexible and reliable information insights in real-time. However, there are some difficulties in designing and developing a useful big data analysis tool using machine learning, such as a centralized approach, security, privacy, resource limitations, and a lack of sufficient training data. On the other hand, Blockchain promotes a decentralized architecture for IIoT applications. It encourages the secure data exchange and resources among the various nodes of the IoT network, removing centralized control and overcoming the industry's current challenges. Our proposed approach goal is to design and implement a consensus mechanism that incorporates Blockchain and AI to allow successful big data analysis. This work presents an improved Delegated Proof of Stake (DPoS) algorithm-based IIoT network that combines Blockchain and AI for real-time data transmission. To accelerate IIoT block generation, nodes use an improved DPoS to reach a consensus for selecting delegates and store block information in the trading node. The proposed approach is evaluated regarding energy consumption and transaction efficiency compared with the exciting consensus mechanism. The evaluation results reveal that the proposed consensus algorithm reduces energy consumption and addresses current security issues.
Digital collection and maintenance of evidence corresponding to an accident is of utmost relevance as vehicles become connected and part of Internet of things ecosystem. A conceptual evidence management framework is proposed examining the future of accident investigation forensics in the era of connected vehicles. The framework discusses how evidence generated from vehicles involved in incident along with supporting evidence from nearby vehicles CCTVs and road users can be collected and managed over blockchain using smart contracts in a vehicle to everything connected environment. The management of evidence over blockchain serves as an immutable and auditable means to investigate and settle cases post an accident among the stakeholders. Dynamic access control over evidence data and reports based on location of incident and vehicle involved is implemented with the help of smart contracts. The cost of deploying and carrying out transactions using the smart contracts is evaluated over both public and private Ethereum blockchain. Mechanism and cost involved in storing evidence on chain versus off chain using Inter Planetary File System in most optimised manner saving memory and execution cost is compared and presented. The smart contract codes are deployed on Rinkeby test network and can be accessed using address mentioned.
D. Palanikkumar, Adel Fahad Alrasheedi, Pavithra Parthasarathi, S. S. Askar · 5 authors
Data management becomes essential component of patient healthcare. Internet of Medical Things (IoMT) performs a wireless communication between E-medical applications and human being. Instead of consulting a doctor in the hospital, patients get health related information remotely from the physician. The main issues in the E-Medical application are lack of safety, security and privacy preservation of patient’s health care data. To overcome these issues, this work proposes block chain based IoMT Processed with Hybrid consensus protocol for secured storage. Patients health data is collected from physician, smart devices etc. The main goal is to store this highly valuable health related data in a secure, safety, easy access and less cost-effective manner. In this research we combine two smart contracts such as Practical Byzantine Fault Tolerance with proof of work (PBFT-PoW). The implementation is done using cloud technology setup with smart contracts (PBFT-PoW). The accuracy rate of PBFT is 90.15%, for PoW is 92.75% and our proposed work PBFT-PoW is 99.88%.
Healthcare data is highly sensitive and must be safeguarded. Personal and sensitive data, such as names and addresses, is stored in Encrypted Electronic Health Records (EHRs). This paper proposes a Blockchain-based distributed application platform for Bangladesh’s public and private healthcare service providers. The proposed application framework enables users to create secure digital agreements for commerce or collaboration by leveraging data immutability and smart contracts. As a result, all stakeholders can collaborate securely over the same Blockchain network, taking advantage of their data’s openness and read/write nature. The proposed application is made up of various application interfaces for various stakeholders. The proposed solution employs Hyperledger Fabric and Blockchain to ensure data integrity, privacy, permissions, and service availability. In the application portal, each user has a profile. The creation of a unique identity for each user, as well as the establishment of digital information centers across the country, has greatly aided the process. This application collects health data from each user in a systematic manner, which is useful for research institutes and healthcare-related organizations. For this application, a national data warehouse in Bangladesh is feasible, and various healthcare-related analyses can be performed using the collected data, assisting the strategy and planning department in making informed decisions regarding the healthcare sector in Bangladesh. Because Bangladesh has both public and private healthcare providers, a simple digital strategy is essential for all organizations to accomplish their services. This study proposes a solution to achieve this goal.
Vahiny Sharma, Ankur Gupta, Najam Ul Hasan, Mohammad Shabaz · 5 authors
Modern healthcare is a data-intensive domain representing an amalgamation of long-term electronic medical records, real-time patient monitoring data, and more recently sensor data from wearable computing. Blockchain in healthcare can address a multitude of challenges in healthcare, including care coordination, data security, and interoperability concerns, as technology advances. Technical challenges such as processing speed and massive data duplication will be resolved as improved technology. This data needs to be accessed seamlessly by a multitude of players from the general physicians to hospitals, medical service providers to insurance companies. Thus, healthcare-related data needs to be verified, securely stored, and shared while maintaining patient privacy and control over what portion of the data is shared, with whom it is shared, and how it is consumed. Blockchain has emerged as a technology stack of choice for distributed authentication, secure storage, and automated analysis of stored data in diverse domains including healthcare. Its distributed nature is a natural fit to the healthcare ecosystem with multiple participating entities and patients in different geographic locations. In this paper, we review the technology of blockchain to the healthcare domain analyzing and classifying work done in the field. Open challenges are identified and future directions for research are also presented.
Samvid B. Pandya, Harshal A. Sanghvi, Riki Patel, Abhijit S. Pandya
Blockchain Technology is considered as an attention-seeking technology and still in its early years according to many researchers. Cryptocurrencies like Bitcoin, Ethereum, Dogecoin and many more have emerged as new area of research for the fintech community as they are using blockchain technology. Bitcoin (BTC) emerged as the first real-world application of the blockchain technology. Bitcoin and other cryptocurrencies depend on the mining of the raw data which is going to be stored in the blocks. These cryptocurrencies depend on crypto mining, which is a complex computation of mathematical equations and problems. To solve these equations and problems, high-powered computing is required. The Graphics Processing Units work on the principle of high-power and high-performance computing. They are also extremely useful for solving complex computation of mathematical equation and problems. We have observed the usage of GPUs to deploy blockchain for mining of cryptocurrencies like Bitcoin, Ethereum, and Dogecoin. The research describes about the applications of GPU and FPGA for deployment of Blockchain for Cryptocurrency.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Maryam Abbasi, Mohammad Hossein Manshaei, Mohammad Ashiqur Rahman, Kemal Akkaya · 5 authors
Algorand is a public proof-of-stake (PoS) blockchain with a throughput of 750 MB of transactions per hour, 125 times more than Bitcoin. While the throughput of Algorand depends on the participation of most of its nodes, rational nodes may behave selfishly and not cooperate with others. To encourage nodes to participate in the consensus protocol, Algorand rewards nodes in each round. However, currently Algorand does not pay transaction fees to participating nodes, rather storing it for future use. In this paper, we show that this current approach of Algorand motivates selfish block proposers to increase their profits by creating empty blocks. Such selfish behavior reduces the throughput of Algorand. Therefore, the price of Algo will decrease in the long run. Because of this price reduction, nodes will leave Algorand, compromising its security. Moreover, lack of an appropriate mechanism to pay fees to participants causes additional issues, such as lack of transparency, centralization, and inability of nodes to prioritize transactions. To overcome this challenge, we design a perfectly competitive market and propose an algorithm for computing optimal transaction fees and block size in Algorand We also propose an algorithm that reduces the cost of Algorand, without compromising its security. We further simulate the Algorand network and show how the optimal transaction fee and block size can be calculated in practice.
Purpose This paper aims to analyze the impact of DARQ technologies (distributed ledger, artificial intelligence, extended reality, quantum computing) in the financial sector, focusing on artificial intelligence (AI) applications in personalized banking, which consists of treating every customer as a segment of one. The research has two main goals. First, providing a complete and organic analysis of the DARQ technologies framework currently missing in the literature. Because this research focuses on the financial sector, more attention is dedicated to DARQ technologies in this industry. Second, studying applications of one of the DARQ technologies, AI, in personalized banking, where it appears to have a great potential impact. Design/methodology/approach The research analyses both the supply side, collecting secondary data from documentation, reports and research studies to study the major trends and results obtained by leading banks, and on the demand side, collecting primary data through a dedicated survey and elaborating opinions and preferences of potential customers. Using this information, a detailed go-to-market plan based on the framework elaborated by Bain and Co. in 2012 is developed, considering the hypothesis of a well-known universal bank, operating globally, with an established brand and access to modern AI technologies, which decides to invest in this field as a priority. Findings In addition to giving a detailed overview of DARQ technologies from a technical and a business perspective, the results related to the hypothetical case of the study help to understand which would be the most suitable target for the launch phase, which value proposition should be offered and how to deliver it, but also how to evolve the project to attract more customers and strengthen the relationship with the existing ones. Nevertheless, this research could be a starting point for future studies and updates, considering related evolutions, investigating more representative demand samples or analyzing how the combination of more DARQ technologies could be applied to the financial sector. Research limitations/implications Some limitations affect this work. First, the topics studied are evolving rapidly and partially dependent on other innovations under development; therefore, they may become obsolete and less significant in the next years. As regard the data collection, the supply-side analysis involves strategical information kept private by companies; therefore, the collected data probably miss some useful details. As concerns primary data, the sample could have been larger and more heterogeneous and biases and misinterpretations could have affected the answers. A compromise has been found between the time and resources available and the qualitative and quantitative characteristics of the sample. Practical implications This research could be a tool for financial companies interested in investing in AI for personalized banking, but it also provides useful insights about the whole DARQ framework, which could be interesting for all the financial and nonfinancial firms. Applying AI effectively and efficiently could offer great benefits, both economic and noneconomic, to financial firms but also to their customers, who could benefit from hyper-tailored services at a reasonable and affordable price, whereas in the past, they were reserved only for very important person clients. This win-win situation could lead the way to further investments and consequent innovations in the future. Social implications Some issues still exist, mainly about data security and privacy, but also the social risk linked to the labor market due to the AI substitution for some tasks and the related shift in professionals required by employers, which could negatively affect the salary gap among workers with different levels of educations, tightening up existing inequality problems. An effort by public and private subjects will be required to make this transition inside the labor market smoother. Despite this, the research shows that AI applications in personalized m-banking could mutually benefit both the demand and the supply of the market. Originality/value Apart from the organic overview offered on DARQ technologies and their related business applications, currently missing in the literature, which could be useful for a better comprehension of the topic and could also give interesting insights to firms, this research presents an original and concrete roadmap to follow for financial companies interested in delivering a personalized mobile banking service leveraging on AI. Every step presented in the output of this work is based on an in-depth analysis of past, and present actions carried out and result obtained by competitive firms on the market and on needs and preferences observed among potential customers.
Mahendra Kumar Shrivas, Srujan Kachhwaha, Ashok Bhansali, Satya Vir Singh
The production of fraudulent academic certificates has become a global issue. People with unethical thinking try to arrange fraud certificates to authorize themselves to exploit and access various high-end paying jobs and advance their careers. Therefore, this problem leads to identity masquerade. There are different blockchain-based solutions to store and validate these university transcripts and educational credentials, intended to provide decentralized exposure to the system. However, most blockchain-based system designs and platforms use pre-quantum cryptography on either public or private Blockchain and do not cover the whole ecosystem. The current systems cannot survive majority and quantum attacks. This paper uses Post Quantum Cryptography (PQC) powered Lattice-Based Cryptosystems and Hash-Based Signature (HBS) in the proposed system on a consortium-based blockchain solution to shield the distributed network from various attacks making it quantum-proof. The proposed system is indented to bring all the stakeholders under a well-defined process of issuance, recording, sharing, and verification of academic and professional educational credentials under a quantum-proof immutable distributed ledger to promote transparency and tamper-proofing to prevent ongoing frauds. The proposed system provides a better privacy mechanism, incorporates access and consent-based sharing control, secure from quantum and majority attacks and does not required any cryptocurrencies or tokens.
Due to its distributed, decentralized and secure nature, data stored within blockchain can not be modified easily by an unauthorized party and because of this it has become the preferred technology for record keeping. Today, every application domain where data or records need to be stored in a secure manner, are migrating to blockchain. Though blockchain provides a secure and convenient way of record keeping, like any other technology, it too suffers from some challenges such as high transaction processing time, resource wastage, and certain types of attacks. This paper provides a systematic review of the various application areas of blockchain and the challenges there in.
Zhaoxin Yang, Ruizhe Yang, F. Richard Yu, Meng Li · 6 authors
Immutability, decentralization, and linear promoted scalability make the sharded blockchain a promising solution, which can effectively address the trust issue in the large-scale Internet of Things (IoT). However, currently, the throughput of sharded blockchains is still limited when it comes to high proportion of cross-shard transactions (CSTs). On the other hand, the assemblage characteristic of the collaborative computing in IoT has not been received attention. Therefore, in this article, we present a clustering-based sharded blockchain strategy for collaborative computing in the IoT, where the sharding of the blockchain system is implemented in two steps:K-means-clustering-based user grouping and the assignment of consensus nodes. In this framework, how to reasonably group the IoT users while simultaneously guaranteeing the system performance is the key point. Specifically, we describe the data transactions among IoT devices by data transaction flow graph (DTFG) based on a dynamic stochastic block model. Then, formed as a Markov decision process (MDP), the optimization of the cluster number (shard number) and the adjustment of consensus parameters are jointly trained by deep reinforcement learning (DRL). Simulation results show that the proposed scheme improves the scalability of the sharded blockchain in the IoT application.
Kazi Tamzid Akhter Md Hasib, Ixion Chowdhury, Saadman Sakib, Mohammad Monirujjaman Khan · 7 authors
Bangladesh should have owned a decentralized medical record server. We face a lot of issues, such as doctor’s appointments, report organization in one spot, and report follow-ups. People now bring a large number of papers to the doctor’s chamber. They carry prescriptions, reports, and X-ray files, among other things. It complicates everyone’s life as a result. All of the reports must be reviewed by doctors on a regular basis. It is difficult to read old reports on a regular basis, and patients do not receive the correct medications or treatment. Doctors also find it extremely difficult to comprehend handwritten prescriptions. Data security, authenticity, time management, and other areas of data administration are dramatically improved when blockchain (smart contract) technology is linked with standard database management solutions. Blockchain is a groundbreaking, decentralized technology that protects data from unauthorized access. After smart contracts are implemented, the management will be satisfied with the patients. As a result, maintaining data privacy and accountability in the system is tough. It signifies that the information is only accessible to those who have been authenticated. This study focuses on limiting third-party engagement in medical health data and improving data security. Throughout the process, this will improve accessibility and time efficiency. People will feel safer during the payment procedure, which is the most significant benefit. A smart contract and a peer-to-peer encrypted technology were used. The hacker will not be able to gain access to this system since this document uses an immutable ledger. They will not be able to change any of the data if they gain access to the system. If the items are found to be defective, the transaction will be halted. Transaction security will be a viable option for recasting these problems using cryptographic methodologies. We developed a website where patients and doctors will both benefit because of the use of blockchain technology to ensure the security of medical data. We have different profiles for doctors and patients. In the patient profile, they can create their own account by using a unique address, name, and age. This unique address will be created from the genesis block. The unique address is completely private to the owner, who will remain fully secure in our network. After creating an account, the patient can view the doctors’ list and they can upload their medical reports such as prescriptions and X-rays. All the records uploaded by the patient will be stored on our local server (Ganache). The records are stored as hashed strings of the data. Those files will also have a unique address, and it will be shown in the patient profile. After granting access, the doctors will be able to view their records in the respective doctor’s profile. For accessing the options such as uploading, viewing, or editing the data, Ethereum currency (a fee) will have to be paid in order to complete the request. On the other hand, doctors can enter their profile using their name and unique address. After logging in, they can view their name, unique address, and the list of patients that have granted access to the doctor to view their files. On our website, the front end is handled by JavaScript, ReactJS, HTML, and CSS. The backend is handled by Solidity. Storage is handled by Ganache as the local host. Finally, this paper will show how to ensure that the procedure is as safe as feasible. We are also maintaining transparency and efficiency here.
Blockchain is one of the prominent rapidly used technology in the last decade in various applications. In recent years, many researchers explored the capabilities of blockchain in smart IoT to address various security challenges. Integration of IoT and blockchain solves the security problems but scalability still remains a huge challenge. To address this, various AI techniques can be applied in the blockchain IoT framework, thus providing an efficient information system. In this survey, various works pertaining to the domains which integrate AI, IoT and Blockchain has been explored. Also, this article discusses potential industrial use cases on fusion of blockchain, AI and IoT applications and its challenges.
Aitizaz Ali, Muhammad Fermi Pasha, Jehad Ali, Ong Huey Fang · 7 authors
Due to the value and importance of patient health records (PHR), security is the most critical feature of encryption over the Internet. Users that perform keyword searches to gain access to the PHR stored in the database are more susceptible to security risks. Although a blockchain-based healthcare system can guarantee security, present schemes have several flaws. Existing techniques have concentrated exclusively on data storage and have utilized blockchain as a storage database. In this research, we developed a unique deep-learning-based secure search-able blockchain as a distributed database using homomorphic encryption to enable users to securely access data via search. Our suggested study will increasingly include secure key revocation and update policies. An IoT dataset was used in this research to evaluate our suggested access control strategies and compare them to benchmark models. The proposed algorithms are implemented using smart contracts in the hyperledger tool. The suggested strategy is evaluated in comparison to existing ones. Our suggested approach significantly improves security, anonymity, and monitoring of user behavior, resulting in a more efficient blockchain-based IoT system as compared to benchmark models.
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.
The Internet of Things(IoT) has changed the world into a smart and autonomous world. The way in which we interact with each other and with the environment has changed.The IoT is experiencing exponential growth in research and industry, but still suffers from privacy and security issues. The integration of blockchain technology with Internet of Things (IoT) has resolved many challenges faced by Internet of Things (IoT) such as decentralization, poor interoperability, privacyand security vulnerabilities. Blockchain when combined with IoT can solve many challenges of IoT systems. This integration will come out to be the better system for the environment in many aspects specially security which is the most important aspect to be considered. Also, the distributed ledger of Blockchain which when used in IoT can resolve many issues like scalability and authenticity. However, the integration of Blockchain technology with IoT originates various challenges like storage capacity and scalability, security, anonymity and data privacy etc. We first introduce Blockchain with Internet of Things (IoT) and key characteristic of this integration. We will also concentrate the issued resolved by blockchain technology in Internet of Things (IoT). The main concern of this paper is to discuss the various challenges of integration of blockchain into IoT.
A. Manimaran, Chandramohan Dhasarathan, N. Arulkumar, Naveen Kumar S N
The internet of things (IoT) represents rapid development in research and industry that enables both virtual and physical objects to be linked and transfers information in order to produce various services that enhance our excellence of life. Traditional security and privacy methods are not applicable for IoT, mostly due to their topological constraints and versatility of IoT devices. Blockchain technology has started to fascinate younger generations because it works especially well in the digital world. Blockchain is suitable for internet of things applications. Advancements in IoT have propelled distributed systems. The blockchain concept demands a method for exchanging and storing data that is managed by a decentralized network. The rise of IoT applications is hindered by these obstacles. One option to fix these problems is to use a distributed ledger technology using blockchain technology. This chapter gives a comprehensive overview of blockchain's strengths and weaknesses with its applications.
Salma Khan, Muhammad Gulistan, Nasreen Kausar, Sajida Kousar · 6 authors
One of the most important innovations brought by digitization is the cryptocurrency, also called virtual or digital currency, which has been discussed in recent years and in particular is a new platform for investors. Different types of cryptocurrencies such as Bitcoin, Ethereum, Binance Coin, and Tether do not depend on a central authority. Decision making is complicated by categorization and transmission of uncertainty, as well as verification of digital currency. The weighted average and weighted geometric aggregation operators are used in this article to define a multi‐attribute decision‐making approach. This work investigates the uniqueness of q‐rung orthopair fuzzy hypersoft sets (q‐ROFHSS), which respond to instabilities, uncertainty, ambiguity, and imprecise information. This research also covers some fundamental topics of q‐ROFHSS. The model offered here is the best option for learning about electronic currency. This study validates the complexity of decision‐making problems with different attributes and subattributes to obtain an optimal choice. We conclude that Bitcoin has a diverse set of applications and that crypto assets are well positioned to become an important asset class in decision making.
Blockchain is a distributed public ledger that keeps track of all transactions that have ever taken place in the system. As a distributed ledger, a consensus mechanism is required to ensure all the transaction functions properly. In order to reach a consensus, it is critical to emphasize the importance of performance and efficiency. The use of the right consensus algorithm will significantly improve the efficiency of a blockchain application. This paper reviewed several types of consensus algorithms used in blockchain and discusses the idea of a new consensus algorithm that can improve the performance of consortium blockchain.
The Ethereum blockchain permits the development and deployment of smart contracts which can store and execute code 'on-chain' - that is, entirely on nodes in the blockchain's network. Smart contracts have traditionally been used for financial purposes, but since smart contracts are Turing-complete, their algorithmic scope is broader than any single domain. To that end, we design, develop, and deploy a comprehensive 3D rendering engine programmed entirely in Ethereum smart contracts, called Shackled. Shackled computes a 2D image from a 3D scene, executing every single computation on-chain, on Ethereum. To our knowledge, Shackled is the first and only fully on-chain 3D rendering engine for Ethereum. In this work, we 1) provide three unique datasets for the purpose of using and benchmarking Shackled, 2) execute said benchmarks and provide results, 3) demonstrate a potential use case of Shackled in the domain of tokenised generative art, 4) provide a no-code user interface to Shackled, 5) enumerate the challenges associated with programming complex algorithms in Solidity smart contracts, and 6) outline potential directions for improving the Shackled platform. It is our hope that this work increases the Ethereum blockchain's native graphics processing capabilities, and that it enables increased use of smart contracts for more complex algorithms, thus increasing the overall richness of the Ethereum ecosystem.