Ethereum Blockchain Research Articles

DPoSEB: Delegated Proof of Stake with Exponential Backoff Consensus Algorithm for Ethereum Blockchain

Blockchain is a technology that is rapidly gaining prominence and finding applications in various sectors such as banking, supply chain, healthcare, and e-governance. The consensus algorithm employed in a blockchain network is crucial as it directly impacts the network's performance and security. Different consensus techniques exist, including Proof of Work (PoW), Proof of Stake (PoS), Robust Proof of Stake (RPoS), and Delegate Proof of Stake (DPoS), each with its own set of advantages and disadvantages. In this work, we propose a new consensus algorithm called Delegated Proof of Stake with Exponential Back-off (DPoSEB). DPoSEB utilizes a stake-based selection of delegates and employs an exponential back-off technique to mitigate collisions among nodes within the network. Each delegate is assigned a random sleep time, and the node with the shortest wake-up time is chosen to mine the block for that particular round. However, collisions among nodes can still occur. To provide a fair chance for each delegate node, collided nodes are assigned an exponential back-off time. We implement our proposed algorithm on an Ethereum-based private blockchain network. To evaluate the effectiveness of our proposed work, we compare it with existing consensus mechanisms such as PoS (version 2) and Delegated RPOS with downgrading (DDRPOS) using different scenarios in terms of transaction latency, waiting time, and fairness as evaluation metrics. The results reveal that DPoSEB performs better than POS and DDRPOS.

Blockchain-Based Car Rental Platform

Abstract: Carpooling has seen a significant upsurge in popularity in recent years since it relieves commuters of the burden of driving a car and later spares them from the mad dash to locate a parking space. The industry now uses centralised database servers, which puts the system at risk of hacking, causes data leaks, and undermines security within the system. Additionally, there is a chance that the owner will misuse the data in a centralised system. Since the newly developed Blockchain technology provides complete anonymity and database transparency, data security and traceability may be guaranteed across the entire server. The goal of the suggested solution is to create and implement a blockchain-based, smart contract-based peer-to-peer vehicle sharing system. The Solidity programming language is utilised to carry out the smart contracts. Ethereum blockchain is used in the ecosystem's construction. Eliminating the middleman would result in a peer-to- peer (P2P) car-sharing programme, which would reflect decreased costs and exposure to data theft.

IoT Forensic Cyber Activities Detection and Prevention with Automated Machine Learning Model

The Internet of Things (IoT) has been deployed in a vast range of applications with exponential increases in data size and complexity. Existing forensic techniques are not effective for the accuracy and detection rate of security issues in IoT forensics. Cyber forensic comprises huge volume constraints that are processing huge volumes of data in the Information and Communication Technology (ICT) comprised of IoT devices and platforms. Trust blockchain is effective technology those are utilized to assess the tamper-proof records in all transaction in the IoT environment. With the implementation of trust blockchain the record and transaction are processed with a distributed ledger that is managed by the network nodes. The challenge associated with the trust blockchain in IoT forensics is cost and security. To achieve significant cost-effectiveness organizations, need to evaluate the risks and benefits associated with IoT forensics in the trust blockchain technology. In this paper, developed a Block Chain Enabled Cyber-Physical system with distributed storage. The developed Blockchain model is termed as Integrated Hadoop Blockchain Forensic Machin Learning (IHBF-ML). The IHBF-ML model uses the Hadoop Distributed File System (HDFS) with cyberspace to improve security. Within the IHBF-ML model, IoT data communication is established with the smart contract. The smart contract-based blockchain process uses the Machine Learning model integrated with Cat Boost classification model for anomaly detection. Cost in IoT forensic is minimized with the parallel processing of the data through MapReduce Framework for the traffic translation, extraction, and analysis of the dynamic feature traffic from the IoT environment. The experimental analysis stated that constructed IHBF-ML model reduces the cost by ~25% than the other conventional blockchain Ethereum and EOS.

Blockchain-enabled framework for transactive home energy management with cloud energy storage under uncertainties

In modern paradigm of smart grid, prosumers can trade energy peer-to-peer in a transactive energy market to reduce energy costs and improve energy efficiency. In addition, cloud energy storage (CES) is a type of shared energy storage systems with high economic efficiency that can provide energy storage services for prosumers and become an active player in energy trading. However, transactive energy implementation in power systems has several challenges such as data privacy and security. In existing researches, energy trading mechanisms rely on central authorities, where security and privacy cannot be maintained. Therefore, this paper presents a decentralized stochastic optimization model of transactive energy management based on blockchain in the presence of CES. In this framework, the smart contract based on Alternating Direction Method of Multipliers technique is deployed on the Ganache and Ethereum blockchains, and the YALMIP toolbox along with CPLEX solver handle decentralized optimization in the MATLAB software. The numerical results demonstrate that not only the capacity of distributed generations is fully utilized, but also total costs of smart homes are reduced by more than 27%, and the total grid’s delivery power to smart homes is decreased by more than 24% compared to the inflexible scheduling.

MIoT-CDPS: Complete decentralized privacy-preserving scheme for medical internet of things

Medical internet of things (MIoT) environments continue to expand, and numerous MIoT services are available to improve the quality of human life. However, these services, facilitated by a multitude of interconnected IoT devices analyzing the environment, face significant security challenges due to the volume of interconnected devices and the exchange of data through open channels. Moreover, the vulnerability is exacerbated by the centralized infrastructure commonly used by IoT services, where compromising a trusted third party (TTP) or service provider jeopardizes the entire system’s security. Existing privacy-preserving schemes for IoT, while aiming for decentralization, often rely on a TTP to sustain the system. In such environments, users typically either entrust their secret keys and parameters to a TTP or store their data in cloud servers. Consequently, as the TTP assumes control over the actual keys and data, a significant challenge arises regarding the assurance of user and data sovereignty. In this paper, we propose a complete decentralized privacy-preserving scheme for MIoT that ensures data self-sovereignty, transparency, and complete decentralization without TTP intervention. In the proposed scheme, users can directly manage their keys with secret parameters. Then, they can upload encrypted data directly to distributed storage and securely share it with other users based on the security levels they have set themselves. We perform informal and formal (mathematical and simulation) security analysis to prove the security of the proposed scheme and conduct comparative analysis to evaluate the security functionalities, communication costs, and computational costs of our scheme compared with those of previous schemes. Further, we implement our scheme in a practical setting through simulations on Ethereum blockchain networks, validating its complete decentralization, security, efficiency, and suitability for MIoT environments. The specificity of our research lies in addressing the critical security concerns inherent in MIoT through a complete decentralized, TTP-independent framework.

A blockchain-based academic degree attestation system

ABSTRACT We propose a novel blockchain-based academic degree verification system. The system relies on a smart contract deployed on the Ethereum blockchain platform. The system protects the privacy of the students who have been verified without the need of encryption, and hence, avoid the complexity of security key management and the potential disaster if the keys are stolen or revealed. The amount of degree data is also designed to be minimum for proper verification. All operations on the critical path of the system are automated without any human intervention. However, the system does assume that the organization would stand behind the proposed system to ensure the system's integrity. The system is open to anyone who wishes to verify the degree of a student. To prevent spamming and to support the long-term sustainability of the system, a small fee is charged for each verification request. A portion of the fees collected is immediately credited to the participating schools. To facilitate automated school enrollment into the system, any school may request to enroll by placing a significant amount of stake in ETH. The stake can be refunded when the school decides to leave the system. However, if the school is blacklisted due to misbehavior, the stake is confiscated. This design strongly discourages adversaries from abusing the system. The performance of the system is fully characterized with regard to the gas consumption of key operations in various use cases. We demonstrate that the system is conducive for long-term sustainability.

Towards a semantic blockchain: A behaviouristic approach to modelling Ethereum

Decentralised ledgers are gaining momentum following the interest of industries and people in smart contracts. Major attention is paid to blockchain applications intended for trading assets that exploit digital cryptographic certificates called tokens. Particularly relevant tokens are the non-fungible tokens (NFTs), namely, unique and non-replicable tokens used to represent the cryptographic counterpart of assets ranging from pieces of art through to licenses and certifications. A relevant consequence of the hard-coded nature of blockchains is the hardness of probing, in particular when advanced searchers involving the capabilities of the smart contracts or the assets digitised by NFTs are required. For this purpose, a formal representation for the operational semantics of smart contracts and of tokens has become particularly urgent, especially in economy and finance, where blockchains become increasingly relevant. Hence, we feel the need to tailor Semantic Web technologies to achieve that semantic representation at least for NFTS. This article reports on an ontology that leverages the Ontology for Agents, Systems, and Integration of Services (“OASIS”) towards the semantic representation of smart contracts responsible for managing ERC721-compliant NFTs and running on the Ethereum blockchain. Called Ether-OASIS, the proposed ontology adopts OASIS and tailors its behaviouristic approach to the Ethereum blockchain by conceiving smart contracts as agents running on the blockchain and, consequently, smart contract interactions as agent commitments. Smart contracts are represented in terms of their actions, purposes and tokens that they manage, thus realising a blockchain that is more usable both by users and automated applications. The ontology is evaluated using standard ontological metrics and applied on a case study concerning the minting and transferring of NFTs that digitise batches of wheat.

Development of cryptogames with Unity on an Ethereum Blockchain Test Network: Case Study and Challenges

Development of cryptogames with Unity on an Ethereum Blockchain Test Network: Case Study and Challenges

Analyzing voting power in decentralized governance: Who controls DAOs?

We empirically study the state of three prominent DAO governance systems on the Ethereum blockchain: Compound, Uniswap and Ethereum name service (ENS). In particular, we examine how the voting power is distributed in these systems. Using a comprehensive dataset of all governance token holders, delegates, proposals, and votes, we analyze who holds the voting power and how this power is being used to influence governance decisions. While we reveal that the majority of voting power is concentrated in the hands of a small number of addresses, we rarely observe these powerful entities overturning a vote by choosing a different outcome than that of the overall community and less influential voters.

Ftdho Zfnet: Block chain based Fractional Tasmanian Devil Harris optimization enabled deep learning using attack detection and mitigation

Block chain technology is regarded for enhancing the characteristics of security because of decentralized design, safe distributed storage, and privacy. However, in recent times the present situation of block chain technology has experienced some crisis that may delay the quick acceptance and utilization in real-time applications. To conquer this subdues, a blockchain based system for attack detection and mitigation with Deep Learning (DL) named Fractional Tasmanian Devil Harris Optimization_Zeiler and Fergus network (FTDHO_ZFNet) is introduced. In this investigation, the entities utilized are owner, block chain, server, trusted authority and user. Here, authentication phase is done by means of Ethereum block chain by Key Exchange module and privacy preserved data sharing and communication is also done. Then, recorded log file creation is executed by the below mentioned stages. At first, a log file is generated with the basis of communication to record the events. After wards, the features are extracted by BoT-IoT database. Then, feature fusion is done by overlap coefficient utilizing Deep Q-Network (DQN). Moreover, data augmentation (DA) is doneusing bootstrapping method. At last, attack detection is observed by ZFNet tuned by FTDHO. Here, FTDHO is unified by Fractional Tasmanian Devil Optimization (FTDO) and Harris Hawks Optimization (HHO). Additionally, FTDO is integrated by Fractional Calculus (FC) concept and Tasmanian devil optimization (TDO). Furthermore, attack mitigation is performed. The performance measures applied for FTDHO_ZFNet are accuracy, and True Negative rate (TNR), observed supreme values with 92.9%, 93.8% and 92.9%.

Blockchain-Based Quality Assurance System for Academic Programs

Nowadays, technology is increasingly being adopted in different kinds of businesses to process, store, and share sensitive information in digital environments that include enormous numbers of users. However, this has also increased the likelihood of cyberattacks and misuse of information, potentially causing severe damage. One promising technology, which can provide the required security services with an improved level of efficiency, is blockchain. This research explores the use of Ethereum blockchain and smart contracts to create a secure and efficient quality assurance system (QAS) for academic programs. By utilizing blockchain and smart contracts, the proposed approach improves the integrity and reliability of sensitive information processed by the QAS, promotes transparency and governance, and reduces the time and effort required for quality operations. The current approach uses an additional access control layer to further enhance user privacy. Smart contracts automate various quality transactions and saves time and resources, and hence increases the efficiency of the QAS. The interplanetary file system (IPFS) is used to address the challenge of size limitations in blockchain. Additionally, this research investigates the use of various cryptographic schemes to provide robust security services at the application layer. The experimental results showed that the use of a hybrid cryptosystem relying on an Elliptic curve digital signature and AES encryption (AES_ECCDSA) outperforms other counterparts’ cryptosystems using an RSA digital signature and AES encryption (AES_RSADSA) and Elliptic Curve Integrated Encryption Scheme (ECIES) in terms of speed. The performance results showed that AES_ECCDSA consumes 188 ms to perform the required cryptographic operations for a standard-quality document with a size of 8088 KB, compared to the 231 ms and 739 ms consumed by the AES_RSADSA and ECIES schemes, respectively. This study presents a prototype implementation of the blockchain-based QAS, which outlines the processing model and system requirements for key QAS processes. It has been found that the cost and time required for blockchain operations vary depending on the size of the input data—a larger data size requires more time and costs more to process. The results of the current study showed that the time delay for blockchain transactions ranges from 15 to 120 s, while the cost ranges from USD 50 to USD 400. This research provides evidence that blockchain and smart contract technologies have the potential to create a secure, efficient, and trustworthy QAS environment for academic programs.

Investment Decision Factors of Non-Fungible Tokens in the Czech Republic: Survey

Abstract Non-fungible Tokens (NFTs), represent a revolution in the digital ownership paradigm. NFTs are a kind of digital asset built on blockchain technology, most commonly the Ethereum blockchain, that validate the uniqueness and ownership of a unique digital item in question. Each NFT carries specific information or attributes that make it original and non-fungible. Unlike cryptocurrencies like Bitcoin or Ethereum, which are identical to each other, non-fungible tokens cannot be exchanged on a like-for-like basis making them non-fungible. NFTs are traded for cryptocurrencies via online trading platforms. Investment in NFTs can present a risky situation due to the large volatility of the assets in a quite short time. This article focuses on identification of key aspects that influence decision making process of potential investors who are considering buying non-fungible tokens as an investment tool in the Czech Republic. From the point of view of investment decision-making, the primary factors appear to be the expected income from the investment, its payback period, and the risk that the investor undertakes. It has been proven that there is a degree of dependence between gender and the mentioned decision-making factors. The research showed that men are more inclined to make decisions based on expected returns, while women are more likely to make decisions based on perceived risk.

Decentralized Chatting Application Using Blockchain Technology

Abstract: The emergence of blockchain technology has spurred innovation in various domains, including decentralized communication systems. In this context, a decentralized chat application leveraging blockchain, Remix Ethereum IDE, Ganache blockchain, and MetaMask offers a novel approach to secure and privacy-centric messaging. The application harnesses blockchain's immutable ledger to store chat messages, ensuring data integrity and censorship resistance. Remix Ethereum IDE provides developers with a robust environment for crafting smart contracts, the backbone of the chat application's functionality. Developers can design and deploy smart contracts defining chatroom logic, message encryption, and user authentication. Ganache blockchain serves as a local testing environment, enabling developers to validate smart contracts and simulate blockchain interactions in a controlled setting. This facilitates rapid iteration and debugging during the development phase. MetaMask acts as the gateway for users to access the decentralized chat application. Through MetaMask, users authenticate securely using their Ethereum wallets, ensuring pseudonymous identity verification and enabling seamless interaction with the Ethereum blockchain. Together, these technologies form the foundation of a decentralized chat application that prioritizes privacy, security, and user control. By leveraging blockchain and associated tools, the application offers a compelling alternative to centralized messaging platforms, empowering users with sovereignty over their data and communication.

Addressing Vulnerabilities in CAN-FD: An Exploration and Security Enhancement Approach

The rapid advancement of technology, alongside state-of-the-art techniques is at an all-time high. However, this unprecedented growth of technological prowess also brings forth potential threats, as oftentimes the security encompassing these technologies is imperfect. Particularly within the automobile industry, the recent strides in technology have brought about increased complexity. A notable flaw lies in the CAN-FD protocol, which lacks robust security measures, making it vulnerable to data theft, injection, replay, and flood data attacks. With the rising complexity of in-vehicular networks and the widespread adoption of CAN-FD, the imperative to safeguard the protocol has never been more crucial. This paper aims to provide a comprehensive review of the existing in-vehicle communication protocol, CAN-FD. It explores existing security approaches designed to fortify CAN-FD, demonstrating multiple multi-layer solutions that leverage modern techniques including Physical Unclonable Function (PUF), Elliptical Curve Cryptography (ECC), Ethereum Blockchain, and Smart contracts. The paper highlights existing multi-layer security measures that offer minimal overhead, optimal performance, and robust security. Moreover, it identifies areas where these security measures fall short and discusses ongoing research along with suggestions for implementing software and hardware-level modifications. These proposed changes aim to streamline complexity, reduce overhead while ensuring forward compatibility. In essence, the methods outlined in this study are poised to excel in real-world applications, offering robust protection for the evolving landscape of in-vehicular communication systems.

A Geth-based real-time detection system for sandwich attacks in Ethereum

With the rapid development of the Ethereum ecosystem and the increasing applications of decentralized finance (DeFi), the security research of smart contracts and blockchain transactions has attracted more and more attention. In particular, front-running attacks on the Ethereum platform have become a major security concern. These attack strategies exploit the transparency and certainty of the blockchain, enabling attackers to gain unfair economic benefits by manipulating the transaction order. This study proposes a sandwich attack detection system integrated into the go-Ethereum client (Geth). This system, by analyzing transaction data streams, effectively detects and defends against front-running and sandwich attacks. It achieves real-time analysis of transactions within blocks, quickly and effectively identifying abnormal patterns and potential attack behaviors. The system has been optimized for performance, with an average processing time of 0.442 s per block and an accuracy rate of 83%. Response time for real-time detection new blocks is within 5 s, with the majority occurring between 1 and 2 s, which is considered acceptable. Research findings indicate that as a part of the go-Ethereum client, this detection system helps enhance the security of the Ethereum blockchain, contributing to the protection of DeFi users’ private funds and the safety of smart contracts. The primary contribution of this study lies in offering an efficient blockchain transaction monitoring system, capable of accurately detecting sandwich attack transactions within blocks while maintaining normal operation speeds as a full node.

Detecting the provenance of price hike in agri-food supply chain using private Ethereum blockchain network

The rise in the cost of essentials affects every nation around the world, but it has become a major concern for developing nations. It is getting increasingly difficult to keep up with rising prices for everyday items in these countries, where the majority of the population is from the middle class or lower middle class. Inflation, pandemics, wars, and other important variables all contribute to price increases. There may be another significant factor at play, which is supply-chain corruption. The supply chain's unreliable, chaotic, and opaque nature is to blame for this corruption. We are concentrating on the agri-food supply chain in our study. Because many of the current agri-food supply chains are intricate and challenging to monitor, dishonest parties can exploit the situation. Therefore, we suggested a thorough blockchain-based agri-food supply chain to identify the source of price increases. The private Ethereum blockchain was used in the suggested system. Since the private Ethereum blockchain is more efficient, safe, and fast, it was chosen. Smart contracts were created to describe the system and its underlying rules and laws. Furthermore, in order to showcase the usefulness of our smart contracts, we exhibited a sample decentralized application to support our hypothesis. We also gave the system a complete security and vulnerability assessment to make sure it is operating properly and is protected from threats and attacks. Due to the use of blockchain, the system is immutable, transparent, and simple to track and monitor. The proposed system has demonstrated greater transparency, traceability, reliability, speed, security, and cost-efficiency compared to conventional systems. It effectively traces the origin of corruption in the supply chain, providing a more straightforward means to tackle concerns related to price hikes.

COST-EFFECTIVE AND EFFICIENT BLOCKCHAIN FRAMEWORK FOR VERIFYING CERTIFICATE IN YEMENI UNIVERSITIES

Recognizing the necessity to preserve the integrity and good name of degrees awarded by Yemeni universities. It should provide an efficient way of verifying certificates. The effectiveness of the conventional method of confirming the validity of certificates in reducing fraud has not been very strong. Therefore, it is necessary to stop this kind of fraud by using blockchain technology, which has several benefits, such as encryption, sharing of data, and the capacity to store information as permanent data that cannot be altered. Low latency and low cost will be available for the issuance, sharing, and verification of these certifications in universities if the suggested system is implemented. The paper presents the proposed framework, which uses smart contracts in the Ethereum blockchain and a distributed peer-to-peer network (filebase) for certification verification by a certificate’s hash immediately without waiting for the facility’s response. It also contains an estimate of the average cost of publishing a certificate. It also frees students from having to constantly carry paper copies of their documents by enabling them to access them via a certificate's hash. Furthermore, there is no extra cost for the verification process, and it does not require an Ethereum network account.

A blockchain-machine learning ecosystem for IoT-Based remote health monitoring of diabetic patients

Diabetes poses a global health challenge, demanding continuous monitoring and expert care for effective management. Conventional monitoring methods lack real-time insights and secure data-sharing capabilities, necessitating innovative solutions that leverage emerging technologies. Existing centralized monitoring systems often entail risks such as data breaches and single points of failure, emphasizing the necessity for a secure, decentralized approach that integrates the Internet of Things (IoT), blockchain, and machine learning for efficient and secure diabetes management. This paper introduces a decentralized, blockchain-based framework for remote diabetes monitoring, IoT sensors, machine learning models, and decentralized applications (DApps). The proposed framework comprises five layers: the IoT Sensor Layer, which collects real-time health data from patients; the Blockchain Layer, leveraging smart contracts on the Ethereum blockchain for secure data sharing and transactions; the machine learning Layer, analyzing patient data to detect diabetes; and the DApps Layer, facilitating interactions between patients, doctors, and hospitals. For intelligent decision-making regarding diabetes based on data collected from different sensors, nine machine learning algorithms, including logistic regression, K-nearest neighbors (KNN), support vector machine (SVM), Decision Tree, Random Forest, AdaBoost, stochastic gradient boosting (SGD), and Naive Bayes, were trained and tested on the PIMA dataset. Based on the performance evaluation parameters such as accuracy, recall, F1-score, and the area under the curve (AUC), it was found that the AdaBoost model achieved the highest predictive accuracy of 92.64%, followed by the Decision Tree with an accuracy of 92.21% in diabetes classification.

SECURED PAYMENT ON BLOCKCHAIN FOR OUTSOURCING SERVICES IN CLOUD COMPUTING

Cloud computing has revolutionized outsourcing services, yet concerns about online payment security and mutual distrust persist. Existing solutions often rely on trusted third parties, limiting their applicability. To address this, we introduce BPay, a novel framework leveraging blockchain technology to enable a payment system that is both secure and equitable.for outsourcing services without intermediaries. We introduce the system framework, adversary model, and objectives of BPay, emphasizing its compatibility with Bitcoin and Ethereum blockchains. Security and compatibility analyses demonstrate BPay's robustness and efficiency. Cloud computing has revolutionized the manner in which outsourcing services are delivered and accessed, offering unprecedented scalability, flexibility, and cost-effectiveness. However, despite its numerous benefits, concerns about the security of online payments and the lack of trust between users and service providers continue to pose significant challenges. Traditional payment systems often rely on trusted third parties to facilitate transactions, which can introduce vulnerabilities and increase the risk of fraud or data breaches. These limitations hinder the broader adoption of cloud computing in various industries and applications. Keywords:efficient fair payment, blockchain-based technology,RSA algorithm,public key private key,security,Encryption-decryption

RRefined and Effective Integration of Access Control Mechanism in Blockchain Enabled DApp

The combination of the Internet of Things (IoT) and aviation integration with the help of satellite and 6G communication technologies has led to the Internet of Unmanned Aerial Vehicles (UAV) or Internet of Drones (IoD). To host and share large amounts of drone data in real time, cloud-based IoD algorithm Cloudbased IoD is the wrong choice to reduce the weight of mobile drones. However, how to protect the sensitive drone at the fair is a matter of curiosity, and it is very difficult to break the environment where drone use is available and limited resources are available. Although our previous work in SPNCE21 (PATLDAC) developed an air-on middle of the main load of based drone data access control system with privacy policy, limited access time and user tracking, it provides conflicting and centralized cloud data storage for cloud environment and access with unreliable data. It is not reliable in terms of data access and tracking of users. To this end, we propose a blockchainbased privacy data access control (BPADAC) scheme for distributed and secure drone data sharing on cloudbased IoDs. Building on the granular, traceable, and privacypreserving drone data access capabilities of our previous work, we extend this by using blockchain and decentralized hash tables (DHT) to provide secure and reliable wireless access to humanmachine data and storage. as well as reliable and limited access guarantee mechanisms for cloud drone data sharing services. We also set up a public and denial user tracking system to prevent user abuse and deny the traitor. Finally, we propose a prototype for security analysis and performance evaluation using smart contracts on the Ethereum blockchain to demonstrate the feasibility of BPADAC. hash table, attributebased ciphertext encryption policy, and blockchain-based privacy-protected enabled and aware data access control Key Words: Blockchain, UAV,IoD, Distributed Hash Table, Ciphertext-Policy-Attribute-Based-Encryption, blockchainbased privacy-aware data access control