Project description:The traditional data-sharing model relies on a centralized third-party platform, which presents challenges such as poor transaction transparency and unsecured data security. In this article, we propose a blockchain-based traceable and secure data-sharing scheme. Firstly, we designed an attribute encryption-based method to protect data and enable fine-grained shared access. Secondly, we developed a secure data storage scheme that combines on-chain and off-chain collaboration. The InterPlanetary File System (IPFS) is used to store encrypted data off-chain, and the hash value of encrypted data is stored on the blockchain. To improve data security, elliptic curve cryptography (ECC) encryption is performed before the hash value is stored. Finally, we designed a smart contract-based log tracking mechanism. The mechanism stores data sharing records on the blockchain and displays them in a visual form to meet the identity tracking needs of both data sharing parties. Experimental results show that our scheme can effectively secure data, track the identities of both parties sharing data in real-time, and ensure high data throughput.
Project description:In heterogeneous wireless networks, the industrial Internet of Things (IIoT) is an essential contributor to increasing productivity and effectiveness. However, in various domains, such as industrial wireless scenarios, small cell domains, and vehicular ad hoc networks, an efficient and stable authentication algorithm is required (VANET). Specifically, IoT vehicles deal with vast amounts of data transmitted between VANET entities in different domains in such a large-scale environment. Also, crossing from one territory to another may have the connectivity services down for a while, leading to service interruption because it is pervasive in remote areas and places with multipath obstructions. Hence, it is vulnerable to specific attacks (e.g., replay attacks, modification attacks, man-in-the-middle attacks, and insider attacks), making the system inefficient. Also, high processing data increases the computation and communication cost, leading to an increased workload in the system. Thus, to solve the above issues, we propose an online/offline lightweight authentication scheme for the VANET cross-domain system in IIoT to improve the security and efficiency of the VANET. The proposed scheme utilizes an efficient AES-RSA algorithm to achieve integrity and confidentiality of the message. The offline joining is added to avoid remote network intrusions and the risk of network service interruptions. The proposed work includes two different significant goals to achieve first, then secure message on which the data is transmitted and efficiency in a cryptographic manner. The Burrows Abdi Needham (BAN logic) logic is used to prove that this scheme is mutually authenticated. The system's security has been tested using the well-known AVISPA tool to evaluate and verify its security formally. The results show that the proposed scheme outperforms the ID-CPPA, AAAS, and HCDA schemes by 53%, 55%, and 47% respectively in terms of computation cost, and 65%, 83%, and 40% respectively in terms of communication cost.
Project description:While emerging technology for self-driving automation in vehicles progresses rapidly, the transition to an era of roads full of fully connected and automated vehicles (CAVs) may take longer than expected. Until then, it is inevitable that CAVs should coexist and interact with drivers of non-autonomous vehicles (NAVs) in urban roads. During this period of transition, it is critical to provide road safety with the mixed vehicular traffic and uncertainty caused by human drivers. To investigate the issues caused by the coexistence and interaction with humans, we propose to build a component-based and interactive intelligent transportation cyber-physical systems (ITCPS) framework. Our design of the interactive ITCPS framework aims to provide a standardized structure for users by defining core components. The framework is specified by behavior models and interfaces for the desired ITCPS components and is implemented as a form of human and hardware-in-the-loop system. We developed an intersection crossing assistance service and an automatic emergency braking service as an example of practical applications using the framework. To evaluate the framework, we tested its performance to show how effectively it operates while supporting real-time processing. The results indicate that it satisfies the timing requirements of vehicle-to-vehicle (V2V) communication and the limited processing time required for performing the functions of behavior models, even though the traffic volume reaches the road capacity. A case study using statistical analysis is conducted to assess the practical value of the developed experimental environment. The results of the case study validate the reliability among the specified variables for the experiments involving human drivers. It has shown that V2V communication support has positive effects on road safety, including intersection safety, braking events, and perception-reaction time (PRT) of the drivers. Furthermore, V2V communication support and PRT are identified as the important indicators affecting road safety at an un-signalized intersection. The proposed interactive framework is expected to contribute in constructing a comprehensive environment for the urban ITCPS and providing experimental support for the analysis of human behavior in the coexistence environment.
Project description:BackgroundBlockchain distributed ledger technology is just starting to be adopted in genomics and healthcare applications. Despite its increased prevalence in biomedical research applications, skepticism regarding the practicality of blockchain technology for real-world problems is still strong and there are few implementations beyond proof-of-concept. We focus on benchmarking blockchain strategies applied to distributed methods for sharing records of gene-drug interactions. We expect this type of sharing will expedite personalized medicine.Basic proceduresWe generated gene-drug interaction test datasets using the Clinical Pharmacogenetics Implementation Consortium (CPIC) resource. We developed three blockchain-based methods to share patient records on gene-drug interactions: Query Index, Index Everything, and Dual-Scenario Indexing.Main findingsWe achieved a runtime of about 60 s for importing 4,000 gene-drug interaction records from four sites, and about 0.5 s for a data retrieval query. Our results demonstrated that it is feasible to leverage blockchain as a new platform to share data among institutions.Principal conclusionsWe show the benchmarking results of novel blockchain-based methods for institutions to share patient outcomes related to gene-drug interactions. Our findings support blockchain utilization in healthcare, genomic and biomedical applications. The source code is publicly available at https://github.com/tsungtingkuo/genedrug.
Project description:In the development of web applications, the rapid advancement of Internet technologies has brought unprecedented opportunities and increased the demand for user authentication schemes. Before the emergence of blockchain technology, establishing trust between two unfamiliar entities relied on a trusted third party for identity verification. However, the failure or malicious behavior of such a trusted third party could undermine such authentication schemes (e.g., single points of failure, credential leaks). A secure authorization system is another requirement of user authentication schemes, as users must authorize other entities to act on their behalf in some situations. If the transfer of authentication permissions is not adequately restricted, security risks such as unauthorized transfer of permissions to entities may occur. Some research has proposed blockchain-based decentralized user authentication solutions to address these risks and enhance availability and auditability. However, as we know, most proposed schemes that allow users to transfer authentication permissions to other entities require significant gas consumption when deployed and triggered in smart contracts. To address this issue, we proposed an authentication scheme with transferability solely based on hash functions. By combining one-time passwords with Hashcash, the scheme can limit the number of times permissions can be transferred while ensuring security. Furthermore, due to its reliance solely on hash functions, our proposed authentication scheme has an absolute advantage regarding computational complexity and gas consumption in smart contracts. Additionally, we have deployed smart contracts on the Goerli test network and demonstrated the practicality and efficiency of this authentication scheme.
Project description:Cross-border transactions have been more and more popular around the world. However, the current cross-border transactions still have risks and challenges, e.g., differences in regulation policies and unbalanced profits of banks. To address this critical issue, we construct a new framework for the transaction system with the support of blockchain technology. In this paper, we propose a new consortium blockchain system, namely asymmetric consortium blockchain (ACB), to ensure the implementation of cross-border transactions. Different from traditional consortium blockchain, the new blockchain system could support the supernode to regulate all the transactions timely. Furthermore, the new smart contract is designed to lower the opportunity loss for each node and make the profits allocation system fairer. In the end, the numerical experiments were carried out based on the transactions of Shenzhen and Hong Kong. The results show that the proposed ACB system is efficient to make the profit allocation fairer for the participants and keep intelligent for the new cross-border transaction system.
Project description:Satellite communication has played an important part in many different industries because of its advantages of wide coverage, strong disaster tolerance and high flexibility. The security of satellite communication systems has always been the concern of many scholars. Without authentication, user should not obtain his/her required services. Beyond that, the anonymity also needs to be protected during communications. In this study, we design an efficient and provably secure key agreement scheme for satellite communication systems. In each session, we replace user's true identity by a temporary identity, which will be updated for each session, to guarantee the anonymity. Because the only use of lightweight algorithms, our proposed scheme has high performance. Furthermore, the security of the proposed scheme is proved in the real-or-random model and the performance analysis shows that the proposed scheme is more efficient than some other schemes for satellite communication systems.
Project description:Patient privacy data security is a pivotal area of research within the burgeoning field of smart healthcare. This study proposes an innovative hybrid blockchain-based framework for the secure sharing of electronic medical record (EMR) data. Unlike traditional privacy protection schemes, our approach employs a novel tripartite blockchain architecture that segregates healthcare data across distinct blockchains for patients and healthcare providers while introducing a separate social blockchain to enable privacy-preserving data sharing with authorized external entities. This structure enhances both security and transparency while fostering collaborative efforts across different stakeholders. To address the inherent complexity of managing multiple blockchains, a unique cross-chain signature algorithm is introduced, based on the Boneh-Lynn-Shacham (BLS) signature aggregation technique. This algorithm not only streamlines the signature process across chains but also strengthens system security and optimizes storage efficiency, addressing a key challenge in multi-chain systems. Additionally, our external sharing algorithm resolves the prevalent issue of medical data silos by facilitating better data categorization and enabling selective, secure external sharing through the social blockchain. Security analyses and experimental results demonstrate that the proposed scheme offers superior security, storage optimization, and flexibility compared to existing solutions, making it a robust choice for safeguarding patient data in smart healthcare environments.
Project description:The Internet of Things (IoT) is the most abundant technology in the fields of manufacturing, automation, transportation, robotics, and agriculture, utilizing the IoT's sensors-sensing capability. It plays a vital role in digital transformation and smart revolutions in critical infrastructure environments. However, handling heterogeneous data from different IoT devices is challenging from the perspective of security and privacy issues. The attacker targets the sensor communication between two IoT devices to jeopardize the regular operations of IoT-based critical infrastructure. In this paper, we propose an artificial intelligence (AI) and blockchain-driven secure data dissemination architecture to deal with critical infrastructure security and privacy issues. First, we reduced dimensionality using principal component analysis (PCA) and explainable AI (XAI) approaches. Furthermore, we applied different AI classifiers such as random forest (RF), decision tree (DT), support vector machine (SVM), perceptron, and Gaussian Naive Bayes (GaussianNB) that classify the data, i.e., malicious or non-malicious. Furthermore, we employ an interplanetary file system (IPFS)-driven blockchain network that offers security to the non-malicious data. In addition, to strengthen the security of AI classifiers, we analyze data poisoning attacks on the dataset that manipulate sensitive data and mislead the classifier, resulting in inaccurate results from the classifiers. To overcome this issue, we provide an anomaly detection approach that identifies malicious instances and removes the poisoned data from the dataset. The proposed architecture is evaluated using performance evaluation metrics such as accuracy, precision, recall, F1 score, and receiver operating characteristic curve (ROC curve). The findings show that the RF classifier transcends other AI classifiers in terms of accuracy, i.e., 98.46%.