Blockchain is a technology that provides security features that can be used for more than just cryptocurrencies. Blockchain achieves security by saving the information of one block in the next block. Changing the information of one block will require changes to all the next block in order for that change to take effect. Which makes it unfeasible for such an attack to happen. However, the structure of how blockchain works makes the last block always vulnerable for attacks, given that its information is not saved yet in any block. This allows malicious node to change the information of the last block and generate a new block and broadcast it to the network. Given that the nodes always follow the longer chain wins rule, the malicious node will win given that it has the longest chain in the network. This paper suggests a solution to this issue by making the nodes send consistency check messages before broadcasting a block. If the nodes manage to successfully verify that the node that generated a new block hasn’t tampered with the blockchain than that block will be broadcasted. The results of the simulation show suggested protocol provided better security compared to the regular blockchain.
As the next‐generation power grid system, the smart grid can realize the balance of supply and demand and help in communication security and privacy protection. However, real‐time power consumption data collection might expose the users’ privacy information, such as their living habits and economic conditions. In addition, during the process of data transmission, it may lead to data inconsistency between the user side and the storage side. Blockchain provides tamper‐resistant and traceable characteristics for solving these problems, and ring signature schemes provide an anonymous authentication mechanism. Therefore, in this work, we consider the applications of ring signature scheme in smart grid based on blockchain. We introduce the notion of multi‐authority traceable ring signature (MA‐TRS) scheme for distributed setting. In our scheme, there is an auditing node that can distinguish the identity of the real signer from the ring without any secret information. Last but not least, we prove that the proposed scheme is unforgeable, anonymous, and traceable.
Internet of Things (IoT) aims to simplify the collection of the distributed data in a global manufacturing business, sharing and processing of information and knowledge across many collaborating partners using appropriate information system architecture. As with the IoT, convergence with blockchain technology that processes data, privacy and security-related issues, and data policies (e.g., regulatory compliance) may apply to data and software artefacts. Besides, blockchain technology could contribute to the more intelligent and flexible handling of transactional data through appropriate convergence with IoT technology in supporting data integration and processing. This paper examines this hybrid architecture’s privacy, security, and policy-related issues to appreciate the convergence and understand the integration of IoT and blockchain technology. This paper primarily identifies common trends focusing on relevant topics in blockchain-based IoT technology research and by highlighting the need to explore security issues further – for example, data privacy challenges in the manufacturing industry.
The right to privacy is the most fundamental right of a citizen in any country. Electronic Health Records (EHRs) in healthcare has faced problems with privacy breaches, insider outsider attacks and unauthenticated record access in recent years, the most serious being related to the privacy and security of medical data. Ensuring privacy and security while handling patient data is of the utmost importance as a patient’s information should only be released to others with the patient’s permission or if it is allowed by law. Electronic health data (EHD) is an emerging health information exchange model that enables healthcare providers and patients to efficiently store and share their private healthcare information from any place and at any time as required. Generally, cloud services provide the infrastructure by reducing the cost of storing, processing and updating information with improved efficiency and quality. However, the privacy of EHRs is a significant hurdle when outsourcing private health data in the cloud because there is a higher risk of health information being leaked to unauthorized parties. Several existing techniques can analyse the security and privacy issues associated with e-healthcare services. These methods are designed for single databases, or databases with an authentication centre and thus cannot adequately protect the data from insider attacks. In fact, storing EHRs on centralized databases increases the security risk footprint and requires trust in a single authority. Therefore, this research study mainly focuses on how to ensure patient privacy and security while sharing sensitive data between the same or different organisations as well as healthcare providers in a distributed environment. This research successfully proposes and implements a permissioned blockchain framework named Healthchain, which maintains the security, privacy, scalability and integrity of the e-health data. The blockchain is built on Hyperledger Fabric, a permissioned distributed ledger solution by employing Hyperledger Composer and stores EHRs by utilizing InterPlanetary File System (IPFS) to build the decentralized web applications. Healthchain builds a two-pronged solution (i) an on-chain solution implemented on the secure network of Hyperledger Fabric which utilizes the state database Couch DB, (ii) an off-chain solution to securely store encrypted data via IPFS. The Healthchain architecture employs Practical Byzantine Fault Tolerance (PBFT) as the distributed network consensus processes to determine which block is to be added to the blockchain. Healthchain Hyperledger Fabric leverages container technology to host smart contracts called “chaincode” that comprises the application logic of this system. This research aimed at contributing towards the scalability in blockchain by storing the data hashes of health records on chain and the actual data is stored cryptographically off chain in IPFS, the decentralized storage. Moreover, the data stored in the IPFS will be encrypted by using special public key cryptographic algorithms to create robust blockchain solutions for EHD. This research study develops a privacy preserving framework with three main core contributions to the e-Health ecosystem: (i) it contributes a privacy preserving patient-centric framework namely Healthchain; (ii) introduces an efficient referral mechanism for the effective sharing of healthcare records; and (iii) prevents prescription drug abuse by performing drug tracking transactions employing smart contract functionality to create a smart health care ecosystem. The results demonstrates that the developed prototype ensures that healthcare records are not traceable to illegal disclosure as the model only stores the encrypted hash of records and is proven to be effective in terms of enhanced data privacy, data security, improved data scalability, interoperability and data integrity when accessing and sharing medical records among stakeholders across the Healthchain network. This research develops a foolproof security solution against cyber-attacks by exploiting the inherent features of the blockchain, thereby contributing to the robustness of healthcare information sharing systems and also unravels the potential for blockchain in health IT solutions.
Amit Kumar Tyagi, S Aswathy, G. Aghila, N. Sreenath
The enhancement (in the past decade) in electronics devices/technology, a rise in most of the accidents concerning security and surveillance intruding the private lives of the users question the existing systems being used to combat this challenge wherein, the third-parties gather and handle large amounts of individual details. As part of the constant evolution of the cyber physical system architecture, one of the goals of our system is to reduce the latency time for enrollment of new information. Generally, the efficiency and benefit of a Cyber Physical Systems (CPS) depends heavily on interconnection of individual devices or nodes. Exchange of data and information relevant to an overall task or functionality is the key to many applications such as smart grids, smart cities, and many others. Trustworthiness of data is needed to make such systems (especially in MCPS systems) successful. To be able to fulfill policies to guarantee the safety of all entities within a Medical Cyber Physical Systems (MCPS) and to provide security measures to enforce these cryptographic solutions have to be embedded. This paper describes a decentralized e-healthcare application framework for personal data management that ensures that users own and access their data. This work proposes a novel mechanism to secure Medical Cyber Physical Systems (MCPS), i.e., as an automated access-control manager (including building trust in a third party). This work also integrates some features in security building blocks in ultra-small devices to provide essential properties to secure embedded systems.
Access Control is mentioned to as the imprisonment of particular activities of an individual to carry out an action. Cloud storing similar to any other untrusted surroundings wants the capacity to protect the shared data. The one of the apparatus of access mechanism is ciphertext-policy attribute-based encryption system over and done with dynamic characteristics. With a blockchain based distributed ledger, the scheme offers immutable log of whole significant safety events, for example key generation, change or revocation, access policy assignment, access request etc. Number of different problems similar to single point of failure, security and privacy etc. were targeted through the appropriate primary studies. The Meta analysis suggests the usage of diverse blockchain platforms, different application areas and different used blockchain properties. The services consist of authentication, privacy, confidentiality, data, access control list and, integrity assurance and resource provenance. Altogether these facilities are dangerous for the present distributed applications, particularly in line for to the huge quantity of information being processed over the webs and also the usage of cloud computing. Verification confirms that the client is who he/she professes to be. Confidentiality assures that the information cannot be read through unapproved users. Privacy gives to the clients the capacity to control who can get to their information. Provenance permits an effective tracing of the information also resources alongside using their ownership as well as utilization on the network. Integrity assists in authenticating that the information has not been changed or else altered. These services stand now managed through central controllers. On the other side, blockchain is a protected plus distributed ledger that can assist to resolve the issue of access control in cloud. We present a systematic analysis of blockchain driven access control systems. The current paper examines previous studies in the region of Access Control in Cloud, by a comprehensive Bibliometric study. The analysis is completed by using the Scopus databases also tools similar to Imap builder, VOSviewer and Word cloud. As of the database of Scopus, it is detected that the publications taking place Access Control in Cloud are 993 is Articles and 31 is a Review articles. The significant of research is limited but an increasing tendency is detected on or after the year 2013. The review shown that the maximum publications of Access Control in Cloud are journals articles and Conference Papers. Chinese top publications followed by the India and United States. The paper determines that the study area is recent also more research is obligatory in the domain Access Control in Cloud using Blockchain.
B. Sowmiya, E. Poovammal, Kadiyala Ramana, Saurabh Singh · 5 authors
Cloud computing is a continuously evolving technology that can enhance agility, availability, collaboration and scalability of data. Blockchain has a secure, immutable ledger which maintains all the transactions along with the timestamp. The blockchain framework and cloud computing technology jointly provides different ways of computational cost reduction. The existing methods help to identify the anonymous documents which are given in the form of requests from the cloud server. If the anonymized document requests are from the authorized users, then cloud provides better security and hence documents are not available for unauthorized users. But the main issue is access rights available for authorized users on sensitive data of the owner. To maintain the privacy the sensitive data are hidden using cryptographic techniques even for authorized users. The method adopted is Linear Elliptical Curve Digital Signature (LECDS) with Hyperledger blockchain, to prevent private data loss. The Linear regression method is used to classify the user information into two classes namely sensitive and non-sensitive. The non-sensitive data is encrypted using RSA and sensitive data is encrypted using LECC method. Modified Spider optimization search Algorithm (MSOA) is used to verify the integrity of outsourced data and search user query information in a cloud server. The hyper ledger blockchain verifies the user policy to create a private network through which the user communicates the cloud. In the analysis of the proposed method, the results are evaluated using various performance metrics such as security, throughput, classification accuracy and error rate.
Open access
Blockchain Technology Applications and Security
Cloud Data Security Solutions
Advanced Steganography and Watermarking Techniques
The classic Elliptic curve digital Signature Algorithm (ECDSA) uses one inversion operation in the process of signature and verification, which greatly reduces the efficiency of digital signatures. Up to now, most research schemes improve efficiency by reducing reverse operations, but they fail to attach importance to such issues as forgery signature attack. At the same time, in the blockchain, the weak randomness of ECDSA will lead to the attack of forging random numbers, which is a potential problem of digital currency transactions. In consideration of this reason, in this article, an improved provably secure elliptic curve digital signature scheme is constructed. First, the new scheme introduces double parameters in the signature process, that can effectively resist the weak randomness attack of ECDSA in Bitcoin, and can be applied to blockchain digital currency trading systems. Second, in the random oracle model, it is provably indistinguishable against Elliptic Curve Discrete Logarithm Problem (ECDLP) under the super type I and type II adversary. Third, the new scheme avoids the inverse operation in the signature and verification phase. Compared with the ECDSA, the running speed is optimized by 50.1%. Similarly, the proposed scheme has higher computational efficiency than other existing algorithms.
Ifeoluwa Oreofe Oluwafemi, T. Prabhakar Clement, Oluwasanmi Segun Adanigbo, Toluwase Peter Gbenle · 5 authors
The global pharmaceutical industry faces growing threats from counterfeit and substandard drugs, undermining public health, regulatory compliance, and supply chain trust. To address these challenges, this paper evaluates the efficacy of DIDChain-enabled blockchain frameworks, which integrate Decentralized Identifiers (DIDs) with distributed ledger technology to establish real-time provenance verification and anti-counterfeit control. Drawing on a comprehensive body of literature, including conceptual frameworks in digital transformation, cybersecurity, business intelligence, and cloud-based analytics, the study explores how DIDChain infrastructure can enhance transparency, immutability, and interoperability in pharmaceutical logistics. The analysis incorporates findings from prior research on AI-driven fraud detection, supply chain resilience, and data governance models, particularly those applied in the financial, energy, and SME sectors. The evaluation highlights the role of DIDChain in supporting secure product authentication, automated compliance auditing, and cross-border regulatory coordination. This research contributes to emerging discourse on digital trust technologies, offering a scalable and interoperable solution for ensuring drug integrity in complex and globalized pharmaceutical ecosystems.
Hyper-connectivity in Industry 4.0 has resulted in not only a rapid increase in the amount of information, but also the expansion of areas and assets to be protected. In terms of information security, it has led to an enormous economic cost due to the various and numerous security solutions used in protecting the increased assets. Also, it has caused difficulties in managing those issues due to reasons such as mutual interference, countless security events and logs’ data, etc. Within this security environment, an organization should identify and classify assets based on the value of data and their security perspective, and then apply appropriate protection measures according to the assets’ security classification for effective security management. But there are still difficulties stemming from the need to manage numerous security solutions in order to protect the classified assets. In this paper, we propose an information classification management service based on blockchain, which presents and uses a model of the value of data and the security perspective. It records transactions of classifying assets and managing assets by each class in a distributed ledger of blockchain. The proposed service reduces assets to be protected and security solutions to be applied, and provides security measures at the platform level rather than individual security solutions, by using blockchain. In the rapidly changing security environment of Industry 4.0, this proposed service enables economic security, provides a new integrated security platform, and demonstrates service value.
Transformation of BPMN business process model will be a very important topic in the future of the Hyperledger Fabric blockchain environment. Machine transformation can increase the quality of transformation and thus reduce errors. The research paper first describes BPMN and the Hyperledger Fabric environment, what smart contracts are and why they are so important. In the second part, the raw transformation model is described, where the inputs for the transformations are BPMN and the metadata file, and the result is a smart contract written in Java that can be imported into the Hyperledger Fabric environment.
Cloud computing has now become a very standardised concept in our society. However, many modern applications need a better level of security that includes saving data from internal breaches. Thus, cloud databases need effective security mechanisms to keep track of data modifications. This paper will introduce the enhanced structure of cloud relational database (RDB) based on blockchain technology (BC) named BC over cloud-RDB. To provide the client with an effective self-verification process to detect and prevent erroneous manipulation of RDBs. We proposed two systems to improve cloud-RDB: agile BC-based RDB and secure BC-based RDB. Both are distributed among several cloud service providers based on the Byzantine Fault Tolerance consensus. Additionally, both rely on linking records to each other using the SHA-256. At the same time, secure BC-based RDB uses a proof-of-work consensus to make data offensive operation impossible. Based on both systems’ performance and security analysis, the agile BC-based RDB is highly suggested for the high throughput database. On the other hand, the secure BC-based RDB is recommended for RDB that contains sensitive data and low throughput performance. The improved RDB is flexible and can be operated based on the data owner’s specifications.
Oyinomomo-emi Emmanuel Akpe, Denis Kisina, Samuel Owoade, Abel Chukwuemeke Uzoka · 6 authors
The increasing complexity of digital platforms, driven by cloud-native architectures, distributed applications, and user-centric services, necessitates robust, scalable, and secure identity management frameworks. This paper explores recent advances in federated authentication and identity management, emphasizing their role in enabling seamless and secure access across interconnected digital ecosystems. Beginning with a foundational overview of identity management’s evolution—from traditional siloed systems to federated and decentralized models—the study outlines key technologies such as SAML, OAuth, OpenID Connect, and emerging paradigms like decentralized identity and blockchain-based verification. It further investigates the integration of artificial intelligence and machine learning for adaptive authentication, anomaly detection, and risk-based decision-making, alongside privacy-enhancing technologies ensuring compliance with data protection regulations such as GDPR. Through the examination of scalability, interoperability, and security challenges, the paper identifies best practices and architectural strategies critical for real-world implementations. The discussion culminates in practical implications for industry adoption across sectors such as healthcare, finance, and e-commerce, and highlights future research directions including the development of standardized identity frameworks, AI integration, and decentralized identity systems in multi-cloud and edge computing environments. This study offers a comprehensive synthesis of current trends and technologies that are shaping the next generation of identity management in scalable digital platforms.
Trust is the main barrier preventing widespread data sharing. The lack of transparent infrastructures for implementing data trust prevents many data owners from sharing their data and concerns data users regarding the quality of the shared data. Data trust is a paradigm that facilitates data sharing by forcing data users to be transparent about the process of sharing and reusing data. Blockchain technology proposes a distributed and transparent administration by employing multiple parties to maintain consensus on an immutable ledger. This paper presents an end-to-end framework for data trust to enhance trustworthy data sharing utilizing blockchain technology. The framework promotes data quality by assessing input data sets, effectively manages access control, and presents data provenance and activity monitoring. We introduce an assessment model that includes reputation, endorsement, and confidence factors to evaluate data quality. We also suggest an adaptive solution to determine the number of transaction validators based on the computed trust value. The proposed data trust framework addresses both data owners' and data users' concerns by ensuring the trustworthiness and quality of the data at origin and ethical and secure usage of the data at the end. A comprehensive experimental study indicates the presented system effectively handles a large number of transactions with low latency.
Yihan Liu, Ke Li, Zihao Huang, Bowen Li · 6 authors
The predominant centralized paradigm in educational data management currently suffers from several critical issues such as vulnerability to malicious tampering, a high prevalence of diploma counterfeiting, and the onerous cost of certificate authentication. Decentralized blockchain technology, with its cutting-edge capabilities, presents a viable solution to these pervasive problems. In this paper, we illuminate the inherent limitations of existing centralized systems and introduce EduChain, a novel heterogeneous blockchain-based system for managing educational data. EduChain uniquely harnesses the strengths of both private and consortium blockchains, offering an unprecedented level of security and efficiency. In addition, we propose a robust mechanism for performing database consistency checks and error tracing. This is achieved through the implementation of a secondary consensus, employing the pt-table-checksum tool. This approach effectively addresses the prevalent issue of database mismatches. Our system demonstrates superior performance in key areas such as information verification, error traceback, and data security, thereby significantly improving the integrity and trustworthiness of educational data management. Through EduChain, we offer a powerful solution for future advancements in secure and efficient educational data management.
Benjamin Körbel, Marten Sigwart, Philip Frauenthaler, Michael Sober · 5 authors
Offloading of computation, e.g., to the cloud, is today a major task in distributed systems. Usually, consumers which apply offloading have to trust that a particular functionality offered by a service provider is delivering correct results. While redundancy (i.e., offloading a task to more than one service provider) or (partial) reprocessing help to identify correct results, they also lead to significantly higher cost. Hence, within this paper, we present an approach to verify the results of offchain computations via the blockchain. For this, we apply zero-knowledge proofs to provide evidence that results are correct. Using our approach, it is possible to establish trust between a service consumer and arbitrary service providers. We evaluate our approach using a very well-known example task, i.e., the Traveling Salesman Problem.
Lorenzo Andolfo, Luigi Coppolino, Salvatore D’Antonio, Giovanni Mazzeo · 8 authors
The majority of financial organizations managing confidential data are aware of security threats and leverage widely accepted solutions (e.g., storage encryption, transport-level encryption, intrusion detection systems) to prevent or detect attacks. Yet these hardening measures do little to face even worse threats posed on data-in-use. Solutions such as Homomorphic Encryption (HE) and hardware-assisted Trusted Execution Environment (TEE) are nowadays among the preferred approaches for mitigating this type of threat. However, given the high-performance overhead of HE, financial institutions -- whose processing rate requirements are stringent -- are more oriented towards TEE-based solutions. The X-Margin Inc. company, for example, offers secure financial computations by combining the Intel SGX TEE technology and HE-based Zero-Knowledge Proofs, which shield customers' data-in-use even against malicious insiders, i.e., users having privileged access to the system. Despite such a solution offers strong security guarantees, it is constrained by having to trust Intel and by the SGX hardware extension availability. In this paper, we evaluate a new frontier for X-Margin, i.e., performing privacy-preserving credit risk scoring via an emerging cryptographic scheme: Functional Encryption (FE), which allows a user to only learn a function of the encrypted data. We describe how the X-Margin application can benefit from this innovative approach and -- most importantly -- evaluate its performance impact.