Blockchain is a technology used with the series of users in peer-to-peer transactions to utilize the usability properties of the immutable data records. The distributed nature of this technology has given the wide acceptance to its range of applications in various sectors. Seeing the prospect of this new technology, we have chosen the field of human resource management as these data needs to be privacy preserving and confidential along with significant research value. Distributed ledger approach is a novel idea in this field of work specifically for the application of human resource records management. We have used a privacy preserving framework that provides a transparent system for human resource record management. Wallets are generated with organization id and outputting with public-private key pair along with privacy parameter mapping with hash. Keys are used to provide confidentiality, integrity and authentication. Smart contract uses distributed but converged decision with privacy level classification. Performance of the proposed work has been measured based on time, memory consumptions, failure point identification and read-write latencies. The analysis of the results confirms the efficiency of the system.
Yiming Liu, F. Richard Yu, Xi Li, Hong Ji · 5 authors
Recently, with the rapid development of information and communication technologies, the infrastructures, resources, end devices, and applications in communications and networking systems are becoming much more complex and heterogeneous. In addition, the large volume of data and massive end devices may bring serious security, privacy, services provisioning, and network management challenges. In order to achieve decentralized, secure, intelligent, and efficient network operation and management, the joint consideration of blockchain and machine learning (ML) may bring significant benefits and have attracted great interests from both academia and industry. On one hand, blockchain can significantly facilitate training data and ML model sharing, decentralized intelligence, security, privacy, and trusted decision-making of ML. On the other hand, ML will have significant impacts on the development of blockchain in communications and networking systems, including energy and resource efficiency, scalability, security, privacy, and intelligent smart contracts. However, some essential open issues and challenges that remain to be addressed before the widespread deployment of the integration of blockchain and ML, including resource management, data processing, scalable operation, and security issues. In this paper, we present a survey on the existing works for blockchain and ML technologies. We identify several important aspects of integrating blockchain and ML, including overview, benefits, and applications. Then we discuss some open issues, challenges, and broader perspectives that need to be addressed to jointly consider blockchain and ML for communications and networking systems.
Blockchain technologies are becoming more popular in securing the sensitive data such as government holding citizens’ s wealth, health and personal information. A blockchain is a shared encrypted data of records, consisting of a ledger of transactions. As the data stored in blockchain is tamper proof, it is proposed to implement new Aadhar enrolments with P2P Blockchains and migrate the existing centralized Aadhar personnel’s personal data from the conventional RDBMS / Big data system repositories to distributed ledger technologies by creating private blockchains. In this paper, we will discuss how to provide security for Aadhar card enrolment data using blockchain architectures. A blockchain-based Aadhaar would help UIDAI in truly complying with the data protection and privacy stipulations outlined in the Right to Privacy Act judgment
A deletable blockchain has been proposed recently to change the immutability of the traditional blockchain. However, the users' identities and transaction contents are all public in the scheme, and the public data may reveal the users' privacy. In order to protect the privacy of the users, we propose a privacy-protected deletable blockchain based on the proof-of-space consensus mechanism, which does not rely on complex cryptographic tools or any trusted party. In order to satisfy full transparency and accountability in an anonymous environment, we use a traceable ring signature or a Pedersen commitment scheme to disclose the users' real identities or the real transaction contents respectively according to different deletion reasons. During the deletion process, we propose a linkable multi-signature scheme, which allows multiple users to generate a valid signature by using their one-time addresses as pseudonyms to protect their identity privacy. Moreover, the proposed multi-signature scheme can link two sub-signatures if they are generated by the same malicious user. Finally, we simulate the generation and deletion process of a block under the proof-of-space consensus mechanism and give the time of generating and deleting a block. The experimental results prove the efficiency and feasibility of our proposed scheme.
Let us consider a situation where someone wants to encrypt his/her will on an existing blockchain, e.g. Bitcoin, and allow an encrypted will to be decryptable only if designated members work together. At a first glance, such a property seems to be easily provided by using conventional threshold encryption. However, this idea cannot be straightforwardly implemented since key pairs for an encryption mechanism is additionally required. In this paper, we propose a new threshold encryption scheme in which key pairs for ECDSA that are already used in the Bitcoin protocol can be directly used as they are. Namely, a unique key pair can be simultaneously used for both ECDSA and our threshold encryption scheme without losing security. Furthermore, we implemented our scheme on the Bitcoin regtest network, and show that it is fairly practical. For example, the execution time of the encryption algorithm Enc (resp., the threshold decryption algorithm Dec) is 0.2sec. (resp., 0.3sec.), and the total time is just only 3sec. including all the cryptographic processes and network communications for a typical parameter setting. Also, we discuss several applications of our threshold encryption scheme in detail: Claiming priority of intellectual property, sealed-bid auction, lottery, and coin tossing service.
Due to enormous increase in development of technology maintenance of user’s information has become major concern. However, user’s information has been effectively maintained by the third parties but the problems with the current system are cost has been increased for maintaining information, lack of transparency and fairness, overuse of power and nature of opaqueness in the current system. So distributed system/ledger i.e., Blockchain came into existence to solve the problems encountered with the current system. The advantages of the proposed distributed system are cost is negligible by eliminating the need of third parties, effectively enhancing the execution speed of transactions and facilitating its reconciliation, maintaining transparency thereby ensuring integrity of user’s information. In this paper, we introduce Ethereum based blockchain network for maintaining user’s information through smart contracts. Experimental results shows that how effectively user’s information has been maintained through blockchain based networks.
Though voting-based consensus algorithms in blockchain outperform proof-based ones in energy- and transaction-efficiency, they are prone to incur wrong elections and bribery elections. The former originates from the uncertainties of candidates’ capability and availability, and the latter comes from the egoism of voters and candidates. Hence, in this paper, we propose an uncertainty- and collusion-proof voting consensus mechanism, including the selection pressure-based voting algorithm and the trustworthiness evaluation algorithm. The first algorithm can decrease the side effects of candidates’ uncertainties, lowering wrong elections while trading off the balance between efficiency and fairness in voting miners. The second algorithm adopts an incentive-compatible scoring rule to evaluate the trustworthiness of voting, motivating voters to report true beliefs on candidates by making egoism consistent with altruism so as to avoid bribery elections. A salient feature of our work is theoretically analyzing the proposed voting consensus mechanism by the large deviation theory. Our analysis provides not only the voting failure rate of a candidate but also its decay speed. The voting failure rate measures the incompetence of any candidate from a personal perspective by voting, based on which the concepts of the effective selection valve and the effective expectation of merit are introduced to help the system designer determine the optimal voting standard and guide a candidate to behave in an optimal way for lowering the voting failure rate.
Riaz Ahmad Ziar, Syed Irfan Ullah, Rafiulllah Omar
The introduction of smart devices and the IOT network has led to the creation of large amounts of data that require protection from intrusion. Most users desire to have personal data kept confidential while seeking for platforms that would prohibit their vendors from distributing it to third parties without their consent. However, the users that are conscious of data privacy often share information with third parties, contradicting their intentions in keeping their information confidential. The difference between user intentions and actions regarding data privacy is called privacy paradox while privacy fatigue refers to the weariness of people on implementing security and privacy solutions. In this proposed system we design and develop smart contracts to provide interaction for the IoT device and company which require personal data. A company or Application requests personal information from the device to share the device sends, that information to the smart contract, smart contract uses dynamic rules to check PII in the users' personal information. Base on the PII(,) system would alert users on the limit and risk of sharing personal information through a public network. We used solidity programing language for the modeled of the smart contract. The performance of the contract is evaluated on the Repsten test network.
Jie Feng, F. Richard Yu, Qingqi Pei, Xiaoli Chu · 6 authors
Mobile-edge computing (MEC) is a promising paradigm to improve the quality of computation experience of mobile devices because it allows mobile devices to offload computing tasks to MEC servers, benefiting from the powerful computing resources of MEC servers. However, the existing computation-offloading works have also some open issues: 1) security and privacy issues; 2) cooperative computation offloading; and 3) dynamic optimization. To address the security and privacy issues, we employ the blockchain technology that ensures the reliability and irreversibility of data in MEC systems. Meanwhile, we jointly design and optimize the performance of blockchain and MEC. In this article, we develop a cooperative computation offloading and resource allocation framework for blockchain-enabled MEC systems. In the framework, we design a multiobjective function to maximize the computation rate of MEC systems and the transaction throughput of blockchain systems by jointly optimizing offloading decision, power allocation, block size, and block interval. Due to the dynamic characteristics of the wireless fading channel and the processing queues at MEC servers, the joint optimization is formulated as a Markov decision process (MDP). To tackle the dynamics and complexity of the blockchain-enabled MEC system, we develop an asynchronous advantage actor–critic-based cooperation computation offloading and resource allocation algorithm to solve the MDP problem. In the algorithm, deep neural networks are optimized by utilizing asynchronous gradient descent and eliminating the correlation of data. The simulation results show that the proposed algorithm converges fast and achieves significant performance improvements over existing schemes in terms of total reward.
The vehicular ad hoc network (VANET) is an intelligent transportation system application that aims to ensure the security of road traffic information over V2V communication and V2I communication. In this paper, we propose a blockchain-based privacy-preserving authentication scheme in VANETs. We explore the strategy of a local blockchain for VANETs. We make use of a private blockchain for authentication and a public blockchain for managing event messages. The trusted authority (TA) is responsible for making the transactions in the private blockchain within the boundary of the countries, the transactions are the identity information required for authentication of vehicles when they join the network for the first time, the other vehicles have the right to read and check from the private blockchain the authenticity of a new vehicle. The public blockchain is used for storing the event messages within the boundary of pre-defined regions to ensure the security of message dissemination, we called this kind of blockchain road-side unit blockchain (RSU-BC) because it takes the role of RSU in a VANET. In this way, we eliminate the necessity of RSU's deployment in VANETs and reduce the dependency on the TA. By way of security analysis and security-proofing, we prove that our scheme satisfies multiple security and privacy requirements and can resist many attacks, while the performance analysis shows the efficiency of the scheme in terms of computation overheads and communication overheads.
Nathaniel Aldred, Luke Baal, Graeham Broda, Steven Trumble · 5 authors
A blockchain is a distributed ledger forming a distributed consensus on a\nhistory of transactions. It is the underlying technology for the Bitcoin\ncryptocurrency, but there are many applications beyond the financial sector.\nWith built-in security and removal of the need for third party trust,\nblockchain has started to see some use within contract applications among other\nthings. In this paper, we present the design and implementation of a\npermissioned-based blockchain third party consent management system, whose\npolicy can be decided by a government agency. We have constructed a proof of\nconcept implementation using Hyperledger Fabric to provide a service that\nallows end-users to control and consent to who manages their private\ninformation. We believe our solution meets the guiding principles of EU General\nData Protection Regulation or GDPR. While our performance and usability\nevaluation are limited, our solution design and its implementation meet the 7\nfoundational principles of privacy by design.\n
Zhaofeng Ma, Lingyun Wang, Wang Xiaochang, Zhen Wang · 5 authors
With the fast development of Internet-of-Things (IoT) technologies, IoT big data and its applications are getting more and more useful. However, traditional IoT data management is fragile and vulnerable. Once the gathered data are untrusted or the stored data are tampered with deliberately from the internal users or attacked by an external hacker, then the tampered data have a serious problem to be utilized. To solve the problems of trust and security of IoT big data management, in this article, we propose a permissioned blockchain-based decentralized trust management and secure usage control scheme of IoT big data (called BlockBDM), upon which all the data operations and management, such as data gathering, invoking, transfer, storage, and usage, are processed over the blockchain smart contract. To encourage the IoT client to supply high-quality content, in our scheme, we design public-blockchain-based tokens reward mechanism for the high-quality data supply contribution. All the data processing and usage procedure can be recorded in a cryptography-signed and Merkle tree-based transaction(s) and block(s) with high-level security in a global and distributed ledger with tamper resistance. For data utilization and consumption, we propose secure usage control for digital rights management and token-based data consumption approach of high-value data from being violated or spread without any limitation. We implemented the BlockBDM scheme based on public and permissioned blockchain for IoT big data management. Finally, a large amount of evaluation manifests that the proposed BlockBDM scheme is feasible, secure, and scalable for decentralized trust management of IoT big data.
Proof of retrievability is a cryptographic tool which interacts between the data user and the server, and the server proves to the data user the integrity of data which he will download. It is a crucial problem in outsourcing storage such as cloud computing. In this paper, a novel scheme called the zero knowledge proof of retrievability is proposed, which combines proof of retrievability and zero knowledge proof. It has lower computation and communication complexity and higher security than the previous schemes.
We consider a public blockchain realized in the mobile edge computing (MEC) network, where the blockchain miners compete against each other to solve the proof-of-work puzzle and win a mining reward. Due to limited computing capabilities of their mobile terminals, miners offload computations to the MEC servers. The MEC servers are maintained by the service provider (SP) that sells its computing resources to the miners. The SP aims at maximizing its long-term profit subject to miners' budget constraints. The miners decide on their hash rates, i.e., computing powers, simultaneously and independently, to maximize their payoffs without revealing their decisions to other miners. As such, the interactions between the SP and miners are modeled as a stochastic Stackelberg game under private information, where the SP assigns the price per unit hash rate, and miners select their actions, i.e., hash rate decisions, without observing actions of other miners. We develop a hierarchical learning framework for this game based on fully- and partially-observable Markov decision models of the decision processes of the SP and miners. We show that the proposed learning algorithms converge to stable states in which miners' actions are the best responses to the optimal price assigned by the SP.
In fifth-generation (5G) networks and beyond, communication latency and network bandwidth will be no longer be bottlenecks to mobile users. Thus, almost every mobile device can participate in distributed learning. That is, the availability issue of distributed learning can be eliminated. However, model safety will become a challenge. This is because the distributed learning system is prone to suffering from byzantine attacks during the stages of updating model parameters and aggregating gradients among multiple learning participants. Therefore, to provide the byzantine-resilience for distributed learning in the 5G era, this article proposes a secure computing framework based on the sharding technique of blockchain, namely PiRATE. To prove the feasibility of the proposed PiRATE, we implemented a prototype. A case study shows how the proposed PiRATE contributes to distributed learning. Finally, we also envision some open issues and challenges based on the proposed byzantine- resilient learning framework.
This paper proposes SilentDelivery, a secure, scalable and cost-efficient protocol for implementing timed information delivery service in a decentralized blockchain network. SilentDelivery employs a novel combination of threshold secret sharing and decentralized smart contracts. The protocol maintains shares of the decryption key of the private information of an information sender using a group of mailmen recruited in a blockchain network before the specified future time-frame and restores the information to the information recipient at the required time-frame. To tackle the key challenges that limit the security and scalability of the protocol, SilentDelivery incorporates two novel countermeasure strategies. The first strategy, namely silent recruitment, enables a mailman to get recruited by a sender silently without the knowledge of any third party. The second strategy, namely dual-mode execution, makes the protocol run in a lightweight mode by default, where the cost of running smart contracts is significantly reduced. We rigorously analyze the security of SilentDelivery and implement the protocol over the Ethereum official test network. The results demonstrate that SilentDelivery is more secure and scalable compared to the state of the art and reduces the cost of running smart contracts by 85%.
Abstract Background With the advent of precision medicine, pharmacogenomics data is becoming increasingly critical to patient care. These data describe the relationship between a particular variant in the genome and the response to a drug by the patient. As utilizing this kind of data becomes more integral to medical treatment decisions, appropriate storage and sharing of this data will be critical. A potential way of securely storing and sharing pharmacogenomics data is a smart contract with the Ethereum blockchain. This is an open-source blockchain platform for decentralized applications. A transaction-based, state machine, the “world” of Ethereum maintains user accounts and storage in a network state. Immutable pieces of code called “smart contracts” may be deployed to the Ethereum network and run on the Ethereum Virtual Machine when called by a user or other contract. The 2019 iDASH (Integrating Data for Analysis, Anonymization, and Sharing) competition for Secure Genome Analysis challenged participants to develop time- and space-efficient smart contracts to log and query gene-drug relationship data on the Ethereum blockchain. Methods We designed a smart contract to store and query pharmacogenomics data (gene-drug interaction data) in Ethereum using an index-based, multi-mapping approach allowing for time and space efficient storage and query. Our solution to the IDASH competition ranked in the top three at a workshop held in Bloomington, IN in October 2019. Although our solution performed well in the challenge, we wanted to improve its scalability and query efficiency. To that end, we developed an alternate “fastQuery” solution that stores pooled rather than raw data, allowing for significantly improved query time for 0-AND queries, and constant query time for 1- and 2-AND queries. Results We tested the performance of both of our solutions in Truffle (v5.0.31) using datasets ranging from 100 to 1000 entries, and inserting data at 25, 50, 100, and 200 observations at a time. On a private, proof-of-authority test network, our challenge solution requires approximately 70 seconds, 500 MB of memory, and 80 MB of disk space to insert 1000 entries (200 at a time); and 400 ms and 5 MB of memory to query a two-AND query from 1000 entries. This solution exhibits constant memory for insertion and querying, and linear query time. Our alternate fastQuery solution requires approximately 60 seconds, 500 MB of memory, and 80 MB of disk space to insert 1000 entries (200 at a time); and 83 ms and 5 MB of memory to query a two-AND query from 1000 entries. This solution exhibits constant memory for insertion and querying, linear query time for 0-AND queries, and constant query time for 1- and 2-AND queries in a database of up to 1000 entries. Conclusion In this study we showed that pharmacogenomics data can be stored and queried efficiently on the Ethereum blockchain. Our approach has the potential to be useful for a wide range of datasets in biomedical research; while we focused on gene-drug interaction data, our solution designs could be used to store a range of clinical trial data. Moreover, our solutions could be adapted to store and query data in any field where high-integrity data storage and efficient access is required.
Benjamin S. Glicksberg, Shohei Burns, Robert Currie, A. Clark Griffin · 8 authors
BACKGROUND: Efficiently sharing health data produced during standard care could dramatically accelerate progress in cancer treatments, but various barriers make this difficult. Not sharing these data to ensure patient privacy is at the cost of little to no learning from real-world data produced during cancer care. Furthermore, recent research has demonstrated a willingness of patients with cancer to share their treatment experiences to fuel research, despite potential risks to privacy. OBJECTIVE: The objective of this study was to design, pilot, and release a decentralized, scalable, efficient, economical, and secure strategy for the dissemination of deidentified clinical and genomic data with a focus on late-stage cancer. METHODS: We created and piloted a blockchain-authenticated system to enable secure sharing of deidentified patient data derived from standard of care imaging, genomic testing, and electronic health records (EHRs), called the Cancer Gene Trust (CGT). We prospectively consented and collected data for a pilot cohort (N=18), which we uploaded to the CGT. EHR data were extracted from both a hospital cancer registry and a common data model (CDM) format to identify optimal data extraction and dissemination practices. Specifically, we scored and compared the level of completeness between two EHR data extraction formats against the gold standard source documentation for patients with available data (n=17). RESULTS: Although the total completeness scores were greater for the registry reports than those for the CDM, this difference was not statistically significant. We did find that some specific data fields, such as histology site, were better captured using the registry reports, which can be used to improve the continually adapting CDM. In terms of the overall pilot study, we found that CGT enables rapid integration of real-world data of patients with cancer in a more clinically useful time frame. We also developed an open-source Web application to allow users to seamlessly search, browse, explore, and download CGT data. CONCLUSIONS: Our pilot demonstrates the willingness of patients with cancer to participate in data sharing and how blockchain-enabled structures can maintain relationships between individual data elements while preserving patient privacy, empowering findings by third-party researchers and clinicians. We demonstrate the feasibility of CGT as a framework to share health data trapped in silos to further cancer research. Further studies to optimize data representation, stream, and integrity are required.
Credential fraud is a widespread practice that undermines investment and confidence in higher education systems and bears significant economic and social costs. Legacy credential verification systems are typically time-consuming, costly, and bureaucratic, and struggle against certain classes of credential fraud. In this paper, we propose a comprehensive blockchain-based credential verification solution, Cerberus, which is considerably more efficient, easy and intuitive to use, and effectively mitigates widespread manifestations of credential fraud. Cerberus also improves significantly upon other blockchain-based solutions in the research literature: it adheres closely to the existing credential verification ecosystem, it addresses a threat model informed by real-world fraud scenarios. Moreover, Cerberus uses on-chain smart contracts for credential revocation, and it does not entail students or employers to manage digital identities or cryptographic credentials to use the system. We prototype our solution and describe our attempt to design an online verification service with a rich feature set, including data privacy, transcript verification, and selective disclosure of data. We hope this effort contributes positively to towards alleviating the problem of fake credentials.
As the integration of the Internet of Vehicles and social networks, vehicular social networks (VSN) not only improves the efficiency and reliability of vehicular communication environment, but also provide more comprehensive social services for users. However, with the emergence of advanced communication and computing technologies, more and more data can be fast and conveniently collected from heterogeneous devices, and VSN has to meet new security challenges such as data security and privacy protection. Searchable encryption (SE) as a promising cryptographic primitive is devoted to data confidentiality without sacrificing data searchability. However, most existing schemes are vulnerable to the adaptive leakage-exploiting attacks or can not meet the efficiency requirements of practical applications, especially the searchable public-key encryption schemes (SPE). To achieve secure and efficient keyword search in VSN, we design a new blockchain-based searchable public-key encryption scheme with forward and backward privacy (BSPEFB). BSPEFB is a decentralized searchable public-key encryption scheme since the central search cloud server is replaced by the smart contract. Meanwhile, BSPEFB supports forward and backward privacy to achieve privacy protection. Finally, we implement a prototype of our basic construction and demonstrate the practicability of the proposed scheme in applications.