In this study, we propose a privacy preservation and efficient distributed searching and matching of Electric Vehicles (EVs) charging demander with suppliers based on reputation. Partially homomorphic encryption-based on reputation computation using local communication is used in the implementation, while hiding EVs users' location. A private blockchain is incorporated in the system to verify and permit secure trading of energy among the EVs' demander and suppliers. The results of the simulation show that the proposed privacy preserved algorithm converges more faster as compared to Bichromatic Mutual Nearest Neighbor (BMNN) algorithm.
Jingxin Zhu, Yao Sun, Lei Zhang, Bin Cao · 6 authors
Blockchain-enabled wireless network has been recognized as an emerging network architecture to be widely employed into the Internet of Things (IoT) ecosystems for establishing trust and consensus mechanisms without the involvement of a third party. However, the uncertainty and vulnerability of wireless channels among the IoT nodes may pose a serious challenge to facilitate the deployment of blockchain in wireless networks. In this paper, we first present a generic system model for blockchain enabled wireless networks with multiple communication connections, where the number of communication connections between a client IoT node and the blockchain full nodes can be any arbitrary positive integer to satisfy different security requirements. Based on the proposed spatial-temporal network model, we theoretically calculate the transmission successful probability and the required communication throughput to support a wireless blockchain network. Finally, simulation results validate the accuracy of our theoretical analysis.
The radically increasing amount and enormous types of data generated by vehicles have brought in the innovated application of data trading in the Internet of Vehicles (IoV). However, the trustless environment in IoV enabled data trading faces conflicting interests and disputes of trading parties. To build trust, we exploit consortium blockchain for secure data trading with information transparency. In addition, a hash list of traded data is maintained by roadside units accompanied by bloom filters for fast lookup, to avoid data duplication. The reliability and integrity of trading data are ensured by using the digital signature scheme based on elliptic curve bilinear pairing. For long term availability of traded data, an external distributed storage, i.e., InterPlanetary File System (IPFS) can provide reliable, high capacity storage resources. The experimental results verified that our proposed solution is efficient for data trading in IoV and reliable for long term availability of data storage.
Jingwei Liu, Gaojian Zhang, Rong Sun, Xiaojiang Du · 5 authors
As a typical application scenarios of Internet of Things (IoT), Internet of Vehicles (IoV) is playing an important role in the field of intelligent transportation. In such a system, vehicles are allowed to collect ambient sensing data and communicate with other vehicles, roadside infrastructure, cloud server, even personal mobile smart devices in order to exchange the relevant traffic information that usually includes the owners' sensitive information, such as geographical location or personally identifiable information. However, in open network environment, different wireless communication technologies make all these information vulnerable to various attacks and compromises. The users' private information is put at the risk of leaking at any time. To address this issue, a blockchain-based privacy-preserving traffic data sharing protocol with cloud storage is proposed based on a novel heterogeneous signcryption scheme between Public Key Infrastructure (PKI) and Certificateless Cryptosystem (CLC). Through theoretical and simulation analysis in terms of security, complexity and time consumption, the proposed traffic data sharing protocol is proved to meet the security requirements of data tamper-proofing, anonymity and traceability with higher efficiency.
Mobile crowdsensing (MCS) is an emerging data acquisition technique that combines crowdsourcing with mobile devices to collect massive data in a cost-satisfactory manner. Two notable challenges of MCS are leakage of privacy and the challenge of malicious users, privacy-preserving reputation management scheme is an efficient method to tackle these challenges. However, most existing schemes rely on a semi-honest server and process data in plaintext domain without considering single point of failure and privacy of participants. In this paper we propose a reputation management scheme with blockchain to identify malicious users and protect users’ privacy simultaneously in MCS scenario. The secure and open nature of blockchain are exploited to build a dependable and efficient reputation management platform. Moreover, we adopt a distributed computing algorithm, Eigentrust, to construct a distributed reputation management framework, nevertheless, it neglects to preserve users’ privacy. So we leverage a verifiable secret sharing scheme into Eigentrust algorithm, which can prevent users’ personal information from being disclosed. The extensive analysis and experiments performed on EOS blockchain demonstrate that our system can effectively identify malicious users while preserving privacy.
Secure message dissemination is an important requirement of intelligent transportation systems (ITS). Existing solutions, such as broadcasting, are effective in flooding a message to a wider area, however, they are inherently unreliable and bandwidth inefficient. Furthermore, it is difficult to both assess the authenticity of a message and maintain the privacy of sender in a single solution. Moreover, as a practical solution, there is a need of economic modeling to incentivise vehicles for safe driving and cooperation. This paper proposes a blockchain based message dissemination approach which utilises incentive distribution and reputation management to overcome these challenges. Specifically, with the proposed voting based consensus algorithm, it can assess the authenticity of a message and select the most suitable relay node for its dissemination in a completely decentralised fashion. Meanwhile, the blockchain based integrated incentive and reputation scheme encourages the cooperation among vehicles and strengthens its ability to deliver authentic messages. The security capacity of the proposed solution is demonstrated by a game theoretic analysis. Simulation results show that the proposed approach can save average consensus time by 11% and improve success rate of authentic message dissemination by 17% with less number of hops as compared to the existing solutions.
AI and Blockchain are two disruptive technologies that have the potential to change business models and impact the society. Their integration can lead to Decentralized AI, which enables analysis, decisions and self-learning on trusted and shared data stored on the Blockchain. Autonomous agents in a multi agent environment can collaborate, act and take decisions. Decentralized AI can help improve system performance by processing relevant data, as well as perform parallel processing across nodes based on different objectives. This paper reviews concepts of Blockchain, AI, power of combining these two technologies, and different platforms providing these capabilities.
Abstract Blockchain technology and Internet of Things technology are two new technologies formed in the current transmission of information technology. In the implementation of its technical control, it can scientifically control the information sharing work and realize the artificial adjustment of the transmission control of the Internet of Things technology. In this paper, research on the Internet of Things data sharing model based on block chain with a view to provide guidance to the security of Things data sharing technology under the block chain. In this paper, Hyperledger Fabric block chain platform-based platform, proposed a block-based chain of IOT data sharing model, security and data privacy is an enhancement, obtained by the performance of the test model. Throughput is maximized when the write transaction sending frequency is 100 TPS and the query transaction sending frequency is 250 TPS. The maximum write throughput is 60 TPS, which is better than Bitcoin and Ethereum on the public chain, which proves the feasibility of the model implementation. This model can achieve storage and sharing without the help of a third-party centralized organization, and directly establish trust between participants, which can ensure the safe sharing of data.
Crowdsourcing is a promising computing paradigm that utilizes collective intelligence to solve complex tasks. While it is valuable, traditional crowdsourcing systems lock computation resources inside each individual system where tasks cannot reach numerous potential workers among the other systems. Therefore, there is a great need to build a federated platform for different crowdsourcing systems to share resources. However, the security issue lies in the center of constructing the federated crowdsourcing platform. Although many studies are focusing on privacy-preserving crowdsourcing, existing solutions require a trusted third party to perform the key management, which is not applicable in our federated platform. The reason is that it is difficult for a third party to be trusted by various systems. In this paper, we present a secure crowdsourcing framework as our initial effort toward this direction, which bridges together the recent advancements of blockchain and cryptographic techniques. Our proposed design, named PFcrowd, allows different crowdsourcing systems to perform encrypted task-worker matching over the blockchain platform without involving any third-party authority. The core idea is to utilize the blockchain to assist the federated crowdsourcing by moving the task recommendation algorithm to the trusted smart contract. To avoid third-party involvement, we first leverage the re-writable deterministic hashing (RDH) technique to convert the problem of federated task-worker matching into the secure query authorization. We then devise a secure scheme based on RDH and searchable encryption (SE) to support privacy-preserving task-worker matching via the smart contract. We formally analyze the security of our proposed scheme and implement the system prototype on Ethereum. Extensive evaluations of real-world datasets demonstrate the efficiency of our design.
Muhammad Umar Javed, Abid Jamal, Nadeem Javaid, Noman Haider · 5 authors
Advertisement sharing in vehicular network through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication is a fascinating in-vehicle service for advertisers and the users due to multiple reasons. It enable advertisers to promote their product or services in the region of their interest. Also the users get to receive more relevant ads. Usually, users tend to contribute in dissemination of ads if their privacy is preserved and if some incentive is provided. Recent researches have focused on enabling both of the parameters for the users by developing fair incentive mechanism which preserves privacy by using Zero-Knowledge Proof of Knowledge (ZKPoK) (Ming et al., 2019). However, the anonymity provided by ZKPoK can introduce internal attacker scenarios in the network due to which authenticated users can disseminate fake ads in the network without payment. As the existing scheme uses certificate-less cryptography, due to which malicious users cannot be removed from the network. In order to resolve these challenges, we employed conditional anonymity and introduced Monitoring Authority (MA) in the system. In our proposed scheme, the pseudonyms are assigned to the vehicles while their real identities are stored in Certification Authority (CA) in encrypted form. The pseudonyms are updated after a pre-defined time threshold to prevent behavioural privacy leakage. We performed security and performance analysis to show the efficiency of our proposed system.
With the development of Internet of Things (IoT), the IoT data security issues have raised great attention of academics and industry. However, due to the IoT essential characteristics of decentralization and distribution, traditional centralized architecture suffers from security and scalability challenges. The blockchain technology has been widely applied in industrial domains such as finance and logistics because of its key features of decentralization, data traceability, immutability and auditability which will greatly benefit the IoT system. In this paper, the foundamental of blockchain technology is summerized and the blockchain-based data protection architecture for IoT is proposed. The data transmission, storage and sharing schemes are detailed discussed and evaluated. The result indicates that the implement of blockchain technology will prevent typical attacks and bring benefit to data security of IoT.
The rapid increase in the number of mobile devices across the globe has brought a new challenge to the forefront, one of mobile traffic management. The ever-increasing number of mobile devices leads to the generation of a large amount of data and computationally intensive applications, which contributes heavily to cellular network congestion. To solve this issue, we propose a mobile data offloading scheme based on a distributed ledger technology (DLT). Existing mobile data offloading schemes based on DLT employ conventional blockchain to set up a peer-to-peer (P2P) network of mobile users. Although these schemes have gained ground in improving the Quality of Experience (QoE) for end-users, they lack efficiency and scalability. Furthermore, generic blockchain does not provide timestamp ordering of events, which is necessary to ensure the computation of delay-sensitive tasks. To overcome these challenges, we propose the use of a directed acyclic graph (DAG) data structure for mobile data offloading. Finally, to ensure time and cost optimality, a game-theoretic approach has been proposed in this paper.
Federated learning enables participants to collaborate on model training without directly exchanging raw data. Existing federated learning methods often follow the parameter server architecture, using third-party collaborators to provide aggregation and key management. In this case, the central node obtains information uploaded by other nodes. Studies have shown that with this information, the central node can infer important information, which leads to data privacy leakage. In addition, the failure on the server node can also cause the entire system to fail. We designed a completely decentralized federated learning framework based on blockchain, thereby avoiding the privacy and failure risk of the centralized structure. Moreover, we develop the corresponding model training approach. Compared with the existing methods, our framework performs better in terms of accuracy, robustness, and privacy.
Dynamic Symmetric Searchable Encryption (SSE) is a practical cryptographic primitive that enables data owners to search and update encrypted data hosted on untrusted servers. Recently, there is a growing interest to design dynamic SSE schemes with forward security. That is, the server cannot learn the association between the updated data and any query made in the past. However, due to the complexity of update operations, this security property introduces a great challenge of designing verifiable SSE schemes. It is difficult to verify the correctness of updated search results while preserving forward privacy. In this work, we explore how blockchain techniques can help us achieve a verifiable and dynamic SSE construction with forward security. First, we propose a new dynamic SSE scheme based on blockchain techniques, and apply it as the underlying building blocks to preserve forward-secure updates. Second, we resort to the emerging smart contract technique to customize a verification scheme, making updated results easily verifiable. Based on this new primitive, the robustness of the encrypted search service is ensured and forward security is preserved for update operations. Finally, we implement the prototype in Python and Solidity, and conduct performance evaluations on Ethereum. The extensive security analysis and performance evaluations on the real-world dataset demonstrate that our blockchain-assisted SSE scheme is secure and feasible.
Weikang Liu, Bin Cao, Lei Zhang, Mugen Peng · 5 authors
Keeping patients' sensitive information secured and untampered in the e-Health system is of paramount importance. Emerging as a promising technology to build a secure and reliable distributed ledger, blockchain can protect data from being falsified, which has attracted much attention from both academia and industry. However, with limited computational resources, medical IoT devices do not have efficient ability to fulfill the functionalities as a full node in wireless blockchain network (WBN). Facing this dilemma, Mobile Edge Computing (MEC) brings us dawn and hope through offloading the high resource demanding blockchain functionalities at the IoT devices to the MEC. However, aiming to maximize the mining profit, most of existing offloading strategies have ignored the other needs of wireless devices, e.g., faster transaction writing. In this paper, according to different needs, blockchain nodes are firstly divided into two categories. One is blockchain users whose needs are faster transaction uploading, the other is blockchain miners whose goals are maximum revenue. Then, to maximize both the utilities of blockchain users and blockchain miners, a Stackelberg game is introduced to formulate the interaction between them. From the simulation results, this game is proved to converge to a unique optimal equilibrium.
Abstract: Because of its accessibility and ease of use, cloud storage has become the most widely used type of storage on the market in recent years. However, the privacy and data security of cloud storage are at risk. The protection of data security and privacy is the main topic of this essay. We suggest a blockchain-based decentralised storage system. Since blockchain is a distributed peer-to-peer system, any processing node connected to the internet can join and build peers' networks, maximising resource usage. Blockchain protects data security. The user's file is encrypted and shared among a number of network peers in the proposed system utilising the IPFS (Interplanetary File System) protocol. Hashes are generated by IPFS. The path of the file is indicated by the hash value, which is kept on the blockchain. This project is focused on decentralised secure data storage, high data availability, and effective storage resource usage.
Tianlin Song, Jingqiang Lin, Wei Wang, Quanwei Cai
User registration is the beginning of the life cycle of an account for most information systems. Some registration servers have special requirements for the validity of the registrant's identity and attributes, and thus demand his real-life identity and raw attributes for verification, which poses a great threat to privacy. However, the exposure of the registrant's real-life identity and raw attributes is not necessary, as long as he can prove to the server that he is associated with a real-life identity (RId) that fulfills the requirements. In this paper, we propose the concept of anonymous registration, with which a user can register an anonymous identity (AId) without privacy leakage. Anonymous registration has two basic features, i.e. privacy and verifiability, and two extended features, i.e. traceability and revocability. We design and implement an anonymous registration scheme with the above features, named Traceable Revocable Anonymous Registration Scheme (TRARS) based on Blockchain. In the proposed registration process, the user can calculate a zero-knowledge proof for a self-generated AId, which can prove to the registration server that the AId is associated with a valid RId and the RId's attributes meet the server's requirements, without leaking any privacy. We also introduce an identity revocation coordinator, with which evil identities can be tracked and outdated AIds can be revoked timely.
With the development of precise positioning technology, a growing number of location-based services (LBSs) facilitate people's life. Most LBSs require proof of location (PoL) to prove that the user satisfies the service requirement, which exposes the user's privacy. In this paper, we propose a zero-knowledge proof of location (zk-PoL) protocol to better protect the user's privacy. With the zk-PoL protocol, the user can choose necessary information to expose to the server, so that hierarchical privacy protection can be achieved. The evaluation shows that the zk-PoL has excellent security to resist main attacks, moreover the computational efficiency is independent of input parameters and the zk-PoL is appropriate to delay-tolerant LBSs.
Blockchain was known by Satoshi Nakamoto in 2008 because of Bitcoin. After more than a decade of development, blockchain has been widely used in medical, digital finance, and electronic evidence, etc. Consensus algorithm is the core part of blockchain and has become the bottleneck of blockchain performance. At present, there are dozens of different consensus algorithms for different application context, such as Proof of Work (PoW), Proof of Stake (PoS), Delegate Proof of Stake (DPoS), Proof of Reputation (PoR), etc. But in Public blockchains, their performance, security and stability are difficult to support a large project. This paper introduces an improved consensus algorithm named Delegated Proof of Stake with node's behavior and Borda Count (DPoSB) which based on the node behavior monitoring in DPoS and Borda count voting. The node's behavior of generating blocks is used as a reference index for node elections, and it will increase the difficulty for nodes that have bad behavior. Then, combined with the Borda Count to elect nodes that is more in line with the other nodes' wishes. So, the elected nodes are more secure and fairer, thereby ensuring the stability of the system and the interests of blockchain nodes. Finally, the feasibility and correctness of the consensus algorithm is proved by simulation experiments of the blockchain system.
Ring confidential transaction (RingCT) protocol is widely used in cryptocurrency to protect the privacy of both users’ identities and transaction amounts. Most recently, a new RingCT protocol (called RingCT 2.0) was proposed by leveraging cryptographic accumulators, which can achieve a constant-size output theoretically but still far from being practical due to the heavy zero-knowledge associated with the accumulator. In this article, we revisit the design of ring confidential transaction protocol and put forward a more efficient privacy-preserving payment protocol, which is built upon an extended version of one-out-of-many proof and a special multi-signature. Compared with previous works, the new protocol is not only more practical, but also does not suffer from a trusted setup. Besides, we show that the protocol satisfies the security requirements provided that the underlying cryptographic primitives are secure in the random oracle model. We implement our new payment protocol in Java, and the experimental results show that it is efficient enough to be used in practice.
Internet of Things (IoT) is a promising technology to provide product traceability for industrial systems. By using sensing and networking techniques, an IoT-enabled industrial system enables its participants to efficiently track products and record their status during production process. Current industrial IoT systems lack a unified product data sharing service, which prevents the participants from acquiring trusted traceability of products. Using emerging blockchain technology to build such a service is a promising direction. However, directly storing product data on blockchain incurs in efficiency and privacy issues in data management due to its distributed infrastructure. In response, we propose Cpds, a compressed and private data sharing framework, that provides efficient and private data management for product data stored on the blockchain. Cpds devises two new mechanisms to store compressed and policy-enforced product data on the blockchain. As a result, multiple industrial participants can efficiently share product data with fine-grained access control in a distributed environment without relying on a trusted intermediary. We conduct extensive empirical studies and demonstrate the feasibility of Cpds in improving the efficiency and security protection of product data storage on the blockchain.
Ethereum is the largest public blockchain by usage. It applies an account-based model, which is inferior to Bitcoin's unspent transaction output model from a privacy perspective. Due to its privacy shortcomings, recently several privacy-enhancing overlays have been deployed on Ethereum, such as non-custodial, trustless coin mixers and confidential transactions. In our privacy analysis of Ethereum's account-based model, we describe several patterns that characterize only a limited set of users and successfully apply these quasi-identifiers in address deanonymization tasks. Using Ethereum Name Service identifiers as ground truth information, we quantitatively compare algorithms in recent branch of machine learning, the so-called graph representation learning, as well as time-of-day activity and transaction fee based user profiling techniques. As an application, we rigorously assess the privacy guarantees of the Tornado Cash coin mixer by discovering strong heuristics to link the mixing parties. To the best of our knowledge, we are the first to propose and implement Ethereum user profiling techniques based on quasi-identifiers. Finally, we describe a malicious value-fingerprinting attack, a variant of the Danaan-gift attack, applicable for the confidential transaction overlays on Ethereum. By incorporating user activity statistics from our data set, we estimate the success probability of such an attack.