Dezhi Han, Yujie Zhu, Dun Li, Wei Liang · 6 authors
Internet of Things (IoT) devices are widely considered in smart cities, intelligent medicine, and intelligent transportation, among other fields that facilitate people's lives, producing a large amount of private data. However, due to the mobility, limited performance, and distributed deployment of IoT, traditional access control methods cannot support the security of private data's access control process in current IoT environments. To address such problems, this article proposes an auditable access control model, based on an attribute-based access control model, and manages the access control policy for private data through the request record, the response record, and the access record stored in the blockchain network. Additionally, a Blockchain-based auditable access control system is also proposed based on the auditable access control model, ensuring private data security in IoT environments and realizing effective management and auditable access to these data. Experimental results show that the proposed system can maintain high throughput while ensuring private data security for real application scenarios in IoT environments.
Chaosheng Feng, Bin Liu, Keping Yu, Sotirios K. Goudos · 5 authors
Motivated by Industry 4.0, 5G-enabled unmanned aerial vehicles (UAVs; also known as drones) are widely applied in various industries. However, the open nature of 5G networks threatens the safe sharing of data. In particular, privacy leakage can lead to serious losses for users. As a new machine learning paradigm, federated learning (FL) avoids privacy leakage by allowing data models to be shared instead of raw data. Unfortunately, the traditional FL framework is strongly dependent on a centralized aggregation server, which will cause the system to crash if the server is compromised. Unauthorized participants may launch poisoning attacks, thereby reducing the usability of models. In addition, communication barriers hinder collaboration among a large number of cross-domain devices for learning. To address the abovementioned issues, a blockchain-empowered decentralized horizontal FL framework is proposed. The authentication of cross-domain UAVs is accomplished through multisignature smart contracts. Global model updates are computed by using these smart contracts instead of a centralized server. Extensive experimental results show that the proposed scheme achieves high efficiency of cross-domain authentication and good accuracy.
Paulo Valente Klaine, Lei Zhang, Muhammad Ali Imran
Nowadays data is one of the most important assets that can be obtained, as many applications rely on data to generate useful services. However, a very few number of companies control, in a centralized manner, a large portion of data. That, combined with inefficiencies in centralized storage and recent data leak scandals, highlights the need for new ways in which data is shared and consumed, in which privacy and access control is guaranteed by design. Based on that, in this paper we present an implementation of a blockchain-based data marketplace utilizing the Go Ethereum (Geth) library. The implementation consists of an IoT node powered by a raspberry pi zero W, which is utilized to collect data from the environment and store it in an InterPlanetary File System (IPFS) external server, a web page that displays the marketplace, and a private blockchain that records transactions. Regarding the private blockchain, three smart contracts are developed in order to: 1) record information about the data in the marketplace; 2) record transactions that occur between users; 3) allow sellers to white/blacklist buyers' access to the data. This implementation shows that a decentralized blockchain-based marketplace is feasible and scalable, and we hope it can serve as an early model for future frameworks.
The IoT devices deployed in various application scenarios will generate massive data with immeasurable value every day. These data often contain the user’s personal privacy information, so there is an imperative need to guarantee the reliability and security of IoT data sharing. We proposed a new encrypted data storing and sharing architecture by combining proxy re-encryption with blockchain technology. The consensus mechanism based on threshold proxy re-encryption eliminates dependence on the third-party central service providers. Multiple consensus nodes in the blockchain network act as proxy service nodes to re-encrypt data and combine converted ciphertext, and personal information will not be disclosed in the whole procedure. That eliminates the restrictions of using decentralized network to store and distribute private encrypted data safely. We implemented a lot of simulated experiments to evaluate the performance of the proposed framework. The results show that the proposed architecture can meet the extensive data access demands and increase a tolerable time latency. Our scheme is one of the essays to utilize the threshold proxy re-encryption and blockchain consensus algorithm to support IoT data sharing.
Junaid Ahmed Khan, Kavyashree Umesh Bangalore, Kaan Özbay
Privacy preservation in contact tracing for COVID-19 is challenging as such applications tend to reveal users sensitive data which is shared together with their location. This paper proposes COVERT-Blockchain, a novel distributed ledger based platform for contact tracing without revealing users privacy where infected users only share their anonymized location traces on the Blockchain with a sliding window. To further reduce the chances of revealing the corresponding users' trajectories, in COVERT-Blockchain we employ an adaptive logging mechanism to store trajectory data for contact tracing only if the users stayed in a location for longer time duration. COVERT-Blockchain is evaluated for scalability and robustness in terms of overhead and delays in storing and retrieving data, results show it to be efficiently achieving contact tracing without privacy leakage.
Recently, with the great development of e-health, more and more countries have made certain achievements in the field of electronic medical treatment. The digitization of medical equipment and the structuralization of electronic medical records are the general trends. While bringing convenience to people, the explosive growth of medical data will further promote the value of mining medical data. Obviously, finding out how to safely store such a large amount of data is a problem that urgently needs to be solved. Additionally, the particularity of medical data makes it necessarily subject to great privacy protection needs. This reinforces the importance of designing a safe solution to ensure data privacy. Many existing schemes are based on single-server architecture, which have some natural defects (such as single-point faults). Although blockchain can help solve such problems, there are still some deficiencies in privacy protection. To solve these problems, this paper designs a medical data privacy protection system, which integrates blockchain, group signature, and asymmetric encryption to realize reliable medical data sharing between medical institutions and protect the data privacy of patients. This paper proves theoretically that it meets our security and privacy requirements, and proves its practicability through system implementation.
In mobile crowdsensing (MCS), sensing data uploaded by dishonest workers may be false or even malicious. Thus, a reputation management system is often set up by using workers’ historical behaviors to indicate the quality of sensing data. As existing management schemes usually protect the reputation update process, reputation scores are generally stored in plaintext, which may destroy the fair bidding property of an MCS system. To address this issue, we propose an anonymous reputation management system based on the dual blockchain architecture, where reputation scores are masked. More precisely, one chain is used to store and update reputation scores, and another chain is responsible for publishing tasks and storing task-related data. To anonymously update and verify the reputation scores without affecting their usages in data sensing process, a kind of ring signature and Pedersen commitment is employed in smart contracts. In addition, a Schnorr signature is generated to make the reputation scores verifiable in the MCS system. We implement a prototype system on Hyperledger Fabric, and simulation results are provided for comparisons with two existing schemes.
Shahzaib Tahir, Hasan Tahir, Ali Sajjad, Muttukrishnan Rajarajan · 5 authors
The outbreak of the COVID-19 virus has caused widespread panic and global initiatives are geared towards treatment and limiting its spread. With technological advancements, several mechanisms and mobile applications have been developed that attempt to trace the physical contact made by a person with someone who has been tested COVID-19 positive. While designing these apps, user's privacy has been an afterthought and has resulted in mass violations of privacy of the public and the patients. A total of 32 countries have designed apps and rely on them as a strategy to flatten the pandemic curve. Along with lack of privacy, these methodologies are centralized, where they are fully controlled by the government and the healthcare providers. Owing to these and many other concerns, people are hesitant in the adoption of these technologies. This paper presents a detailed analysis of user tracking apps belonging to 32 countries, thus demonstrating that they collect personal data and are a gross violation of user privacy. This paper presents a novel architecture for the efficient, effective and privacy-preserving contact tracing of COVID-19 patients using blockchain. The proposed architecture preserves the privacy of individuals and their contact history by encrypting all the data specific to an individual using a privacy-preserving Homomorphic encryption scheme and storing it on a permissioned blockchain network. The contacts made with a COVID-19 positive patient are identified by performing search queries directly over the Homomorphic encrypted data stored in the blocks. Therefore, only those contacts that are suspected to be COVID-19 positive may be decrypted by the healthcare professional or government for further contact tracing/diagnosis and COVID-19 testing; thereby leading to enhanced privacy.
Smart cameras, as typical IoT devices, are widely adopted to provide surveillance on individuals, homes, and the environment. The unavoidably captured sensitive visuals via these cameras may raise significant security concerns, while the prevalent software defects and authentication misconfiguration issues aggravate the vulnerability of such devices. However, traditional cryptography techniques are inadequate to provide full protection of these devices due to the large computation overhead. In this context, realizing accountability for these surveillance systems shall be the last line of defense in the presence of fast-evolving and high-influential threats. We propose EviChain, a scalable blockchain-based solution to trace the operations on intelligent surveillance cameras and reserve the evidence for any misuse in tamper-proofing manipulation records. Building a blockchain over the distributed cameras is challenging due to the limited capacity of on-board memory. To tackle this challenge, we design a cooperative mechanism that enables cameras to adaptively join in groups and share storage for recording blocks. In addition, we present a computation efficiency and delay-aware block generation strategy to reduce the cost of the consensus process. We perform extensive simulations to validate the superior performance of EviChain over other baselines, for example, Practical Byzantine Fault Tolerance (PBFT).
Abdullah Lakhan, Mazin Abed Mohammed, S. A. Kozlov, Joel J. P. C. Rodrigues
Abstract The Internet of Medical Things (IoMT) is increasingly being used to secure blockchain technology to operate healthcare applications in a distributed network. The applications are mobile and can move from one place to another with different wireless connectivity. However, there are a lot of challenges that are investigated further. For instance, dynamic content values changed during mobile applications during any business goal. The workflow healthcare applications are complex as compared to coarse‐grained and fine‐grained workload in IoMT. In this article, the study analyzed offloading and scheduling problems for healthcare workflows in IoMT fog‐cloud network. Therefore, the study considered the problem as an offloading and scheduling problem formulated deep reinforcement learning as Markov problem. The study devises the novel deep reinforcement learning and blockchain‐enabled system, consisting of multi‐criteria offloading based on deep reinforcement learning policies and blockchain task scheduling with task sequencing and research matching methods for healthcare workloads in the IoMT system. The simulation results suggested strategies that reduced the communication and computation time for each application in the system.
In the traditional blockchain system, data is public and cannot be redacted. With the development of blockchain technology, the problem that the data cannot be altered will be more serious once it is written on the chain. Recently, some redactable blockchain schemes have been proposed. However, most of the schemes are based on the public blockchain, and the users’ identities and transaction data may be disclosed. To solve the problem of privacy disclosure, we propose a privacy-preserving transaction-level redactable blockchain. In the proposed scheme, symmetric encryption and ring signature are used to protect transaction data and the users’ identities, respectively. In order to prove the legality of data redaction, the transaction sender can reveal the invalid users’ identities and transaction data in an anonymous environment. To construct a transaction-level redactable blockchain, the users only need to replace a single transaction to complete the data redaction instead of replacing the entire block. The experimental results show that the proposed scheme saves 20% of the redaction time compared to the previous privacy-preserving blockchains, so the redaction efficiency is higher.
Open access
Blockchain Technology Applications and Security
Privacy-Preserving Technologies in Data
Advanced Steganography and Watermarking Techniques
While 5G can facilitate high-speed Internet access and make over-the-horizon control a reality for unmanned aerial vehicles (UAVs; also known as drones), there are also potential security and privacy considerations, for example, authentication among drones. Centralized authentication approaches not only suffer from a single point of failure but they are also incapable of cross-domain authentication. This complicates the cooperation of drones from different domains. To address these limitations, a blockchain-based cross-domain authentication scheme for intelligent 5G-enabled Internet of drones is proposed in this article. Our approach employs multiple signatures based on threshold sharing to build an identity federation for collaborative domains. This allows us to support domain joining and exiting. Reliable communication between cross-domain devices is achieved by utilizing smart contract for authentication. The session keys are negotiated to secure subsequent communication between two parties. Our security and performance evaluations show that the proposed scheme is resistant to common attacks targeting Internet of Things (IoT) devices (including drones), as well as demonstrating its effectiveness and efficiency.
Yiping Zuo, Shi Jin, Shengli Zhang, Yu Han · 5 authors
The proof-of-work (PoW) mining process requires a large amount of intensive computing, which leads to some plights such as heavy equipment and fixed access nodes in traditional blockchain networks. A novel mobile blockchain network with the help of a mobile edge computing (MEC) server is presented, where all mobile users participate in the PoW mining process. The traditional Bitcoin network adjusts the target difficulty value to ensure a stable block time. However, for MEC-assisted mobile blockchain networks, the adjusted difficulty value needs to be broadcast to all mobile users, which results in expensive communication costs. To maintain a stable block time of mobile blockchain networks, we formulate the delay-limited computation offloading strategy of the PoW-based mining task as a non-cooperative game that maximizes an individual revenue in the MEC-assisted mobile blockchain network. Specifically, the non-cooperative game problem can be divided into multiple sub-game optimization problems to obtain final solutions for all users. We analyze the sub-game optimization problem and prove the existence of Nash equilibrium (NE) of the non-cooperative game. Moreover, we design an alternating iterative algorithm based on the continuous relaxation and greedy rounding (CRGR) to achieve the NE of this game. Given the sub-optimal delay-limited computation offloading results, we also derive the optimal transmit power for an individual user within the maximum mining delay range. From the analytical results, we can see that the proposed CRGR-based alternating iterative algorithm can efficiently attain the sub-optimal delay-limited computation offloading strategies of all mobile users in the polynomial time. The individual transmit power increases accordingly with the delay-limited computation offloading strategies of all users. Numerical results demonstrate that the proposed CRGR-based alternating iterative algorithm has fast convergence and good stability.
IoT technology has been widely valued and applied, and the resulting massive IoT data brings many challenges to the traditional centralized data management, such as performance, privacy, and security challenges. This paper proposes an IoT data access control scheme that combines attribute-based encryption (ABE) and blockchain technology. Symmetric encryption and ABE algorithms are utilized to realize fine-grained access control and ensure the security and openness of IoT data. Moreover, blockchain technology is combined with distributed storage to solve the storage bottleneck of blockchain systems. Only the hash values of the data, the hash values of the ciphertext location, the access control policy, and other important information are stored on the blockchain. In this scheme, smart contract is used to implement access control. The results of experiments demonstrate that the proposed scheme can effectively protect the security and privacy of IoT data and realize the secure sharing of data.
Bitcoin and many other similar Cryptocurrencies have been in existence for\nover a decade, prominently focusing on decentralized, pseudo-anonymous\nledger-based transactions. Many protocol improvements and changes have resulted\nin new variants of Cryptocurrencies that are known for their peculiar\ncharacteristics. For instance, Storjcoin is a Proof-of-Storage-based\nCryptocurrency that incentivizes its peers based on the amount of storage owned\nby them. Cryptocurrencies like Monero strive for user privacy by using\nprivacy-centric cryptographic algorithms. While Cryptocurrencies strive to\nmaintain peer transparency by making the transactions and the entire ledger\npublic, user privacy is compromised at times. Monero and many other\nprivacy-centric Cryptocurrencies have significantly improved from the original\nBitcoin protocol after several problems were found in the protocol. Most of\nthese deficiencies were related to the privacy of users. Even though Bitcoin\nclaims to have pseudo-anonymous user identities, many attacks have managed to\nsuccessfully de-anonymize users. In this paper, we present some well-known\nattacks and analysis techniques that have compromised the privacy of Bitcoin\nand many other similar Cryptocurrencies. We also analyze and study different\nprivacy-preserving algorithms and the problems these algorithms manage to\nsolve. Lastly, we touch upon the ethics, impact, legality, and acceptance of\nimposing these privacy algorithms.\n
In a ubiquitous environment enclosing cooperative Internet-of-Things (IoT) devices, individuals, and entities, digital identity management (DIM) becomes critical and challenging. DIM pertains to device identities authentication and verification to enable trustworthy service exchange, data collection, and decision making. DIM is the supporting pillar for all online services and the foundation for security and authentication mechanisms. Due to the extreme heterogeneity, scale, and configuration complexity of such environments, enabling trustworthy DIM is crucial and seriously challenging. In an IoT context, devices use local digital identities stored within a tamper-proof unit and verified by a centralized authority for authentication. The recent attacks on IoT systems showed how vulnerable such a design is. It is also an inherent problem that influences humans. From that, self-sovereign identity (SSI) has emerged as a decentralized DIM approach embracing the concept of portable self-possession identity. SSI was presented to couple the digital identity from the owner to enable large-scale cooperation. However, digital identity storage and verification still occur on the device and in a centralized manner. Utilizing a local single-point-of-failure storage memory for verifiable credentials is one of the considerable drawbacks in contemporary SSI. In this regard, this article introduces decentralized trustworthy-self-sovereign identity management (DT-SSIM), a novel decentralized trustworthy SSI management framework. DT-SSIM integrates the secret share scheme with the blockchain-based smart contracts technologies to provide transparent and trustworthy SSI-based DIM services for IoT. Storing IoT identity credentials outside the devices’ local storage preserves the identity credentials from being tampered with or misused. Evaluations and discussions show the resiliency assessment of the system and the cost and estimated running times for verification processes in DT-SSIM.
Philipp Winter, Anna Harbluk Lorimer, Peter Snyder, Benjamin Livshits
Much of the recent excitement around decentralized finance (DeFi) comes from hopes that DeFi can be a secure, private, less centralized alternative to traditional finance systems but the accuracy of these hopes has to date been understudied; people moving to DeFi sites to improve their privacy and security may actually end up with less of both.
In this work, we improve the state of DeFi by conducting the first measurement of the privacy and security properties of popular DeFi applications. We find that DeFi applications suffer from the same kinds of privacy and security risks that frequent other parts of the Web. For example, we find that one common tracker has the ability to record Ethereum addresses on over 56% of websites analyzed. Further, we find that many trackers on DeFi sites can trivially link a user's Ethereum address with PII (e.g., name or demographic information) or phish users.
This work also proposes remedies to the vulnerabilities we identify, in the form of improvements to the most common cryptocurrency wallet. Our wallet modification replaces the user's real Ethereum address with site-specific addresses, making it harder for DeFi sites and third parties to (i) learn the user's real address and (ii) track them across sites.
Message exchange among vehicles plays an important role in ensuring road safety. Emergency message dissemination is usually carried out by broadcasting. However, high vehicle density and mobility lead to challenges in message dissemination such as broadcasting storm and low probability of packet reception. This paper proposes a federated learning based blockchain-assisted message dissemination solution. Similar to the incentive-based Proof-of-Work consensus in blockchain, vehicles compete to become a relay node (miner) by processing the proposed Proof-of-Federated-Learning (PoFL) consensus which is embedded in the smart contract of blockchain. Both theoretical and practical analysis of the proposed solution are provided. Specifically, the proposed blockchain based federated learning results in more vehicles uploading their models in a given time, which can potentially lead to a more accurate model in less time as compared to the same solution without using blockchain. It also outperforms other blockchain approaches in reducing 65.2% of time delay in consensus, improving at least 8.2% message delivery rate and preserving privacy of neighbor vehicle more efficiently. The economic model to incentivize vehicles participating in federated learning and message dissemination is further analyzed using Stackelberg game. The analysis of asymptotic complexity proves PoFL as the most scalable solution compared to other consensus algorithms in vehicular networks.
Most of the existing identity management is the centralized architecture that has to validate, certify, and manage identity in a centralized approach by trusted authorities. Decentralized identity is causing widespread public concern because it enables to give back control of identity to clients, and the client then has the ability to control when, where, and with whom they share their credentials. A decentralized solution atop on blockchain will bypass the centralized architecture and address the single point of the failure problem. To our knowledge, blockchain is an inherited pseudonym but it cannot achieve anonymity and auditability directly. In this paper, we approach the problem of decentralized identity management starting from the designated-verifier anonymous credential (DVAC in short). DVAC would assist to build a new practical decentralized identity management with anonymity and auditability. Apart from the advantages of the conventional anonymous credential, the main advantage of the proposed DVAC atop blockchain is that the issued cryptographic token will be divided into shares at the issue phase and will be combined at the showing credential phase. Further, the smooth projective hash function ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi mathvariant="sans-serif">SPHF</a:mi> </a:math> in short) is regarded as a designated-verifier zero-knowledge proof system. Thus, we introduce the <d:math xmlns:d="http://www.w3.org/1998/Math/MathML" id="M2"> <d:mi mathvariant="sans-serif">SPHF</d:mi> </d:math> to achieve the designated verifiability without compromising the privacy of clients. Finally, the security of the proposed DVAC is proved along with theoretical and experimental evaluations.
Cristina Regueiro, Iñaki Seco, Santiago de Diego, Óscar Lage · 5 authors
The recent increase in reported incidents of security breaches compromising users' privacy call into question the current centralized model in which third-parties collect and control massive amounts of personal data. Blockchain has demonstrated that trusted and auditable computing is possible using a decentralized network of peers accompanied by a public ledger. Furthermore, Homomorphic Encryption (HE) guarantees confidentiality not only on the computation but also on the transmission, and storage processes. The synergy between Blockchain and HE is rapidly increasing in the computing environment. This research proposes a privacy-enhancing distributed and secure protocol for data aggregation backboned by Blockchain and HE technologies. Blockchain acts as a distributed ledger which facilitates efficient data aggregation through a Smart Contract. On the top, HE will be used for data encryption allowing private aggregation operations. The theoretical description, potential applications, a suggested implementation and a performance analysis are presented to validate the proposed solution.