Single Point Of Failure Problem Research Articles

A Secure Data E-Governance for Healthcare Application in Cyber Physical Systems

The bio-medical devices gather patient information and communicate it to data consumers via wireless networks to take the appropriate action and decision by informing the doctors. However, IoMT is adopted by healthcare departments with a greater speed, yet the majority of devices are limited to resource constraints and security perspectives. The classical e-healthcare systems that are centric have the inherent problem of single-point failure with low transparency and low control over records. Many proposals have been validated in IoT for addressing the inadequate computing and storage of records through sensors. The main focus of this paper is to propose a novel hybrid architecture called Zero Trust Blockchain Architecture for decentralized E-health-CPS systems to support low latency along with storage and processing of records while monitoring the patients. In addition, a probability distribution function may further draft an accurate and real-time monitoring of patients. The proposed mechanism is analyzed against adequate decision, storage, accuracy and transmission of records.

Multiple time servers timed-release encryption based on Shamir secret sharing for EHR cloud system

Electronic health record (EHR) cloud system, as a primary tool driving the informatization of medical data, have positively impacted both doctors and patients by providing accurate and complete patient information. However, ensuring the security of EHR cloud system remains a critical issue. Some patients require regular remote medical services, and controlling access to medical data involving patient privacy during specific times is essential. Timed-release encryption (TRE) technology enables the sender to preset a future time T at which the data can be decrypted and accessed. It is a cryptographic primitive with time-dependent properties. Currently, mainstream TRE schemes are based on non-interactive single time server methods. However, if the single time server is attacked or corrupted, it is easy to directly threaten the security applications of TRE. Although some research schemes “distribute” the single time server into multiple ones, they still cannot resist the single point of failure problem. To address this issue, we propose a multiple time servers TRE scheme based on Shamir secret sharing and another variant derived from it. In our proposed schemes, the data receiver does not need to interact with the time servers; instead, they only need to obtain the time trapdoors that exceed or equal the preset threshold value for decryption, which ensures the identity privacy of the data sender and tolerates partial downtime or other failures of some time servers, significantly improving TRE reliability. Security analysis indicates that our proposed schemes demonstrate data confidentiality, verifiability, anti-advance decryption, and robust decryption with multiple time trapdoors, making them more practical. Efficiency analysis indicates that although our schemes have slightly higher computational costs than most efficient existing TRE schemes, such differences are insignificant from a practical application perspective.

Distributed Energy Dispatch for Geo-Data Centers Port Microgrid

With the development of port automation and artificial intelligence, coordination with multi-geographic data centers (Geo-DCs) has become a viable solution to address the issue of limited port computing resources. This study proposes a distributed energy dispatch method for the port microgrid coordinated with Geo-DCs (Geo-DCPM), aimed at reducing port carbon emissions and operational costs. Consider the single point of failure problem and high construction costs of centralized data centers. Geo-DCs are first introduced to solve the problem of insufficient computing resources in ports. An energy consumption calculation model for Geo-DCs is established, considering the data load delay constraint and the data space transfer constraint caused by specific delay-sensitive loads in the port microgrid. Then, an energy dispatch model (EDM) is constructed for the Geo-DCPM, taking into account carbon capture costs. Moreover, based on mixed-integer linear programming, a distributed algorithm is proposed to solve the EDM problem. Finally, the simulation results verify the effectiveness of the proposed method. Compared with the centralized algorithm, the packet loss rate of the distributed algorithm combined with Geo-DCs is significantly lower, reduced by about 70%.

Federated learning with blockchain-based model aggregation and incentives

Federated learning is a privacy-preserving machine learning technique that allows mutually distrusting parties to collaboratively train a model without sharing their data. Most federated learning techniques require a centralized aggregator that stores and aggregates models received from multiple parties. However, having a centralized entity may lead to a single point of failure problem. Another problem of federated learning is the leakage of sensitive data through model updates. To address these issues, we propose a Blockchain-based protocol for federated learning. Our protocol uses Blockchain as a model aggregator solving single-point-of-failure problems. Also, we use a Blockchain-based privacy-preserving technique to avoid data leakage problems. We also incorporate a Blockchain-based incentive distribution module to distribute incentives to model contributors. We perform experiments with well-known datasets and show that the proposed model's accuracy is close to that of a centralized aggregator. We also show the overhead of Blockchain by implementing the protocol and running it on Ethereum Blockchain.

A practical and UC-secure decentralized key management and authentication scheme based on blockchain for VNDN

In Vehicular Named Data Networking (VNDN), most of the existing key management mechanisms still rely on the hierarchical key trust model or the Public Key Infrastructure (PKI), in which the centralized certificate authority is used as a Trusted Third Party (TTP) to provide a signature for the user?s public key. Thus, the TTP becomes vulnerable to attacks and maybe there exists a singlepoint failure problem. In addition, the in-network caching in the VNDN may incur a threat to the system and make it is vulnerable to the DoS attack caused by Interest flooding aimed at the Content-Store. To tackle these security issues, we firstly propose an efficient decentralized key management solution based on blockchain for VNDN. Secondly, based on the proposed key management scheme, a lightweight mutual authentication scheme and a key agreement protocol for V2X are respectively proposed in this paper. Finally, we analyze the security attributes of our solutions in the Universally Composable (UC) framework. Our analysis results show that our novel schemes can meet the security requirements of our solutions. In addition, our experimental results show our new schemes have highly efficient, lower computation and communication costs than other related schemes.

B-UAVM: A Blockchain-Supported Secure Multi-UAV Task Management Scheme

The advent of unmanned aerial vehicle (UAV) swarm technology brings possibilities to help humans complete tasks in no man’s land, such as deserts, and rainforests. However, UAV network faces many cyber threats, where attackers can impersonate legitimate entities or tamper with UAV task data. For identity security, most of the existing methods use centralized authentication schemes, which have a single point of failure problem. For data security, the existing methods only secure the task data in the ground system, ignoring the data security in the air network. Therefore, the existing methods are not suitable for ubiquitous UAV scenarios. Blockchain secures data security while eliminating the single point of failure problem, and has been widely used in distributed scenarios. In this paper, to secure entity identity and task data, we propose a Blockchain-supported Secure Multi UAV Task Management Scheme (B-UAVM). Specifically, a three-layer blockchain structure is constructed to secure multi-tasks, and achieve ubiquitous control of UAV formations. Besides, six types of blocks and three types of transactions are designed to achieve safe processing and storage of task data and entity information. Furthermore, an improved Practical Byzantine Fault Tolerance (IPBFT) consensus mechanism and a UAV-formation-action-considered ground station consensus mechanism (UFAGS) are introduced in the Server Network and Ground Control Network, respectively, to accelerate the consensus. The experimental results show that the number of transactions generated per second (TPS) of B-UAVM is about 0.5× and 3.7× of the existing method when the block size or the number of blockchain nodes increases, respectively.

Secure decision tree classification with decentralized authorization and access control

Outsourcing decision tree classification services to the cloud is highly beneficial, yet raises critical privacy problems. In order to preserve data privacy, data owners may choose to upload encrypted data rather than raw data to the classification services. However, these solutions adopted today for encrypted data classification not only fall short in system flexibility and scalability, but also face the single point of failure problem. In this paper, we design, implement, and evaluate a secure decision tree classification scheme that allows decentralized authorization and access control service (SDTC-DAAC). Firstly, we propose a new framework that decouples data encryption and data computation logic to achieve the separation of data storage and computation, which significantly improves upon the flexibility and effectiveness, thus achieving cross-system compatibility requirements. Secondly, we present an end-to-end encrypted access control mechanism which enables authorized users from different parties to participate in calculations together. Finally, we further devise a scheme which serves decentralized storage service of data access control policies and access authorization without trusted intermediaries. Extensive property and performance analysis shows that SDTC-DAAC is effectiveness, as well as satisfying the security requirements for data privacy in an outsourcing environment.

Massive Data Connection Architecture Design of Web Platform Based on Blockchain

In order to improve the universality and security of the data management of the Internet of Things and avoid the single point of failure problem in the traditional management architecture, this paper proposes a massive connection management architecture based on blockchain. The blockchain is reconstructed according to the hierarchical structure of blockchain technology, and with reference to the attribute-based access control mechanism, a data exchange model is designed using gossip mode and TLS networking mode to ensure the safe transmission of data. The peer computer network technology, data signature, and consensus mechanism are used to complete the design of the data exchange network layer and realize the design of the blockchain-based massive connection management architecture, so as to effectively avoid the single point of failure problem in the traditional management architecture and greatly reduce the burden of the management center. The access requests of massive devices in 5G application scenarios were simulated, and the results showed that the blockchain-based access control architecture designed in this article can quickly process received requests, with information leakage below 10%, improving the security and processing performance of data connections, achieving efficient processing and management of large-scale data, and providing reliable guarantees for the development of the Internet era.

A tamper-resistant timed secure data transmission protocol based on smart contract

Many time-sensitive scenarios need to decrypt data at a specified time. The timed-release encryption (TRE) primitive can meet this requirement. However, in the single-time server TRE model, there is a single point of failure problem. Therefore, we propose a tamper-resistant timed secure data transmission protocol based on smart contracts. Firstly, by decomposing the ciphertext into ciphertext fragments, the amount of deposit that a single middleman needs to submit is reduced. Secondly, it provides the system with security redundancy that changes with the decomposition mode. Thirdly, the sender is required to submit the hash value of each ciphertext fragment to the blockchain network at the same time as sending data, so that the receiver can quickly verify the authenticity of the ciphertext to resist substitution attack. Security analysis shows that the proposed protocol model can resist interruption attacks, release-ahead attacks and replacement attacks. Finally, we conduct a monetary cost test on the Ethereum’s Rinkeby test network. The results show that our running cost is almost double compared with the existing similar scheme, but it is still very low and almost negligible compared with the value of the content and the expected profits it brings.

A Certificateless Signcryption Mechanism Based on Blockchain for Edge Computing

The emergence of edge computing makes it possible to realize new technologies such as virtual reality and augmented reality. However, a large number of devices and more messages at the edge bring more security problems. Therefore, it is an important research topic to provide users with faster network services while ensuring confidentiality and authentication of data transmission. Because signcryption can encrypt and sign messages at the same time, it has become a new cryptographic primitive. In the meantime, certificateless signcryption guarantees data confidentiality and authentication and addresses traditional single point failure problems based on the trust center and the problem of relying on a trusted third party. Therefore, certificateless signcryption has attracted great attention from academia and industry. But certificateless signcryption also faces two types of attacks. In order to more effectively resist these two types of attacks, we propose a certificateless signcryption mechanism based on blockchain. This mechanism can make good use of the nontamperable feature of blockchain, prevent illegal users from substituting public key of the user, and guarantee signature non-repudiation. And our scheme is investigated in a comparative study with eight schemes. Comparative analysis outcomes demonstrate our scheme has achieved better results in efficiency and security. The process of signcryption and unsigncryption consumes the least amount of computation, which is very suitable for the edge computing environment.

Enable the proactively load-balanced control plane for SDN via intelligent switch-to-controller selection strategy

The novelty of the software-defined network(SDN) is to separate the control plane and the data plane for easier manipulation of the network. The distributed control plane is designed to achieve more powerful computation capacity and address the single-point failure problem. However, it also poses a new challenge that how to arrange switch-controller associations effectively. The direct static configuration cannot adapt the time-varying requests from switches well, and it would result in imbalance problems on the control plane and cause long-tail latency. Thus, it is necessary to take proper actions to adjust the switch-to-controller association dynamically. Existing controller-based load balancing methods need to communicate with the switches frequently and incur not only high assumptions of the rare control channel of SDN but also high computation costs. In this paper, we provide a switch-based solution that puts Reinforcement Learning agents on all Switches (RLoS). Instead of setting static rules predefined by operators, RLoS makes each switch actively select the best controller. RLoS treats every switch as an independent agent with its own neural network and parameters. With the carefully designed training algorithm, the agents could choose their preferable controllers via their local information. The results show that even with partial observation, the RLoS still can achieve considerable improvement in the load balance among all controllers compared with those controller-based association benchmarks. Our RLoS could decrease the maximum response latency among controllers by about 5%∼15% under different scenarios on average.

Accountable multi-authority attribute-based data access control in smart grids

The developments of AI, information security and network technology have improved the security, efficiency of the smart grid system. However real-time data and consume data sharing make privacy leakage, malicious entities and users be uncontrollable factors in the grid. Accountability can solve them partly and give an enhanced security guarantee to smart grid. The existing accountability system only focuses on the device level, and does not consider actual security. In this paper, an accountable multi-authority access control framework based attribute-based encryption (ABE) on for smart grid was proposed to solve the above problems. The proposed scheme not only solves the single-point failure problem in the smart grid, but also supports securely fine-grained access control to sharing data in real time. Furthermore, this scheme uses a protocol to limit the control of private keys by malicious entities, and can trace the responsibilities of malicious entities to ensure data security and privacy. Finally, theoretical analyses and performance evaluations show the proposal is more efficient and secure than the available.

Antiquantum Privacy Protection Scheme in Advanced Metering Infrastructure of Smart Grid Based on Consortium Blockchain and RLWE

Smart meters in advanced metering infrastructure (AMI) collect fine-grained, real-time power consumption data may result in user privacy leakage. Aiming at the problem that existing privacy protection schemes cannot resist quantum attacks, an antiquantum privacy protection scheme in AMI of smart grid based on consortium blockchain and ring learning with errors (RLWE) is proposed. The scheme has the following contributions. First, the RLWE-based secure communication scheme is designed in this article, which ensures the resistance of the scheme to quantum attacks. Second, all smart meters in AMI use anonymous identity to communicate with the control center, and the fine-grained power consumption data is also encrypted and digitally signed to prevent user privacy leakage and tampering of power consumption data. And the scheme does not use bilinear pairings and exponential operations and has efficient computational performance. Third, a two-tier consortium blockchain storage system consisted of regional gateways and data aggregators are designed to eliminate the single point of failure problems of the data aggregators. The practical byzantine fault tolerance consensus mechanism is improved to reduce the communication cost in the consensus process. The scheme's security is proven theoretically, and the experimental results show that the scheme has a low computational cost.

Cross-Domain Access Control Model in Industrial IoT Environment

The Industrial Internet of Things (IIoT) accelerates smart manufacturing and boosts production efficiency through heterogeneous industrial equipment, intelligent sensors, and actuators. The Industrial Internet of Things is transforming from a traditional factory model to a new manufacturing mode, which allows cross-domain data-sharing among multiple system departments to enable smart manufacturing. A complete industrial product comes from the combined efforts of many different departments. Therefore, secure and reliable cross-domain access control has become the key to ensuring the security of cross-domain communication and resource-sharing. Traditional centralized access control schemes are prone to single-point failure problems. Recently, many researchers have integrated blockchain technology into access control models. However, most blockchain-based approaches use a single-chain structure, which has weak data management capability and scalability, while ensuring system security, and low access control efficiency, making it difficult to meet the needs of multi-domain cooperation in IIoT scenarios. Therefore, this paper proposes a decentralized cross-domain access model based on a master–slave chain with high scalability. Moreover, the model ensures the security and reliability of the master chain through a reputation-based node selection mechanism. Access control efficiency is improved by a grouping strategy retrieval method in the access control process. The experimental benchmarks of the proposed scheme use various performance metrics to highlight its applicability in the IIoT environment. The results show an 82% improvement in the throughput for the master–slave chain structure over the single-chain structure. There is also an improvement in the throughput and latency compared to the results of other studies.

Fog-enabled private blockchain-based identity authentication scheme for smart home

As the Internet of Things (IoT) technology continues to advance, it has found widespread application in various fields, including smart health, smart cities, and smart transportation. Among these applications, smart homes are particularly noteworthy due to their intimate connection to our daily lives. However, the use of smart devices in a home environment exposes users to various security threats, such as impersonation attacks and insider privilege attacks, as users must communicate with multiple devices through a public channel. Additionally, traditional authentication schemes that rely on trusted third-party present a single point of failure, as users and smart devices must be registered and authenticated by a central authority. Blockchain technology offers a decentralized, tamper-proof, and flexible solution for authentication and access control of data. By using blockchain, the single point of failure problem in traditional authentication schemes can be resolved. In the context of smart homes, the real-time nature of the environment necessitates the use of fog nodes to provide localized computing services. Fog nodes are closer to IoT devices than cloud nodes, making fog computing more efficient and faster than cloud computing. This paper proposes an authentication scheme for blockchain-enabled fog nodes in smart homes. The scheme involves registering all fog nodes and intelligent devices on a local private blockchain, and authentication is performed jointly by smart contracts on the blockchain and off-chain operations. The scheme provides comprehensive security and better performance, as demonstrated by security analysis and performance evaluation. Moreover, the proposed scheme offers a certain level of user privacy protection.

Distributed anti-windup NN-sliding mode formation control of multi-ships with minimum cost

Due to the harsh marine environment, the communication cost of multi-ship formation is expensive, but it is often ignored in the existing research. On this basis, this paper proposes a novel distributed anti-windup neural network (NN)-sliding mode formation controller of multi-ships with minimum cost. Firstly, distributed control is applied to devise the formation controller of multi-ships because it is a promising solution for the problem of single point failure. Secondly, the Dijkstra algorithm is introduced to optimize the communication topology, and then an optimized communication topology with minimum cost is used in the distributed formation controller design. Thirdly, to alleviate the influence of input saturation, an anti-windup mechanism is devised by combining an auxiliary design system with sliding mode control and radial basis function neural network method; and then a novel distributed anti-windup neural network-sliding mode formation controller of multi-ships is obtained, which can also handle the problem of nonlinearity, model uncertainty, and time-varying disturbances of ship motion. On the strength of Lyapunov theory, the closed-loop signals are proved to be stable. Multiple comparative simulations are carried out to validate the effectiveness and advantage of the proposed distributed formation controller.

Improvement of blockchain-based multi-layer location data sharing scheme for Internet of Things

With the continuous development of the Internet of Things, user location data sharing has attracted increasing attention in various fields. However, current state-of-the-art data sharing system rely on centralized servers. This can create a single point of failure, with deleted data being unrecoverable. In addition, when performing data integrity verification, present schemes are only applicable to static scenarios. Dynamic update scenarios will incur enormous computational and communication costs. In this paper, we design a multi-layer location sharing scheme based on blockchain, which solves the single point of failure problem well. Our proposed scheme can also be adapted to dynamic scenarios. We utilize an accumulator to make our scheme more efficient in data updating and verification. The scheme also has a constant communication cost. Finally, we adopt a formal security analysis based on Real-Or-Random (ROR), and evaluate the performance of our scheme. The experimental results show that our scheme in comparison with existing methods, finding it to be superior in terms of computational cost, communication cost, safety, and efficiency.

A hybrid blockchain-based identity authentication scheme for Mobile Crowd Sensing

With the continuous innovative development and popularization of mobile smart devices, the application of Mobile Crowd Sensing (MCS) continues to be studied extensively. However, existing centralized MCS applications that use servers for task publishing and data collection exhibit common problems, such as single points of failure and security vulnerabilities. Accordingly, we proposed a hybrid blockchain-based identity authentication scheme for MCS called HBIA, which uses blockchain technology to resolve the single-point failure problem. HBIA builds a cluster structure based on factors such as geographical location and balance, and uses it to construct a hybrid blockchain, with the cluster head node and internal cluster node authenticating on the public and private chains, respectively. We also implemented zero-knowledge proof (ZKP) to ensure the privacy of participants’ identities, thus balancing the contradiction between blockchain transparency and security. In addition, HBIA uses the zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK) technology to enable off-chain computing and on-chain verification, further reducing the blockchain’s workload. Finally,​ HBIA was evaluated based on the pavement crack detection task and tested on the Ethereum public test network known as Ropsten. The test results indicate that the identity authentication scheme proposed in this paper is superior to existing schemes in terms of authentication time.

Visual Object Detection for Privacy-Preserving Federated Learning

Visual object detection is a computer vision technique based on deep learning. However, due to privacy issues, it is highly challenging to build an object detection model according to the current methods on the centrally stored training dataset. Federated learning is an effective approach to solving the challenge of training data collection by using distributed training. We propose FedVisionBC, a blockchain-based federated learning system for visual object detection that addresses the challenges of single point of failure, model poisoning attacks, and membership inference attacks in traditional federated learning. In the FedVisionBC system, we set up an aggregation node and a verification node instead of a central server to solve the single point of failure problem. We establish a security mechanism that uses encryption techniques, verification nodes, and smart contracts to resist model poisoning attacks. Experimental results show that FedVisionBC can accomplish the object detection task when the percentage of malicious clients is less than 60%. We also propose a new algorithm, ADPFedAvg, to prevent membership inference attacks, which relies on user-level differential privacy technology and the federal average algorithm. Experimental results indicate that ADPFedAvg can achieve a large-scale visual object detection model with differential privacy protection, while only a negligible cost in predictive accuracy.

A Blockchain-Based Data Sharing System with Enhanced Auditability

Cloud platforms provide a low-cost and convenient way for users to share data. One important issue of cloud-based data sharing systems is how to prevent the sensitive information contained in users’ data from being disclosed. Existing studies often utilize cryptographic primitives, such as attribute-based encryption and proxy re-encryption, to protect data privacy. These approaches generally rely on a centralized server which may cause a single point of failure problem. Blockchain is known for its ability to solve such a problem. Some blockchain-based approaches have been proposed to realize privacy-preserving data sharing. However, these approaches did not fully explore the auditability provided by the blockchain. The dishonest cloud server can share data with a requester without notifying the data owner or being logged by the blockchain. In this paper, we propose a blockchain-based privacy-preserving data sharing system with enhanced auditability. The proposed system follows the idea of hybrid encryption to protect data privacy. The data to be shared are encrypted with a symmetric key, and the symmetric key is encrypted with a joint public key which is the sum of multiple blockchain nodes’ public keys. Only if a data requester is authorized, the blockchain nodes will be triggered to execute a verifiable key switch protocol. By using the output of the protocol, the data requester can get the plaintext of the symmetric key. The blockchain nodes participate in both the authorization process and the key switch process, which means the behavior of the data requester is witnessed by multi-parties and is auditable. We implement the proposed system on Hyperledger Fabric. The simulation results show that the performance overhead is acceptable.