Node Verification Research Articles

Developing a method for the detection and identification of rootstock blockchain network nodes

The object of this study is the protocol for detecting nodes in the Rootstock blockchain network and crawling tools. Node discovery protocols are the foundation of any decentralized peer-to-peer network. In blockchain systems, full nodes store and maintain a complete copy of all transactions performed in the network. However, they do not store information about all other nodes, such as their IDs or IP addresses. Each node usually maintains an incomplete list of nodes to which it connects to exchange blockchain data. In decentralized networks, nodes join and leave the network and their IP addresses can change, making it impractical to maintain a complete, up-to-date list of all nodes. Therefore, the only way to get a list of all nodes in the network is to poll each node sequentially. The developed method involves sending specially formed messages to nodes to obtain their neighbors. The graph search algorithm is used to traverse all received neighboring nodes. This allows one to consistently detect all network nodes. Identifying the desired sequence of messages requires a preliminary analysis of the node software RSKj in the part of node discovery protocol. Effectiveness of the proposed method was verified using the developed software and an experiment in the main network. 6 verification nodes were deployed in different physical locations and at different times. All test nodes were detected in less than 10 minutes. The developed method found 222 nodes that have 209 unique IP addresses. Results of this study show how to perform analysis of node discovery protocol. They provide the means to obtain information about the available nodes of the Rootstock blockchain system, enabling the analysis of both the blockchain network in general and individual node

Towards load balancing in IoV system: A vehicle-assisted batch verification scheme

The Internet of Vehicles (IoV) can improve the efficiency of transportation systems while enhancing the passenger travel experience. However, due to the open wireless communication environment of the IoV, the transmission of data faces the threats of eavesdropping, forging and tampering. Fortunately, the concept of Vehicle-assisted Message Verification Schemes (VMS) are proposed which not only ensures the integrity and authenticity of message but also alleviates the burden of original verification nodes such as Roadside Units (RSUs). Nevertheless, since the individual rationality of vehicles, not all vehicles are willing to participate the message verification tasks. Besides, there may be an overlap in sensory ranges of vehicles that results in redundant verification data. Such two challenges greatly hinder the development of the VMS. Therefore, we present LBABV, a vehicle-assisted batch verification scheme towards load balancing in the IoV system. Firstly, we propose a novel batch verification scheme to enhance the efficiency of messages verification. Then, based on the proposed batch verification scheme, an assisted nodes selection algorithm with incentive mechanism is designed to select a suitable set of vehicles for parallel verification. In this way, the problems of redundant verification as well as individual rationality are elegantly addressed. Theoretical analysis demonstrates the security of our proposal. In the meanwhile, the simulation results show that the system total delay of our LBABV is reduced by 75% compared to batch verification and 81% compared to individual verification, respectively.

Aggregation algorithm based on consensus verification

Distributed learning, as the most popular solution for training large-scale data for deep learning, consists of multiple participants collaborating on data training tasks. However, the malicious behavior of some during the training process, like Byzantine participants who would interrupt or control the learning process, will trigger the crisis of data security. Although recent existing defense mechanisms use the variability of Byzantine node gradients to clear Byzantine values, it is still unable to identify and then clear the delicate disturbance/attack. To address this critical issue, we propose an algorithm named consensus aggregation in this paper. This algorithm allows computational nodes to use the information of verification nodes to verify the effectiveness of the gradient in the perturbation attack, reaching a consensus based on the effective verification of the gradient. Then the server node uses the gradient as the valid gradient for gradient aggregation calculation through the consensus reached by other computing nodes. On the MNIST and CIFAR10 datasets, when faced with Drift attacks, the proposed algorithm outperforms common existing aggregation algorithms (Krum, Trimmed Mean, Bulyan), with accuracies of 93.3%, 94.06% (MNIST dataset), and 48.66%, 51.55% (CIFAR10 dataset), respectively. This is an improvement of 3.0%, 3.8% (MNIST dataset), and 19.0%, 26.1% (CIFAR10 dataset) over the current state-of-the-art methods, and successfully defended against other attack methods.

A Software-Based Remote Attestation Scheme for Internet of Things Devices

With the rapid development of intelligent applications, many Internet of Things (IoT) devices are deployed in various application scenarios, playing an extremely important role. Remote attestation is an important method to ensure the software integrity of these devices and protect them from several attacks. Due to the lack of security hardware and no support of hardware extensions for Class-1 IoT devices, it is particularly important to design a suitable remote attestation scheme for these devices. In this paper, we first propose the delayed observation mechanism to alleviate the problem that the software-based remote attestation scheme is not suitable for wireless networks. At the same time, we propose a "filling memory at attestation-time" mechanism, which solves the problem that attackers hide malicious code through return-oriented programming. Finally, we introduce a reputation mechanism to assist our attestation, and adopt the principle of "making higher-performance verification nodes take on more work" to greatly reduce the time-consuming attestation. We analyze the security of the scheme and implement it on a UNO-R3 development board to prove its practicability and effectiveness. Compared with traditional software-based attestation schemes, our scheme can reduce the attestation time and resist proxy attacks.

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.

An IoV-PBFT Consensus-Based Blockchain for Collaborative Congestion Avoidance and Simulation Test

This paper proposes a novel Internet of Vehicles (IoV) practical Byzantine fault tolerance (PBFT) consensus mechanism suitable for the distributed vehicle-to-vehicle (V2V) scenario and the V2V collaborative congestion avoidance mechanism based on blockchain. Compared with the traditional PBFT consensus mechanism, the proposed IoV-PBFT consensus mechanism has been improved in three aspects. (1) The authenticated vehicles are divided into three types including common nodes, production nodes, and verification nodes. The vehicles in the same congestion road section are used as the consensus participation nodes, which are divided into the production node and verification node. Since the vehicles in this section are moving slowly or even stopping and the number of newly added and departing nodes are less, the identity of the previous nodes is verified before each round of consensus, which ensures the dynamic tolerance with less additional delay. (2) The verification nodes are grouped based on path loss, and the nodes with good channel quality are selected as the leader nodes. (3) The main node in traditional PBFT is omitted, and the two-stage process is used instead of the traditional three-stage process, which effectively reduces the consensus delay and communication complexity. The theoretical derivation and simulation results show that the proposed IoV-PBFT has greatly improved the V2V link quality compared with traditional PBFT, and the success ratio of links between nodes can reach more than 93%, which has met the requirements of establishing blockchain in IoV.

Dynamic Transaction Confirmation Double-chain System Based on Alliance Chain

In recent years, the high performance, strong controllability and partial decentralization of the alliance chain make it have a wide range of application scenarios and development potential. However, restricted by the consensus algorithm, the alliance chain cannot fully meet the needs of practical applications at present. Aiming at the poor stability of the Byzantine Fault Tolerance (PBFT) consensus algorithm, this paper proposes a fast consensus algorithm, which reduces the message size by optimizing the transaction verification process and dynamically adjusting the number of verification nodes. Combined with the reward and punishment system of points, a dynamic transaction confirmation double-chain system is designed. Compared with the alliance chain system implemented by the PBFT algorithm, the system has stronger stability in the case of multiple nodes, and the TPS is increased by at least 21% under the same number of nodes. It is suitable for some nodes with frequent access and poor network.

Distributed Error Correction Coding Scheme for Low Storage Blockchain Systems

This article presents a novel way to reduce blockchain nodes’ memory requirements using error correcting codes. In particular, LDPC codes are taken as examples to explicitly demonstrate the scheme. The proposed coding scheme encodes data across multiple blocks, respectively, block headers, in the blockchain. This leads to a significant reduction in required memory at each node. We then apply the proposed coding technique to blockchains organized in two different ways. Our first scheme has the same protocol for mining, broadcasting, and verification of blocks, as Bitcoin-type blockchains. Our scheme is different in that full nodes do not have to store all blocks. Instead they will need to store only one block of a group of $t$ blocks. In the second scheme, we consider a new block verification protocol and an account-based model under the assumption that transmission between any two nodes can be established, as well as the broadcast transmission. Our block verification protocol uses the Byzantine fault tolerance algorithm and requires sending a newly mined block to only a small number of verification nodes, instead of broadcasting it to the entire network, which leads to a reduction of the network load.

A novel routing verification approach based on blockchain for inter-domain routing in smart metropolitan area networks

In recent years, with the continuous expansion of metropolitan area networks, the routing security problem has become more and more serious. In particular, promise-violating attack to inter-domain routing protocol is one of the most difficult attacks to defend, which always leads to serious consequences, such as maliciously attracting traffic and disrupting the network. To deal with such attack, current research generally adopts routing verification. However, it can only detect attacks violating a specific routing policy triggered by one malicious node, and no research has yet solved the problem caused by multiple collusion nodes. In this paper, we propose BRVM, a blockchain-based routing verification model, to address the issue that violating the shortest AS Path policy. The main idea of BRVM is to construct a route proof chain to verify whether a route violates the policy with the help of the blockchain technology. The precondition that avoiding the collusion attack is that the proportion of the malicious verification nodes is lower than the fault tolerance rate of the consensus algorithm. Then, we prove the correctness of BRVM in theory, and implement a prototype based on Quagga and Hyperledger Fabric. Some experiments on this prototype show that BRVM can indeed solve the promise-violating problem caused by multiple collusion nodes, and about 15.5% faster in performance compared with SPIDeR.

Blockchain Data Privacy Access Control Based on Searchable Attribute Encryption

Data privacy is important to the security of our society, and enabling authorized users to query this data efficiently is facing more challenge. Recently, blockchain has gained extensive attention with its prominent characteristics as public, distributed, decentration and chronological characteristics. However, the transaction information on the blockchain is open to all nodes, the transaction information update operation is even more transparent. And the leakage of transaction information will cause huge losses to the transaction party. In response to these problems, this paper combines hierarchical attribute encryption with linear secret sharing, and proposes a blockchain data privacy protection control scheme based on searchable attribute encryption, which solves the privacy exposure problem in traditional blockchain transactions. The user’s access control is implemented by the verification nodes, which avoids the security risks of submitting private keys and access structures to the blockchain network. Associating the private key component with the random identity of the user node in the blockchain can solve the collusion problem. In addition, authorized users can quickly search and supervise transaction information through searchable encryption. The improved algorithm ensures the security of keywords. Finally, based on the DBDH hypothesis, the security of the scheme is proved in the random prediction model.

Dynamic Autonomous Cross Consortium Chain Mechanism in e-Healthcare.

Safe and scalable dynamic autonomous data interaction between medical institutions can increase the number of clinical trial records, which is of great significance for improving the level of medical trial collaboration, especially for clinical decision-making with regard to rare diseases. Through a preset authorization access and consensus mechanism, consortium chain provides integrity and traceability management for medical clinical data. However, how to enable users have ownership of their own medical data and share their medical data safely and dynamically between different medical institutions remains an area of particular concern. To achieve dynamic communication between medical consortium chains, this paper proposes (i) a cross-chain communication mechanism by simplifying the heterogeneous node communication topology and (ii) the construction rules of the node identity credibility path-proof to carry out dynamic construction and verification of the path-proof for cross-chain transactions. In addition, the consensus of the cross-chain transaction is modeled as a threshold digital signature process with multiple privileged subgroups; thus, the intra-chain consortium consensus based on the verification node list is extended to the cross-chain consensus. A smart contract deployment and execution scheme based on rational node value transfer mechanism is proposed by analyzing the value transfer game between nodes. Experimental results showed that the proposed scheme can not only enable patients to share their records safely and autonomously in an authorized medical consortium chain within milliseconds but also realize dynamic adaptive interaction among heterogeneous consortium chains.

Calculation and application of surface nominal electric fields of ±1100 kV UHVDC power lines

Electric field strength is one of fundamental electromagnetic environmental parameters for the design of ultra-high voltage direct current (UHVDC) power lines and towers when considering human exposure and transient shock. In order to investigate the impacts of power lines’ geometric parameters on the nominal electric fields on the surfaces of ±1100 kV UHVDC sub-conductors, charge simulation method is used for calculations. The algorithm is verified by both verification nodes’ potentials in the process and measurement experiments in the laboratory. The geometric parameter of sub-conductor radius has the most obvious effect on the field. When the radius varies by 10%, the electric field strength on the sub-conductor’s surfaces may change approximately by 8%. Calculation results demonstrate that increasing sub-conductor radius may be most effective measure to restrict the electric field on the ground.

AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks.

Static sink-based wireless sensor networks (WSNs) suffer from an energy-hole problem. This incurs as the rate of energy consumption on sensor nodes around sinks and on critical paths is considerably faster. State-of-the-art en-routing filtering schemes save energy by countering false report injection attacks. In addition to their unique limitations, these schemes generally do not examine energy awareness in underlying routing. Mostly, these security methods are based on a fixed filtering capacity, unable to respond to changes in attack intensity. Therefore, these limitations cause network partition(s), exhibiting adverse effects on network lifetime. Extending network lifetime while preserving energy and security thus becomes an interesting challenge. In this article, we address the aforesaid shortcomings with the proposed adaptive en-route filtering (AEF) scheme. In energy-aware routing, the fitness function, which is used to select forwarding nodes, considers residual energy and other factors as opposed to distance only. In pre-deterministic key distribution, keys are distributed based on the consideration of having paths with a different number of verification nodes. This, consequently, permits us to have multiple paths with different security levels that can be exploited to counter different attack intensities. Taken together, the integration of the special fitness function with the new key distribution approach enables the AEF to adapt the underlying dynamic network conditions. The simulation experiments under different settings show significant improvements in network lifetime.

Homomorphic Consortium Blockchain for Smart Home System Sensitive Data Privacy Preserving

The relative low level of smart home system (SHS) device information security may threaten the privacy of users. In this paper, we propose a homomorphic consortium blockchain for SHS sensitive data privacy preserving (HCB-SDPP), which is based on the traditional smart home system. We add verification services, which are composed of verification nodes, to our model to verify working nodes and transactions in SHS. In order to record the SHS device information transaction, we propose a new block data structure based on homomorphic encryption (HEBDS). Using the HCB-SDPP model, we design an encrypted algorithm based on Paillier encrypted for privacy protection. To verify the validity of the HCB-SDPP model, we firstly encrypt sensitive data of all gateway peers and upload them to the consortium blockchain. Then, we validate the security of sensitive data after homomorphic encryption processing. In the experiment, we also design attack experiments to attack different types of peers on the consortium blockchain in the HCB-SDPP model. If these nodes are insecure, the influence on the whole model will be analyzed. The simulation result shows that the HCB-SDPP model can protect customer privacy more effectively than SHS.

WSN Lifetime Extension Using GA Optimised Fuzzy Logic

A wireless sensor network (WSN) consists of multiple sensor nodes and base stations that collect information from widely deployed sensors. However, the disadvantage is that WSNs are randomly distributed in an open environment, which makes them difficult to manage individually and more easily found and compromised by an attacker. An attacker can execute a false report insertion or invalid vote insertion attack through a compromised node. The Probabilistic Voting Filtering System (PVFS) is a system that prevents these two types of attacks. Before sending a report, the proposed method probabilistically selects a validation node, determines the validity of the report, and filters the report based on the thresholds that have been set. In this paper, the proposed scheme improves the lifetime, detection rate, and report delivery rate of the entire network by increasing the lifetime of the cluster head (CH) by selecting the numbers of message authentication codes (MACs) and verification nodes of the report. Using this system, the event detection rate and the network lifetime are improved by up to 18% and 6%, respectively, relative to the existing PVFS.

WSN Lifetime Extension Using GA Optimised Fuzzy Logic

A wireless sensor network (WSN) consists of multiple sensor nodes and base stations that collect information from widely deployed sensors. However, the disadvantage is that WSNs are randomly distributed in an open environment, which makes them difficult to manage individually and more easily found and compromised by an attacker. An attacker can execute a false report insertion or invalid vote insertion attack through a compromised node. The Probabilistic Voting Filtering System (PVFS) is a system that prevents these two types of attacks. Before sending a report, the proposed method probabilistically selects a validation node, determines the validity of the report, and filters the report based on the thresholds that have been set. In this paper, the proposed scheme improves the lifetime, detection rate, and report delivery rate of the entire network by increasing the lifetime of the cluster head (CH) by selecting the numbers of message authentication codes (MACs) and verification nodes of the report. Using this system, the event detection rate and the network lifetime are improved by up to 18% and 6%, respectively, relative to the existing PVFS.

Overview of Emerging Blockchain Architectures and Platforms for Electronic Trading Exchanges

Several international electronic primary financial exchanges have begun to announce they will explore the adoption of blockchain technology in their trade processing and reporting for execution and clearing. Therefore, in this work we will begin by providing an overview of the new exchange regulations appearing in different jurisdictions around the world, including EMIR, Dodd Frank, MiFID I/II, MiFIR, REMIT, Reg NMS and T2S. We will discuss some of their key features, specifically in regard to transparency reporting and trade/transaction reporting requirements.The current status of regulatory requirements for reporting and the massive data sets such regulation will generate as well as the significant challenges faced by firms and market participants in meeting such requirements in an automated manner, is a key to the discussion in this paper. We explain different blockchain solutions based on blockchain architectures being currently developed in the market place to handle key aspects of transparency and pre and post trade reporting requirements that will be universal in applicability in both UK, Europe and U.S. regulations.In the process of this commentary we will discuss the different emerging architectures and features that are being developed in a range of different blockchain technologies. This will include details on different forms of blockchain technology including : permissionless blockchains, where anyone can participate in the veri cation process, i.e. no prior authorisation is required and a user can contribute his/her computational power, usually in return for a monetary reward. Permissioned blockchains, where verification nodes are preselected by a central authority or consortium. Public blockchains, where anyone can read and submit transactions to the blockchain and Private blockchains, where this permission is restricted to users within an organisation or group of organisations. We detail which market participants and which blockchain architectures are emerging as possible solutions for addressing pre and post trade reporting requirements in modern electronic exchanges.

Energy efficient fuzzy adaptive selection of verification nodes in wireless sensor networks

In Wireless Sensor Networks, sensor nodes are highly vulnerable to several security attacks because they are usually installed in hostile environments. These energy and hardware–resource-constrained nodes, without suitable safeguards, may be compromised by adversaries. Adversaries launch two major types of attacks: false-report injection and false-vote injection attacks via these compromised nodes. These attacks drain significant amounts of energy and drop valid reports. PVFS11Probabilistic voting-based filtering scheme by F. Li et al. [1] counters these two major attacks. One of the reasons to launch false-report injection attack is to drain the energy resource of the entire network to render it unresponsive. We propose Fuzzy-based adaptive selection of the intermediate verification nodes in PVFS to achieve optimal energy savings. We demonstrate that our proposed method achieves better energy conservation in the presence of both the aforementioned security threats while providing the same high filtering control of the PVFS.

무선 센서 네트워크에서 확률적 투표 기반 여과 기법의 에너지 효율성을 위한 퍼지 로직 시스템 기반의 다음 이웃 노드 선택 기법

무선 센서 네트워크에서 센서 노드들은 개방된 환경에 배치되기 때문에 공격자들을 통해 쉽게 훼손된다. 공격자는 훼손된 노드를 통해 허위 보고서 및 허위 투표 주입 공격을 할 수 있다. 이러한 공격은 센서 노드의 에너지를 고갈시키거나 정상 보고서의 전송을 막는다. 이 두 가지 공격에 대응하기 위해 Li와 Wu는 확률적 투표 기반 여과 기법을 제안하였다. 이 기법은 보고서 임계값과 검증 노드를 고정적으로 사용하기 때문에 센서 노드의 에너지를 비효율적으로 사용한다. 본 논문에서는 PVFS의 에너지 향상을 위해 퍼지 로직 시스템을 기반으로 다음 이웃 노드 선택 방법을 제안한다. 퍼지 로직 시스템의 매개변수들은 에너지, 홉의 수, 검증 성공 횟수이며, CH는 퍼지 로직 시스템을 기반으로 도출된 2개의 이웃 노드 중에서 상태 정보가 높은 다음 이웃 노드를 선택한다. 실험을 통해 제안 기법은 기존 기법과 비교하여 약 9%의 에너지가 향상되었고, 센서 노드들의 에너지 절감을 통해 전체 네트워크의 수명 연장을 기대한다. Sensor nodes are easily compromised by attacker when which are divided in open environment. The attacker may inject false report and false vote attack through compromised sensor node. These attacks interrupt to transmission legitimate report or the energy of sensor node is exhausted. PVFS are proposed by Li and Wu for countermeasure in two attacks. The scheme use inefficiency to energy of sensor node as fixed report threshold and verification node. In this paper, our propose the next neighbor node selection scheme based on fuzzy logic system for energy improvement of PVFS. The parameter of fuzzy logic system are energy, hops, verification success count, CH select high the next neighbor node among neighbor nodes of two as deduction based on fuzzy logic system. In the experimental, our proposed scheme was improvement to energy of about 9% compare to PVFS.

Distributed Information Flow Verification Framework for the Composition of Service Chain in Wireless Sensor Network

Dynamic service composition provides us with a promising approach to cooperate different sensor nodes in WSN to build complex applications based on their basic functions. Usually multiple nodes located in different regions provide data with different security levels, and it is critical to ensure the security of the information flow in the composite services. However, the energy-limited nature of sensor nodes in WSN poses a significant challenge for the centralized information flow verification with which the verification node needs to consume lots of computation and network resources. In this paper, we specify the security constraints for each service participant to secure the information flow in a service chain based in the lattice model and then present a distributed verification framework that cooperates different service participants to verify their information flow policies distributively. The evaluation results show a significant decrease on the verification cost of the single verification node, which provides a better load balance in each sensor node.