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Showing papers in "Peer-to-peer Networking and Applications in 2021"


Journal ArticleDOI
TL;DR: A comprehensive survey of blockchain-enabled smart contracts from both technical and usage points of view is presented in this article, where the authors identify a set of challenges and open issues that need to be addressed in future studies.
Abstract: In recent years, the rapid development of blockchain technology and cryptocurrencies has influenced the financial industry by creating a new crypto-economy. Then, next-generation decentralized applications without involving a trusted third-party have emerged thanks to the appearance of smart contracts, which are computer protocols designed to facilitate, verify, and enforce automatically the negotiation and agreement among multiple untrustworthy parties. Despite the bright side of smart contracts, several concerns continue to undermine their adoption, such as security threats, vulnerabilities, and legal issues. In this paper, we present a comprehensive survey of blockchain-enabled smart contracts from both technical and usage points of view. To do so, we present a taxonomy of existing blockchain-enabled smart contract solutions, categorize the included research papers, and discuss the existing smart contract-based studies. Based on the findings from the survey, we identify a set of challenges and open issues that need to be addressed in future studies. Finally, we identify future trends.

140 citations


Journal ArticleDOI
TL;DR: The proposed ODSD framework has exceptional benefits for real-time applications while maintaining the security of the dynamic storage of data.
Abstract: The Industry 4.0 IoT network integration with blockchain architecture is a decentralized, distributed ledger mechanism used to record multi-user transactions. Blockchain requires a data storage system designed to be secure, reliable, and fully transparent, emerged as a preferred IoT-based digital storage on WSN. Blockchain technology is being used in the paper to construct the node recognition system according to the storage of data for WSNs. The data storage process on such data must be secure and traceable in different forensics and decision making. The primary theme of the dynamic data security is therefore for rejecting exploitation of the unauthorized user and for evaluating the mechanism in tracing and evidence of system’s data operation in a dynamic manner, growth and quality features under the stochastic state of the model; (1) a mathematical method for the secured storage of data in dynamic is built through distributed node cooperation in IoT industry. (2) the ownership transition feature and the dynamic storage of data system architecture are configured, (3) the emerging distributed storage architecture for blockchain-based WSN will substantially reduce overhead storage for each node without affecting data integrity; (4) minimize the latency of data reconstruction in distributed over storage system, and propose an effective and scalable algorithm for optimizing storage latency issue. In addition to this research, the system implements verified possession of data for replacing the evidence in original digital currency for mining and to store new data blocks that will be compared to the proof system, dramatically reduces computational capacity. The proposed ODSD framework has exceptional benefits for real-time applications while maintaining the security of the dynamic storage of data.

114 citations


Journal ArticleDOI
TL;DR: By simulation results, it is proves that the proposed trust based authentication method for clustered vehicular ad hoc networks increases the accuracy in detecting malicious nodes and the packet delivery ratio, and decreases the delay of authentication and overhead.
Abstract: Vehicular Ad hoc Networks (VANETs) as a subset of mobile ad hoc networks which allow communication between any vehicle with other adjacent vehicles, road side units and infrastructure. In these networks, the purpose is to enhance the security, improve the management of urban and road traffic and provide services to the passenger. Due to problems such as reliability and privacy, messages that are exchanged in the network should be confidential and secure. Therefore, we need a secure topology to maintain trust, which enables the cryptographic process. In this paper, a trust based authentication method for clustered vehicular ad hoc networks is proposed. The efficient authentication method should be able to accurately detect malicious nodes and reduced delay and overhead. The main purpose of the proposed method is to create trustworthy and stable clusters that lead to the stability of the entire network. For this purpose, we estimate the trust degree of each vehicle by combining the trust between vehicles and the trust between the vehicle and Road Side Units (RSUs), and Cluster Heads (CHs) are selected based on this estimated trust degree. Cluster Heads along with verifiers are responsible for monitoring each vehicle. On the other hand, the cluster heads provide an optimal and secure route for transmitting messages. Messages are digitally signed by the sender and encrypted using a public/private key as distributed by a Trusted Authority (TA) and decrypted by the destination; so that each message contains a certificate from a trusted authority. In this identification, the sender and receiver of the message are verified and authentication will be achieved. By simulation results, it is proves that the proposed method increases the accuracy in detecting malicious nodes and the packet delivery ratio, and decreases the delay of authentication and overhead.

93 citations


Journal ArticleDOI
TL;DR: This paper focuses on solving some identity authentication issues remained in the smart grid, and proposes a reliable and efficient authentication protocol for smart meters and utility centers with security and performance improvement compared with the other ECC related schemes.
Abstract: Smart grid has been acknowledged as the next-generation intelligent network that optimizes energy efficiency. Primarily through a bidirectional communication channel, suppliers and users can dynamically adjust power transmission in real time. Nonetheless, many security issues occur with the widespread deployment of smart grid, e.g., centralized register authority and potential Distributed-Denial-of-Service (DDoS) attack. These existing problems threaten the availability of smart grid. In this paper, we mainly focus on solving some identity authentication issues remained in the smart grid. Combined with blockchain, Elliptic Curve Cryptography (ECC), dynamic Join-and-Exit mechanism and batch verification, a reliable and efficient authentication protocol is proposed for smart meters and utility centers. Simultaneously, the provable security of this protocol is assured by the computational hard problem assumptions. Experiment results show that our protocol has achieved security and performance improvement compared with the other ECC related schemes.

79 citations


Journal ArticleDOI
TL;DR: The simulation results show that compared with PBFT and RAFT, the new consensus algorithm increases the data throughput while supporting more nodes, and effectively reducing the consensus delay and the number of communication times between nodes.
Abstract: According to different application scenarios of blockchain system, it is generally divided into public chain, private chain and consortium chain. Consortium chain is a typical multi-center blockchain, because it has better landing, it is supported by more and more enterprises and governments. This paper analyzes the advantages and problems of Practical Byzantine Fault Tolerance (PBFT) algorithm for the application scenarios of the consortium chain. In order to be more suitable for consortium chains, this paper proposes a new optimized consensus algorithm based on PBFT. Aiming at the shortcomings of PBFT, such as the inability to dynamically join nodes, low multi-node consensus efficiency, and primary master node selection, our optimized algorithm has designed a hierarchical structure to increase scalability and improve consensus efficiency. The simulation results show that compared with PBFT and RAFT, our new consensus algorithm increases the data throughput while supporting more nodes, and effectively reducing the consensus delay and the number of communication times between nodes.

63 citations


Journal ArticleDOI
TL;DR: This research presents a new Penetration Testing framework for smart contracts and decentralized apps and compared results from the proposed penetration-testing framework with automated penetration test Scanners, which detected missing vulnerability that were not reported during regular pen test process.
Abstract: Smart contracts powered by blockchain ensure transaction processes are effective, secure and efficient as compared to conventional contacts. Smart contracts facilitate trustless process, time efficiency, cost effectiveness and transparency without any intervention by third party intermediaries like lawyers. While blockchain can counter traditional cybersecurity attacks on smart contract applications, cyberattacks keep evolving in the form of new threats and attack vectors that influence blockchain similar to other web and application based systems. Effective blockchain testing help organizations to build and utilize the technology securely withe connected infrastructure. However, during the course of our research, the authors detected that Blockchain technology comes with security considerations like irreversible transactions, insufficient access, and non-competent strategies. Attack vectors, like these are not found on web portals and other applications. This research presents a new Penetration Testing framework for smart contracts and decentralized apps. The authors compared results from the proposed penetration-testing framework with automated penetration test Scanners. The results detected missing vulnerability that were not reported during regular pen test process.

50 citations


Journal ArticleDOI
TL;DR: The safety, communication, and traffic-related issues in VANET systems and their implementation in-feasibility are highlighted and how machine learning algorithms can overcome these issues are explored.
Abstract: Low latency in communication among the vehicles and RSUs, smooth traffic flow, and road safety are the major concerns of the Intelligent Transportation Systems. Vehicular Ad hoc Network (VANET) has gained attention from various research communities for such a matters. These systems need constant monitoring for proper functioning, opening the doors to apply Machine Learning algorithms on enormous data generated from different applications in VANET (for example, crowdsourcing, pollution control, environment monitoring, etc.). Machine Learning is an approach where the system automatically learns and improves itself based on previously processed data. These algorithms provide efficient supervised and unsupervised learning of these collected data, which effectively implements VANET’s objective. We highlighted the safety, communication, and traffic-related issues in VANET systems and their implementation in-feasibility and explored how machine learning algorithms can overcome these issues. Finally, we discussed future direction and challenges, along with a case study depicting a VANET based scenario.

47 citations


Journal ArticleDOI
TL;DR: In this paper, the authors proposed a secure and intelligent sensing and tracking architecture for AV system using beyond 5G communication network using Blockchain (BC) technology, which is evaluated by considering the parameters as mobility and data transfer time against the traditional LTE-A and 5G communications networks.
Abstract: For the past few years, the automation of transportation becomes a hot research topic for smart cities. Intelligent Transportation System (ITS) aims to manage and optimize the traffic congestion, road accidents, parking allocation using Autonomous Vehicles (AV) system, where the AVs are internally connected for message passing and critical decision making in time-sensitive applications. The data security in such applications can be offered using Blockchain (BC) technology. But, as per the existing literature, there exists no system which can call AVs automatically based on the situation, i.e., call an ambulance in case of an accident, call logistic service in case of home transfer, and call the traffic department in case of traffic jam. Motivated from the aforementioned reasons, in this article, we propose a BC-based secure and intelligent sensing and tracking architecture for AV system using beyond 5G communication network. Recently, AVs are facing issues with sensing and tracking technology as well as the data thefts. AV system contains sensitive information and transfers it through a communication channel to Connected AVs (CAVs), where the corrupted information or delay of a fraction of a second can lead to a critical situation. So, here we present possib the attacks and safety countermeasures using BC technology to protect the AV system. The proposed architecture ensures secure sensing and tracking of an object through BC by deploying AI algorithms at the edge servers. Also, the beyond 5G network enables communications with low latency and high reliability to meet the desires of the aforementioned time-sensitive applications. The proposed system is evaluated by considering the parameters as mobility and data transfer time against the traditional LTE-A and 5G communication networks. The proposed system outperforms traditional systems and can be suitable for diverse applications where latency, reliability, and security are the prime concerns.

41 citations


Journal ArticleDOI
TL;DR: The security analysis proved that the proposed protocol is secured against well-known attacks and also it provides better performance as well as additional features when compared to existing protocols.
Abstract: Due to the advancement of wireless technology, the Internet of Things (IoT) Device to Device communication for exchanging messages is feasible without human involvement. Authentication and identification of device location are highly essential tasks to verify the originality of IoT Devices (IoTDs) during communication via open channel. In recent days, IoTD registration is processed through the Registration Center Authority (RAC) and this may face single point of failure and insider attack. To solve these problems, we propose a Blockchain based Internet of Things (IoT) Device to Device Authentication Protocol for Smart City Applications using 5G Technology (BIDAPSCA5G). In the proposed protocol, the IoT Devices registration process is performed through private blockchain. The Blockchain has the Distributed Ledger (DL) for storing IoTD credential details, which is accessed only by authenticated entities. In the proposed protocol, mutual authentication was performed without involvement of RAC/Gate-Way-Node (GWN) to reduce the computation cost. The proposed protocol has the additional features such as location based authentication, blockchain based revocation phase and registration of IoTDs, IoTD anonymity property at device level. The security analysis of the proposed protocol was performed through formal security verification using Proverif tool, formal security analysis using Random Oracle Model (RoM) and informal security analysis. The security analysis proved that the proposed protocol is secured against well-known attacks and also it provides better performance as well as additional features when compared to existing protocols.

40 citations


Journal ArticleDOI
TL;DR: In this paper, the authors presented two schedulers based on integer linear programming (ILP) that schedule tasks either in the cloud or on fog resources, which differ from existing ones by the use of class of services to select the processing elements on which the tasks should be executed.
Abstract: Fog computing extends cloud services to the edge of the network In such scenario, it is necessary to decide where applications should be executed so that their quality of service requirements can be supported Thus, a cloud-fog system requires an efficient task scheduler to decide the locality where applications should run This paper presents two schedulers based on integer linear programming, that schedule tasks either in the cloud or on fog resources The schedulers differ from existing ones by the use of class of services to select the processing elements on which the tasks should be executed Numerical results evince that the proposed schedulers outperform traditional ones, eg, Random and Round Robin algorithms without causing violation of QoS requirements

40 citations


Journal ArticleDOI
TL;DR: Various resource allocation algorithms and methodologies have been seriously analysed and evaluated based on the degree of involvement of the Base Station to figure out the research gap and to provide a strong theoretical basis for the research problems related to resource allocation in D2D communication.
Abstract: Device to Device communication is an important aspect of the fifth-generation(5G) and beyond fifth-generation (B5G) wireless networks. 5G facilitates network connectivity among a large number of devices. This tremendous growth in the number of devices requires a large number of spectrum resources to support a variety of applications and also lays a huge burden on the Base Station. D2D skips the need to forward the data to the Base Station and helps the devices to take part in direct Peer-to-Peer (P2P) transmission. This enables high-speed data transmission, efficient information transmission with improved latency and most importantly is used to offload the traffic that is laid on the Base Station. D2D has many practical issues and challenges that are briefly explained in this paper, out of which resource allocation is the main area of focus as it plays an important role in the performance of the system. The optimal allocation of resources such as power, time and spectrum can improve the system performance. Therefore, in order to identify the open research issues in the field of resource allocation in D2D communication, a detailed survey is needed. In this paper, various resource allocation algorithms and methodologies have been seriously analysed and evaluated based on the degree of involvement of the Base Station to figure out the research gap and to provide a strong theoretical basis for the research problems related to resource allocation in D2D communication.

Journal ArticleDOI
TL;DR: In this article, a secure data aggregation scheme has been proposed, which has three phases: intra-cluster data aggregation, inter-clusters data aggregation and data transfer, and a fuzzy scheduling system is designed to adjust the appropriate data transmission rates of the cluster member nodes.
Abstract: A wireless sensor network (WSN) consists of a set of sensor nodes that are widely scattered in inaccessible areas When deployed in large areas, WSNs generate a large volume of the data Therefore, efficient methods are needed to process the data One solution to minimize traffic on large-scale wireless sensor networks is to use data aggregation schemes In this paper, a secure data aggregation method is proposed The proposed secure data aggregation scheme has three phases: intra-cluster data aggregation, inter-cluster data aggregation, and data transfer In the intra-cluster data aggregation phase, a fuzzy scheduling system is designed to adjust the appropriate data transmission rates of the cluster member nodes In the inter-cluster data aggregation phase, an aggregation tree is created between the cluster head nodes The dragonfly algorithm (DA) is used to find the optimal aggregation tree between cluster head nodes In the data transfer phase, the columnar transposition cipher method is used to establish a secure connection between cluster member nodes and their cluster head node Also, a symmetric and lightweight encryption method based on the residue number system (RNS) is utilized to provide secure communications between the cluster head nodes We modify RNS and call it RNS+ Finally, the simulation results of the proposed scheme are compared to three data aggregation methods including Sign-share, Sham-share, and RCDA The results show that the proposed data aggregation scheme outperforms other data aggregation methods in terms of network lifetime, delay and packet delivery rate

Journal ArticleDOI
TL;DR: The results of the simulation reveal that the proposed multipath routing outperforms other routing methods in end-to-end delay, energy consumption, packet loss rate, and network lifetime.
Abstract: Routing is one of the major challenges in wireless sensor networks (WSNs). Unbalanced energy consumption in the routing process of data packets is one of the main issues in WSNs. The issue needs consideration, because the energy level of sensor nodes is limited. Multipath routing methods reduce energy consumption, improve scalability and provide load balancing in WSNs. In this study, we suggested a multipath routing method for homogeneous WSNs. The proposed method includes 3 phases: clustering the network nodes, discovering the paths between CHs, and maintaining the paths. In the first phase, wireless sensor network is clustered through the firefly algorithm. In the second phase, routing is performed between CHs based on the fuzzy logic. Routing between CHs results in creating 2 paths: primary path and backup path. CHs transmit data packets to the base station through the primary paths; however, failures in primary paths cause CHs to employ backup paths. In the third phase, the paths are maintained so that path breakages cause to restart route discovery. The results of the simulation reveal that the proposed multipath routing outperforms other routing methods in end-to-end delay, energy consumption, packet loss rate, and network lifetime.

Journal ArticleDOI
TL;DR: This paper employs a multi-criteria decision-making (MCDM) approach to rank and outline the suitable public blockchain platforms and presents ECWM, a new weight assignment technique, which is a combination of Entropy and CRITIC method.
Abstract: Public blockchain enables decentralized trust models in distributed systems. The programmable features such as smart contracts and decentralized applications are attracting application developers, systems integrators, and users to adopt public blockchain systems for a large plethora of applications across all industries. However, the abundance and variety of features in immature blockchain ecosystems make it hard to select an appropriate and useful public blockchain platform. This paper employs a multi-criteria decision-making (MCDM) approach to rank and outline the suitable public blockchain platforms. To this end, we present ECWM, a new weight assignment technique, which is a combination of Entropy and CRITIC method. We applied ECWM on a diverse dataset curated with 16 features (i.e., indicators representing different criteria for blockchain adoption) from 30 public blockchain systems. We apply three MCDM techniques, namely WSM, TOPSIS, and VIKOR, to generate ranks. These techniques produce divergent rankings; therefore, we use Spearman’s rank correlation coefficient to resolve disagreements and outline the best possible ranking with the given dataset. We also rank blockchains according to three categories: popularity, sustainability, and profitability. The ranks are meticulously evaluated by domain experts and are deemed quite effective to guide future researchers and system developers.

Journal ArticleDOI
TL;DR: This research paper proposes a protocol to overcome security-based issues and shows that secure data transfer can be performed in an efficient way for online e-voting applications.
Abstract: Most of the various sectors in today’s life such as bank, transport, voting, health, electricity, etc., are currently digitalized. In our research paper, we have surveyed the voting system and explored the existing drawbacks of the voting system concerning security and malfunction. The demerits in the existing schemes include less data security, vote modification, man in the middle attack, masquerade attack, denial of service attack, impersonation attack, etc. Such attacks can compromise security and allows attackers to modify the results. To resolve the above-mentioned issues as well as the attacks, this research paper proposes a protocol to overcome security-based issues. In the proposed system, a secure online e-voting system is developed for end-to-end users to avoid misappropriation on the vote during the result publication in India or any other country. The proposed E-Voting Cloud System (ECS) system has three phases: The first phase is the registration phase, the second phase is vote polling, and the third phase is result announcements. In the proposed system, the election commission of India can search and verify the vote data through cloud computing. For a detailed description of our proposed protocol, a cube data storage structure and user differentiated system are first implemented. Based on the cube data structure and user differentiated system model, the proposed protocol helps to store voter data in the cloud with the encrypted model and ECS. Finally, the candidate can decrypt the data using their key. The people can verify the result announced by the ECS. The performance analysis clearly shows that our proposed system is highly secure when compared to the existing system. Using the proposed work, secure data transfer can be performed in an efficient way for online e-voting applications.

Journal ArticleDOI
TL;DR: In this article, the authors proposed a robust and lightweight, secure access scheme for cloud-based E-healthcare services by providing a secure interface to stakeholders and prohibiting unauthorized users from accessing information stored in the cloud.
Abstract: Traditional healthcare services have transitioned into modern healthcare services where doctors remotely diagnose the patients. Cloud computing plays a significant role in this change by providing easy access to patients’ medical records to all stakeholders, such as doctors, nurses, patients, life insurance agents, etc. Cloud services are scalable, cost-effective, and offer a broad range of mobile access to patients’ electronic health record (EHR). Despite the cloud’s enormous benefits like real-time data access, patients’ EHR security and privacy are major concerns. Since the information about patients’ health is highly sensitive and crucial, sharing it over the unsecured wireless medium brings many security challenges such as eavesdropping, modifications, etc. Considering the security needs of remote healthcare, this paper proposes a robust and lightweight, secure access scheme for cloud-based E-healthcare services. The proposed scheme addresses the potential threats to E-healthcare by providing a secure interface to stakeholders and prohibiting unauthorized users from accessing information stored in the cloud. The scheme makes use of multiple keys formed through the key derivation function (KDF) to ensure end-to-end ciphering of information for preventing misuse. The rights to access the cloud services are provided based on the identity and the association between stakeholders, thus ensuring privacy. Due to its simplicity and robustness, the proposed scheme is the best fit for protecting data security and privacy in cloud-based E-healthcare services.

Journal ArticleDOI
TL;DR: In this article, the authors proposed an algorithm named Energy-efficient Cluster-based Routing Protocol using Unequal Clustering and improved Ant Colony Optimization (ACO) techniques (ECRP-UCA).
Abstract: Routing and hotspot are considered among the key issues in Wireless Sensor Networks (WSNs). Several routing protocols have been proposed; yet they suffer from the lack of fault tolerance, the uneven load balancing and the local optimal solution issues. To fix these issues, we propose in this paper an algorithm named Energy-efficient Cluster-based Routing Protocol using Unequal Clustering and improved Ant Colony Optimization (ACO) techniques (ECRP-UCA). ECRP-UCA divides the network into unequal clusters based on residual energy, distance to the sink, number of neighbor nodes, and a new parameter named number of backward relay nodes in previous round to properly balance the load among Cluster Heads (CHs). We propose also a batch-based clustering method that allows the network to function several rounds without requiring control overhead for its configuration. Additionally, we devise an improved ACO based routing technique for efficient and reliable inter-cluster routing from CHs to the sink. In this algorithm, the heuristic function is formulated considering the energy of next hop sensor node, distance from the current sensor node to the next sensor node and the latter to the destination, and the new parameter Number of Preferred Probable Relay Nodes (NPPRN). By using NPPRN, the ants have the probability to follow other paths, which improves the algorithm’s ability to obtain the optimal global solution and protect the algorithm from converging quickly into the optimal local solution. Moreover, the ant searching direction is improved. The proposed routing protocol is intensively experimented and compared with recent and relevant existing protocols. The simulation results show that the proposed ECRP-UCA outperforms these protocols in terms of various interesting metrics.

Journal ArticleDOI
TL;DR: This paper introduces message dissemination with re-route planning (MDRP) method, which initiates a dissemination boundary for selecting neighbors and weight for selecting the re-routing path based on the traffic conditions of the road segment.
Abstract: Emergency vehicles (EVs) are significant in disseminating sensitive information across the road-side communication networks. This amalgamation of vehicles and communication networks improves the reachability and accessibility of sensitive data along the driving scenario. However, the communication network experiences data and traffic congestion due to wireless medium and varying vehicle densities. In order to address the problem of data and traffic congestion, this paper introduces message dissemination with re-route planning (MDRP) method. This method initiates a dissemination boundary for selecting neighbors and weight for selecting the re-routing path. The weight is based on the traffic conditions of the road segment along with consideration of the timeout of the EV message. The joint process of rerouting and data transmission is supported by dependent queue management for improving the message delivery and reducing the impact of delaying instances in the travelling path.

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper proposed an Automated Separated-Federated Graph Neural Network (ASFGNN) learning paradigm, which decouples the training of GNN into two parts: the message passing part that is done by clients separately, and the loss computing part that are learnt by clients jointly.
Abstract: Graph Neural Networks (GNNs) have achieved remarkable performance by taking advantage of graph data The success of GNN models always depends on rich features and adjacent relationships However, in practice, such data are usually isolated by different data owners (clients) and thus are likely to be Non-Independent and Identically Distributed (Non-IID) Meanwhile, considering the limited network status of data owners, hyper-parameters optimization for collaborative learning approaches is time-consuming in data isolation scenarios To address these problems, we propose an Automated Separated-Federated Graph Neural Network (ASFGNN) learning paradigm ASFGNN consists of two main components, ie, the training of GNN and the tuning of hyper-parameters Specifically, to solve the data Non-IID problem, we first propose a separated-federated GNN learning model, which decouples the training of GNN into two parts: the message passing part that is done by clients separately, and the loss computing part that is learnt by clients federally To handle the time-consuming parameter tuning problem, we leverage Bayesian optimization technique to automatically tune the hyper-parameters of all the clients We conduct experiments on benchmark datasets and the results demonstrate that ASFGNN significantly outperforms the naive federated GNN, in terms of both accuracy and parameter-tuning efficiency

Journal ArticleDOI
TL;DR: In this article, a reliable tree-based data aggregation method is proposed, where sensor nodes are organized in the form of a binary tree and aggregation requests are authenticated by a shared key, and if the request is acknowledged, the aggregation process begins.
Abstract: Aggregating the sensed data by nodes is a natural way to increase the network lifetime and reduce the number of bits sent and received by each sensor node. This paper presents a reliable tree-based data aggregation method. In the proposed method, sensor nodes are organized in the form of a binary tree. Then, aggregation requests are authenticated by a shared key, and if the request is acknowledged, the aggregation process begins. In the proposed method, using dynamic generator polynomial-size for cycle error detection code (CRC), the error generated along the path is detected hop by hop. In case of an error, the request for retransmission will be sent to the previous hop. Also, intermediate nodes apply certain aggregating functions like summation or averaging on the received packages, which cause a reduction in the amount of data transmission on the network. This method reduces the number of sent packets and the amount of energy consumed, so the network has a longer lifetime. Also, this method significantly increased reliability using the CRC code. The proposed method is compared with EESSDA, SDAACA, and LAG methods. The simulation results show that the proposed method has greater superiority over its comparative techniques, particularly on aspects such as energy consumption, network lifetime, and reliability.

Journal ArticleDOI
TL;DR: In this article, a resource optimization scheme for efficient cellular device association and optimal power control in NOMA-enabled HetNets is proposed to maximize the energy efficiency while guaranteeing the signal decoding and minimum rate of each cellular device.
Abstract: Non-orthogonal multiple access (NOMA) is expected to play a critical role in heterogeneous networks (HetNets) for beyond fifth-generation (5G) wireless systems. The unrivaled benefits of NOMA along with the multi-tier architecture of HetNets has the potential to significantly improve the performance of cellular networks. Motivated by such possibilities, this article provides a new resource optimization scheme for efficient cellular device association and optimal power control in NOMA-enabled HetNets. Our objective is to maximize the energy efficiency of the proposed HetNets while guaranteeing the signal decoding and minimum rate of each cellular device. The problem of cellular device association and power control is jointly formulated as a non-convex optimization. Since the problem of energy efficiency is coupled with both devise association and power control, it contains high complexity and, hence, it is very difficult to obtain the joint solution. To obtain an efficient solution and reduce the complexity, we decouple the original problem into two subproblems for efficient device association and optimal power control. For any given power allocation of base stations (BSs), we first adopt dual theory for cellular device association, and then a new sequential quadratic programming (SQP) is employed to calculate the optimal power control. Later, we also present the benchmark suboptimal power control method which is based on Karush-Kuhn-Tucker conditions. Monte Carlo simulation results unveil that the proposed NOMA resource optimization scheme in HetNets can significantly improve the system performance compared to the benchmark NOMA and orthogonal multiple access (OMA) schemes.

Journal ArticleDOI
TL;DR: A distributed media transaction framework for DRM is proposed, which is based on the digital watermarking and a scalable blockchain model, which allows only authorized users to use online content and provide original multimedia content.
Abstract: Even though the Internet promotes data sharing and transparency, however it does not protect digital content. In today’s digital world, it has become a difficult task to release a DRM (Digital Rights Management) system that can be considered well-protected. Digital content that becomes easily available in open-source environments will in time be worthless to the creator. There may only be a one-time payment to creators upon initial upload to a given platform after which time the rights of the intellectual property are shifted to the platform itself. However, due to the online availability of content, anyone can download content and make copies. The value of digital content slowly decreases, because the value of content can usually be determined through the difficulty of it’s accessibility. There is no way to track the leakage or copyright for the spread of digital material. In this paper, a distributed media transaction framework for DRM is proposed, which is based on the digital watermarking and a scalable blockchain model. In this paper, our focus is on improving the classic blockchain systems to make it suitable for a DRM model. The DRM model in this paper allows only authorized users to use online content and provide original multimedia content. While the digital watermarking is used to reclaim the copyright ownership of offline contents in the event when the contents are leaked.

Journal ArticleDOI
TL;DR: A novel access control model that maintains a temporary table based on the data type and popularity value of the Data Owner for fast and efficient data accessing and proves its efficiency over the existing schemes.
Abstract: With the rapid advancement of emerging technologies, a huge amount of data is created and processed in daily life. Nowadays, Cloud Computing (CC) technology is one of the frequently adopted technologies to access and store data over the internet. CC mainly provides on-demand and pay-per-use services to users. However, access control and security are two major issues that users face in a cloud environment. During data access from a cloud server, the searching time of a Data Owner (DO) and the data accessing time are high. Therefore, users utilize more cloud services and pay more. High system overhead is another issue of a cloud environment. In this paper, a novel access control model has been proposed to overcome all these concerns. Here, the Cloud Service Provider (CSP) maintains a temporary table based on the data type and popularity value of the DO for fast and efficient data accessing. The cloud service provider can easily search the data owner by using the table and the data accessing time is remarkably reduced. Experimental results and theoretical analysis of the proposed scheme prove its efficiency over the existing schemes.

Journal ArticleDOI
TL;DR: An effective data transmission scheme in opportunistic social networks, that is, A source node Centrality and community Restructuring based Hybrid Routing (CRHR) algorithm that can significantly improve the data transmission rate and efficiency is proposed.
Abstract: With the advent of 5G era and the development of personal mobile devices, people’s demand for information and bandwidth is growing exponentially. In the traditional social network and its routing algorithm, there are only a few fixed source nodes and transmission mode. The huge amount of data may lead to delay and loss of data transmission and even the collapse of the source node. In order to solve this problem, this paper proposes an effective data transmission scheme in opportunistic social networks, that is, A source node Centrality and community Restructuring based Hybrid Routing (CRHR) algorithm. The algorithm consists of two parts. In the first part, we measure the centrality of the source node by calculating the critical path where the node is located, and iterate to get the optimal source node and its corresponding relay node. In the second part, we will expand the Opportunity Social Network and rebuild the extended community with the Steiner Minimum Tree to minimize the cost of community data transmission. The simulation results show that the algorithm has lower data transmission delay and cost than other algorithms, and can significantly improve the data transmission rate and efficiency.

Journal ArticleDOI
TL;DR: A smart card based secure addressing and authentication (SCSAA) scheme by modifying the standard IPv6 protocol to mitigate the security threats in the IoT network is proposed.
Abstract: The edge-based Internet of Things (IoT) computing provides a new value for the consumer where the smart devices, objects, and appliances connected over the internet. The data generated from the smart IoT devices need to be securely processed. With the increasing rate of smart IoT devices, the existing addressing schemes and security protocols do not guaranty to perform well in all situations. This paper proposed a smart card based secure addressing and authentication (SCSAA) scheme by modifying the standard IPv6 protocol to mitigate the security threats in the IoT network. The proposed scheme has two folds; firstly, this scheme provides a unique way of addressing by assigning unique 64-bit interface identifier (IID) to smart devices/appliances and uniquely authenticates them in IoT network. Secondly, this scheme uses the secret session key to prevent the network from unauthorized access. Additionally, this work also evaluates the informal security analysis, formal security analysis using ROR model and AVISPA tool. The overall security analysis proves that proposed scheme protect the smart home IoT network from various vulnerabilities and attacks.

Journal ArticleDOI
TL;DR: A new vehicle edge computing framework is proposed, which introduces the reputation to measure the contribution of each vehicle as the basis for providing different quality of services, and proves the existence and uniqueness of Stackelberg equilibrium in two-stage game.
Abstract: Service caching can improve the QoS of computationally intensive vehicle applications by pre-storing the necessary application programs and related data for computing tasks on edge servers. In this paper, we propose a new vehicle edge computing framework based on software defined networks, which introduces the reputation to measure the contribution of each vehicle as the basis for providing different quality of services. The process is divided into two phases: in the first phase, the vehicle requests the offload application task from the edge server; and in the second phase, the edge server makes the service caching decision after processing the task. We design the whole interaction process as a kind of incentive mechanism based on reputation via using Stackelberg game modeling, and analyze the optimal strategy for both sides of the game by reverse induction. Furthermore, we also prove the existence and uniqueness of Stackelberg equilibrium in two-stage game, and a genetic optimization algorithm is designed to quickly obtain the optimal strategy for both sides of the game. Experimental results show that the proposed scheme not only brings more profits to the edge server side, but also reduces the average delay by 76 % compared with the ordinary mobile edge computing scheme.

Journal ArticleDOI
TL;DR: A reliable scheduling approach for allocating customers’ requests to the resources of Cloud-Fog environments is introduced, called Load Balanced Service Scheduling Approach (LBSSA), which considers load balancing among resources when assigning requests to them by classifying requests to real-time, important and time-tolerant.
Abstract: Fog computing broadens the computing services to serve requests of Internet of Things (IoT) by resources at the edge of Cloud-Fog environments instead of serving these requests by resources at the environment’s core The aim of fog computing is to reduce load of computing in data centers and reduce latency of requests, especially real-time ones Load balancing and scheduling play essential roles and represent main key challenges to guarantee high throughput and reliability of services in Cloud-Fog environments Therefore, this paper introduces a reliable scheduling approach for allocating customers’ requests to the resources of Cloud-Fog environments The approach is called Load Balanced Service Scheduling Approach (LBSSA) and it considers load balancing among resources when assigning requests to them by classifying requests to real-time, important and time-tolerant In addition, scheduling of requests in the proposed approach considers the failure rate of resources in order to provide high reliability for requested services The approach has a set of algorithms for handling different types of requests Simulation experiments using CloudSim are conducted to assess the LBSSA approach in terms of number of computing resources, utilization of resources, load balance variance and running time

Journal ArticleDOI
TL;DR: It was discovered that basic escape clauses in blockchain can be beaten utilizing the prototyped structure and protected keen agreements dependent on ERC20 interface of controlled Ethereum based Distributed Ledger Technology with significant cycles and capacities to get an all encompassing structure for making sure about Cloud-Based Manufacturing activities.
Abstract: Past local and worldwide international logistic operations have been related with obscure data streams that have thwarted detectability and made obstacles in deregulation. Ethereum based Distributed Ledger Technology and unified advancements were explored for solving the issues looked of Cloud-Based Manufacturers. Nonetheless, past writing has zeroed in on restricted parts of a regular Cloud-Based Manufacturing chain, for example, checking resources and making sure about discernibility, which is generally dismissing information trustworthiness and information access. To conquer such disadvantages, the current study attempts to protected keen agreements dependent on ERC20 interface of controlled Ethereum based Distributed Ledger Technology with significant cycles and capacities to get an all encompassing structure for making sure about Cloud-Based Manufacturing activities. The adequacy was exhibited on the study. So, it was discovered that basic escape clauses in blockchain can be beaten utilizing the prototyped structure. Also, a few blueprints for future examination are plot.

Journal ArticleDOI
TL;DR: In this paper, the authors analyze the fundamental concepts of FHE, practical implementations, state-of-the-art approaches, limitations, advantages, disadvantages, potential applications, and development tools focusing on neural networks.
Abstract: Classical machine learning modeling demands considerable computing power for internal calculations and training with big data in a reasonable amount of time. In recent years, clouds provide services to facilitate this process, but it introduces new security threats of data breaches. Modern encryption techniques ensure security and are considered as the best option to protect stored data and data in transit from an unauthorized third-party. However, a decryption process is necessary when the data must be processed or analyzed, falling into the initial problem of data vulnerability. Fully Homomorphic Encryption (FHE) is considered the holy grail of cryptography. It allows a non-trustworthy third-party resource to process encrypted information without disclosing confidential data. In this paper, we analyze the fundamental concepts of FHE, practical implementations, state-of-the-art approaches, limitations, advantages, disadvantages, potential applications, and development tools focusing on neural networks. In recent years, FHE development demonstrates remarkable progress. However, current literature in the homomorphic neural networks is almost exclusively addressed by practitioners looking for suitable implementations. It still lacks comprehensive and more thorough reviews. We focus on the privacy-preserving homomorphic encryption cryptosystems targeted at neural networks identifying current solutions, open issues, challenges, opportunities, and potential research directions.

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a novel privacy-preserving data collection scheme for IoT based healthcare services systems using a clustering-based anonymity model to develop an efficient privacypreserving scheme to meet privacy requirements and prevent healthcare IoT from various privacy attacks.
Abstract: The healthcare services industry has seen a huge transformation since the prominent rise of the Internet of Things (IoT). IoT in healthcare services includes a large number of unified and interconnected sensors, and medical devices that generate and exchange sensitive information. Thus, an enormous amount of data is transmitted through the network which raises an alarming concern for the privacy of patient information. Therefore, privacy preserving data collection (PPDC) is on-demand to ensure the privacy of patient data. Several pieces of research on PPDC have been proposed recently. However, the research literatures have fallen short in privacy requirements and are prone to various privacy attacks. In this paper, we propose a novel privacy-preserving data collection scheme for IoT based healthcare services systems. A clustering-based anonymity model is utilized to develop an efficient privacy-preserving scheme to meet privacy requirements and to prevent healthcare IoT from various privacy attacks. We formulated the threat model as client-server-to-user to ensure privacy on both ends. On the client-side, a modified clustering-based k-anonymity model with α-deassociation is used to anonymize the data generated from the IoT nodes. The base-level privacy is then ensured through a bottom-up clustering method which generates clusters of records as per the privacy requirements. On the server-side, the cluster-combination method-UPGMA is utilized to reduce communication costs and to achieve a better level of privacy. The proposed scheme is efficient in tackling privacy attacks such as attribute disclosure, identity disclosure, membership disclosure, sensitivity attacks, similarity attacks, and skewness attacks. The effectiveness and efficiency of the proposed scheme are proven through theoretical and experimental analyses.