Scheme For Wireless Sensor Networks Research Articles

An Improved and Secured 3-Factor Authentication Scheme for WSN in IoT Based Applications

Wireless Sensor Networks (WSN) has top-notch capacity for numerous domains of utility due to the potential to sense and apprehend unattended environments. IoT is playing an increasingly more essential position in clever healthcare, smart transportation and elegant grid using WSN. Therefore, challenges like privacy and data security associated with IoT wireless sensor networks because of sensor node being captured easily, consume less computing energy and low storage. Designing a secure authentication scheme will enable secure communication in WSN. Here, we proposed a improved three-factor authentication scheme for WSN utilizing biometric, password and smart card withstand against security attacks. Subsequently, by comparing the security, functional and performance parameters of our proposed scheme to the other schemes, our scheme provides better and efficient one. Therefore, our scheme is fairly workout in real time IoT applications involved in WSN scenario.

Understanding the security failures of four user authentication schemes for wireless sensor networks in IoT environment

User authentication protocols are applied to provide a secure conversation between participating entities in wireless sensor networks (WSNs). To identify how to ensure security in these schemes, it is imperative to look into the security vulnerabilities of these authentication mechanisms. As a part of this study, we examine the security of four 2-factor authentication schemes for WSNs (namely, Zhang and Wen, Jangirala et al., Maurya and Sastry and Singh et al.). Security verification result shows that they are all confronted by serious security weaknesses (like sensor node capture attack, exposer of session key by gateway node attack, smart card lost attack, malicious gateway node attack, and session-specific ephemeral information loss attack) and lack of important security functionalities (like multi-factor security, perfect forward secrecy, user anonymity and untraceability, and session key security). This research concentrates on the ‘root cause of the problem. This will help in the research and development of reliable and efficient user authentication mechanisms for WSNs. Our research results point out some new challenges in building reliable multi-factor mechanisms of user authentication for WSNs. We additionally identify some significant insights from the cryptanalysis results of these mechanisms.

Analysis on the Improvement of Energy Efficiency by using its Models in Wireless Sensor Networks

Aims and Background: A self-configured and infrastructure-less wireless network is named as a wireless sensor network (WSN), which has the role of monitoring physical or environmental conditions like sound, motion, temperature, vibration, and pollutants for passing their data throughout the network to a center of location where the data could be easily observed as well as analyzed. Methodology: In WSN, the small-sized sensor node is working with a very small battery with limited energy. Replacing the battery or recharging the battery is not feasible, and so, the energyefficient operation of WSN is the key factor. While designing routing protocols (RPs) for WSNs, one among the significant goals is energy conservation owing to this lower power. Totally, three models, namely, state, cluster, and content, were utilized for enhancing energy efficiency (EE). Each protocol has its own way of routing that varies from the other in terms of the parameters selected or the approach. Results: This paper explicates a survey on WSNs, upgrading EE in WSN based on the state model, EE improvement in WSN based on the cluster model, and EE enhancement in WSN using a contentbased model with its performance comparison. Conclusion: This paper evaluates the number of cluster heads (CHs) of CADS in different nodes with different schemes for WSNs and a comparison of the four schemes in WSNs.

Mobility target tracking with meta‐heuristic aided target movement prediction scheme in WSN using adaptive distributed extended Kalman filtering

SummaryIn wireless sensor networks (WSNs), target tracking has been prominently raised in recent days. Because of the frequent utilization of WSN, the attention on target tracking is greatly increased. The estimated optimal value derived from the earlier moment is rarely taken into consideration in traditional target‐tracking algorithms. One of the most crucial uses of WSNs is mobile target tracking, and it is especially used for spying. Precision surveillance is heavily dependent on localization or distance estimation, and extensive study has been done in this area. This research aims to develop a new target‐tracking network‐assisted target movement prediction model in WSN with reduced energy consumption. The major phases involved in the proposed target movement prediction in WSN are (a) mobility target tracking and (b) target movement prediction. Initially, the mobility target tracking is done with the help of adaptive distributed extended Kalman filtering (ADEKF). The mobility target tracking performance is improved by optimally tuning the parameters from ADEKF with the support of the improved squid game optimizer (ISGO). Then, the target movement prediction phase is executed with the help of input parameters like “Angle of Arrival (AoA) and Received Signal Strength (RSS),” and the optimal progress of the mobile node is predicted. The implementation outcome of the proposed tracking network‐assisted target movement prediction model is validated concerning various performance metrics. Overall performance analysis shows that the developed model offers 2.5% in terms of RMSE measures. The developed model shows better analysis while validating with existing approaches.

An Enhanced Mechanism for Fault Tolerance in Agricultural Wireless Sensor Networks

Fault tolerance is a critical aspect for any wireless sensor network (WSN), which can be defined in plain terms as the quality of being dependable or performing consistently well. In other words, it may be described as the effectiveness of fault tolerance in the event of crucial component failures in the network. As a WSN is composed of sensors with constrained energy resources, network disconnections and faults may occur because of a power failure or exhaustion of the battery. When such a network is used for precision agriculture, which needs periodic and timely readings from the agricultural field, necessary measures are needed to handle the effects of such faults in the network. As climate change is affecting many parts of the globe, WSN-based precision agriculture could provide timely and early warnings to the farmers about unpredictable weather events and they could take the necessary measures to save their crops or to lessen the potential damage. Considering this as a critical application area, in this paper, we propose a fault-tolerant scheme for WSNs deployed for precision agriculture. Along with the description of our mechanism, we provide a theoretical operational model, simulation, analysis, and a formal verification using the UPPAAL model checker.

Physical‐layer security enhancement in wireless sensor networks through artificial noise optimization

AbstractEnsuring network security is of utmost importance, especially in wireless sensor networks (WSNs), where the confidentiality of data is at risk due to eavesdropping. This paper introduces an artificial‐noise‐aided secure communication scheme for WSNs. This scheme comprises numerous sensor nodes, the sink, a friendly jammer, and an eavesdropper. The primary aim is to enhance the secrecy rate of the network by optimizing the jamming power. The friendly jammer plays a crucial role in degrading the wiretap channel between the sensor nodes and the eavesdropper. The optimization process revolves around maximizing the secrecy rate, while carefully managing the jamming power to prevent any negative impact on the main transmission link between the sink node and the sensor nodes. Due to the nonconvexity of the secrecy rate problem, the convex approximation‐based algorithm is recommened to get a safe convex approximation of the original solution. To address this optimization problem, an iterative algorithm based on quadratic transformation is proposed. Afterwards, the optimum jamming power to achieve high security is obtained. The simulation outcomes underscore the dual impact of the jammer in WSNs. The jammer diminishes the eavesdropper channel. Unfortunately, it introduces interference that consequently affects the security enhancement. In response, we concentrate on the optimization of jamming power. The proposed scheme consistently elevates secrecy rates across a spectrum of eavesdropper positions, adeptly addressing worst‐case scenarios. Notably, the algorithm showcases resilience across diverse node distributions.

An Intelligent Energy-Efficient Data Routing Scheme for Wireless Sensor Networks Utilizing Mobile Sink

Data collection and energy consumption are critical concerns in Wireless sensor networks (WSNs). To address these issues, both clustering and routing algorithms are utilized. Therefore, this paper proposes an intelligent energy-efficient data routing scheme for WSNs utilizing a mobile sink (MS) to save energy and prolong network lifetime. The proposed scheme operates in two major modes: configure and operational modes. During the configure mode, a novel clustering mechanism is applied once, and a prescheduling cluster head (CH) selection is introduced to ensure uniform energy expenditure among sensor nodes (SNs). The scheduling technique selects successive CHs for each cluster throughout the WSNs’ lifetime rounds, managed at the base station (BS) to minimize SN energy consumption. In the operational mode, two main objectives are achieved: sensing and gathering data by each CH with minimal message overhead, and establishing an optimal path for the MS using the genetic algorithm. Finally, the MS uploads the gathered data to the BS. Extensive simulations are conducted to verify the efficiency of the proposed scheme in terms of stability period, network lifetime, average energy consumption, data transmission latency, message overhead, and throughput. The results demonstrate that the proposed scheme outperforms the most recent state-of-the-art methods significantly. The results are substantiated through statistical validation via hypothesis testing utilizing ANOVA, as well as post hoc analysis.

Block chain technology for secured dynamic optimal routing in WSN with optimized generative adversarial capsule network

SummaryOne of the key strategies in wireless sensor network (WSN) for sending data packets to the base station (BC) is known as routing. However, malicious node outbreaks will occur, which exaggerate the functions of WSNs during the routing procedure. A secure routing protocol is necessary to protect the effectiveness of WSN and routing fortification. In real‐time scenarios, the existing routing protocol is volatile dynamically; it makes difficult to identify the performance of unprotected routing nodes. In this manuscript, a unique routing strategy is proposed for secured dynamic optimal routing (SDOR) in WSN that combines block chain technology optimized with a generative adversarial capsule network. Every routing sensor node contains a secret key, which is used to construct a crypto hash signature (CHS) token for flow access. The proposed block chain‐based WSN is used to provide SDOR information using a self‐attention‐based generative adversarial capsule network that is improved using the flamingo search algorithm. Following that, the security on the proposed block chain WSN is assessed from six angles. Block chain token transactions are evaluated using measures including average latency, average energy usage, and throughput. The proposed SDOR‐SA‐GAC‐FSA‐CHS‐BWSN delivers 53.87%, 42.57%, and 32.87% lower average packet delay, 28.97%, 37.73%, and 34.75% lesser identification time analyzed to the existing methods, such as trusted distributed routing scheme for WSNs using block chain (SDOR‐DCNN‐SSOA‐BWSN), secure authentication with DSM‐KL ascertained presentation optimization of hybrid block chain‐enabled model for multi‐WSN (SDOR‐DSM‐KL‐BWSN), and optimizing the valid transaction utilizing reinforcement learning‐based block chain ecosystem in WSN (SDOR‐RIL‐BWSN).

ECC-based three-factor authentication and key agreement scheme for wireless sensor networks

In wireless sensor networks (WSNs), protocols with authentication and key agreement functions can enhance the security of the interaction between users and sensor nodes, guaranteeing the security of user access and sensor node information. Existing schemes have various security vulnerabilities and are susceptible to security attacks (e.g., masquerading user, password guessing, internal privilege, and MITT attacks), so they cannot meet the anonymity requirements or achieve forward security. To effectively improve the security performance of WSNs, an elliptic curve cryptography (ECC)-based three-factor authentication and key agreement scheme for WSNs is proposed. The scheme is based on the ECC protocol and combines biometrics, smart card and password authentication technology; uses a challenge/response mechanism to complete the authentication between users, gateways, and sensors; and negotiates a secure session key. The Burrows, Abadi and Needham logic for formal security analysis proves the correctness and security of the scheme, and the informal analysis of multiple known attacks proves that the scheme can resist various attacks and has high security characteristics. The feasibility of the scheme has been analysed and verified with the ProVerif tool. The efficiency analysis results show that the scheme is suitable for resource-constrained WSNs.

Analysis and Improvement on an Authentication Scheme for Wireless Sensor Networks in Internet of Things Environment

Nowadays, Internet of Everything has become a major trend, and Internet of Things (IoT) has emerged. Wireless sensor networks (WSNs) are core technologies for IoT to sense the real world. Due to the unattended and resource-constrained characteristics of WSNs, it is a great challenge to design an efficient and secure authentication scheme for communication between users and sensor nodes in WSNs. Recently, Hu et al proposed an authentication scheme for WSNs in an IoT environment. They claimed that their scheme could maximize the balance between security and computational cost as well as efficiency, and be resistant to many known attacks. However, we find that the scheme is difficult to resist stolen smart card attack and denial-of-service attack. Moreover, during the login and key negotiation phase of the scheme, Gateway (GWN) is unable to extract key values for subsequent computation based on the messages sent by the sensor nodes, which in turn leads to the inability to achieve mutual authentication and key agreement. To overcome these shortcomings, we propose an improved scheme. The proposed scheme enables real-time data exchange and transmission as well as secure communication between users and sensor nodes.

Energy Efficient Cluster based Routing Scheme for WSN based IoT to Extend Network Lifetime

With the development and advancement of wireless sensor networks (WSN), the emergence of the Internet of Things (IoT) has achieved prominence in the modern era. With the increasing number of connected devices, WSN has become a key factor in the communication component of the IoT. In IoT-based WSN infrastructure, devices are equipped with intelligent sensors that sense the environment to collect data, process data, and deliver information to the sink or base station (BS). WSN-assisted IoT has become a key technology for various data-centric applications such as health care, smart cities, and the military. Sensor nodes in IoT devices are equipped with bound and irreplaceable batteries. An increased number of connected devices face serious issues of energy depletion, maintenance, and load balancing, which might result in device failure. Energy efficiency is considered a vital parameter in the design of an IoT based WSN, and this can be accomplished through clustering and multihop routing techniques. In this paper, we propose an energy-aware multihop routing scheme (EAMRS) for hierarchical cluster-based WSN-assisted IoT. EAMRS considers the improved low-energy adaptive clustering algorithm (I-LEACH) to select optimal cluster heads (CH). During data transmission, multihop routing is involved by considering routing metrics such as residual energy, distance to BS and optimal route choice to balance the energy load. However, conventional routing schemes fail to achieve the flexibility and adaptability prerequisites of load balancing mechanisms. EAMRS decreases computation overhead and restricts energy usage, resulting in a prolonged network lifetime.

Trust Score based Optimized Cluster Routing (TSOCR) approach for Enhancing the Lifetime of Wireless Sensor Networks

Energy efficiency is the most significant obstacle that Wireless Sensor Networks (WSN) must overcome, and the desire for solutions that maximize energy efficiency will never go away. There are a variety of methods that can be utilized to improve energy efficiency, with data transmission as the primary driver of maximum energy consumption. The transmission of data from the source to destination nodes uses more energy. When the transmission of data is handled better, the energy efficiency is improved and the lifetime of the network is increased. The purpose of this research is to propose an Trust Score based Optimized Cluster Routing (TSOCR) scheme for WSNs, which is based on Whale Optimization Algorithm (WOA). A total trust score is derived by combining the results of computing three distinct trust scores, such as the direct, indirect, and the most recent trust score. The path that has the highest trust score is chosen as the route and employed for data transmission. The effectiveness of the work is evaluated by looking at factors such as the rate of packet delivery, the latency, the amount of energy consumed and the lifetime of the network.

Effective cluster scheduling scheme using local gravitation method for wireless sensor networks

Ensuring a certain clustering of distributed sensor nodes is significant for energy efficiency of wireless sensor networks (WSNs). Recently, several energy efficient artificial intelligence based-methods that provide cluster scheduling schemes have been proposed. However, there are few methods providing balanced energy exhausting of the number of nodes in clusters. In this paper, we present a novel cluster scheduling scheme for WSNs using local gravitational method to adaptively determine the number of time-varying clusters based on a sequence of vectors. The main idea in this method is to be inspired by the physical features of gravity force among the mass units. These features are considered to be units of mass of nodes in vector space. It is based on the fact that with clustering, the highest gravitational force on moving the units of mass is applied by the area with feature vectors that are high-density. Cooperative and distributed clustering is formed and the number of clusters is found by sharing the gravitational force between neighboring nodes through a distribution-optimization scheme. The results of this study have been compared with the existing methods in various scenarios and with many performance criteria through the Matlab programming. Especially in dense networks, the proposed algorithm has increased the number of clusters and ensured the clustering balance as much as possible. The proposed method has scaled down the energy consumption, and enhanced the network lifetime.

A Data Integrity Authentication Scheme in WSNs Based on Double Watermark

Aiming at data security in Wireless Sensor Networks (WSNs), a data authentication scheme based on double watermark is proposed in this paper. Double watermark includes reversible watermark and irreversible watermark. The former generated by group head data is embedded into the effective precision bit of data, and the latter generated by the effective precision bit of the data themselves and a defined array is embedded into the flag bit in two cases. Two adjacent groups form a working group. For the first case, a flag-check matrix is constructed by the special data set which includes the head of the current group and the tail of the previous group, and the data around them. Through the matrix, the watermark is embedded into the special data set to ensure the robustness of grouping. For the second case, watermark is embedded into the group data except special data set (the rest data) to ensure efficient detection of attacks. When the attacked position and type are detected, the data that are not tampered with in this group can still recover the effective precision bit. The security analysis and experimental results demonstrate that the comprehensive performance of the proposed scheme outperforms that of those state-of-the-art schemes.

Secure Key Management and Mutual Authentication Protocol for Wireless Sensor Network by Linking Edge Devices using Hybrid Approach

Wireless Sensor Networks (WSNs) play a crucial role in developing the Internet of Things (IoT) by collecting data from hostile environments like military and civil domains with limited resources. IoT devices need edge devices to perform real-time processing without compromising the security with the help of key management and authentication schemes. The above applications are prone to eavesdropper due to cryptographic algorithms' weaknesses for providing security in WSNs. The security protocols for WSNs are different from the traditional networks because of the limited resource of sensor nodes. Existing key management schemes require large key sizes to provide high-security levels, increasing the computational and communication cost for key establishment. This paper proposes a Hybrid Key Management Scheme for WSNs linking edge devices which use Elliptic Curve Cryptography (ECC) and a hash function to generate key pre-distribution keys. The Key establishment is carried out by merely broadcasting the node identity. The main reason for incorporating a hybrid approach in the key pre-distribution method is to achieve mutual authentication between the sensor nodes during the establishment phase. The proposed method reduces computational complexity with greater security and the proposed scheme can be competently applied into resource constraint sensor nodes.

MCSO-MW: An Energy Optimized Data Switching Scheme for Multi-hop Wireless Sensor Networks

Due to continuous growth in the field of wireless sensor networks (WSN), it holds enormous growth in the multidisciplinary domains to provide a promising solution. Especially, on the internet of things (IoT) based edge device network, WSN plays a significant area in the field of data collection and physical entity monitoring. The effectiveness of the routing scheme in WSN can be directly measured through the amount of data transmission, network topology, intermediate hop counts, and data transmission distance. Similarly, an ideal energy model can improve the entire system’s performance and sustainability over successive data transmission. In this paper, a multi-objective chicken swarm optimization (CSO) algorithm is adopted to optimize energy consumption over WSN and improve the system performance through an effective routing approach. Furthermore, the proposed approach is adopted to partition the entire sensor network into multiple clusters and select the partitioned head among the sensor nodes. The competence of the proposed approach is validated against other existing approaches.

An Efficient Grid-Based Geocasting Scheme for Wireless Sensor Networks

In a wireless sensor network (WSN), geocasting is a location-based routing protocol used for data collection or information delivery. In geocasting, a target region usually contains many sensor nodes with limited battery capacity, and sensor nodes in multiple target regions need to transmit data to the sink. Therefore, how to use location information to construct an energy efficient geocasting path is a very important issue. FERMA is a geocasting scheme for WSNs based on Fermat points. In this paper, an efficient grid-based geocasting scheme for WSNs, which is called GB-FERMA, is proposed. The scheme uses the Fermat point theorem to search for the specific nodes as Fermat points in a grid-based WSN, and it selects the optimal relay nodes (gateways) in the grid structure to realize energy-aware forwarding. In the simulations, when the initial power 0.25 J, the average energy consumption of GB-FERMA is about 53% of FERMA-QL, 37% of FERMA, and 23% of GEAR; however, when with the initial power 0.5 J, the average energy consumption of GB-FERMA is about 77% of FERMA-QL, 65% of FERMA, and 43% of GEAR. The proposed GB-FERMA can effectively reduce the energy consumption and thus prolong the lifetime of the WSN.

Cryptanalysis and improvement of an authentication protocol for wireless sensor networks

SummaryThe Wireless Sensor Network (WSN) is a network which is composed of many sensor nodes. The sensor nodes in WSN are widespread and lightweight which are deployed for environmental or system monitoring. These sensor nodes within the WSNs communicate with one another using wireless lines. WSNs have practical applications in numerous fields such as smart city, medicine, military, agriculture, and so forth. It is easy for an adversary to intercept the network and steal the valuable information. Consequently, these sensor nodes need enhanced security. Recently, Kwon et al have proposed an authentication scheme for WSNs. However, in this paper, we analyze the security of their scheme and discover that their protocol fails to provide perfect forward security and user untraceability. Also their protocol fails to withstand against session specific random number leakage attack, privileged insider attack and password guessing attack. Their protocol uses only two‐factor authentication scheme. In order to overcome the weaknesses of their protocol, we develop a secure three‐factor authentication protocol which is based on symmetric key cryptography. We use ProVerif tool to perform its formal security verification and use random oracle model for its formal security analysis. We also show the correctness of mutual authentication of the proposed scheme using BAN logic. Its informal security analysis indicates that the designed scheme can withstand against various known attacks. In the performance analysis, we show that the proposed scheme offers more security features than the other related schemes and has less communication cost as compared to Kwon et al protocol.

An Enhanced User Authentication and Key Agreement Scheme for Wireless Sensor Networks Tailored for IoT.

A security protocol for wireless transmission is essential to defend sensitive information from malicious enemies by providing a variety of facilities such as privacy of the user's information, secure session key, associated authentication, and user-repeal facility when a person's authorizations are suddenly disclosed. Singh et al. proposed an improved user authentication and key agreement system for wireless sensor networks (WSNs). Authors are sure that their protocol is secure from various attacks. Here, we find several security pitfalls in their scheme, such as an offline password-guessing attack, failure to protect the session key, and a man-in-the-middle attack. To remove the identified pitfalls found in Singh et al.'s scheme, we design an enhanced authentication scheme for WSNs tailored for IoT. We prove the reliability of our proposed protocol using the real or random (RoR) model. We also evaluate the proposed scheme with the associated schemes and show its superior efficacy as compared to its counterparts.

Quantum tunicate swarm algorithm based energy aware clustering scheme for wireless sensor networks

Wireless Sensor Network (WSN) is represented by a group of sensor nodes with limited battery capacity deployed in a target region for data collection purposes. Energy is treated as a major issue from the design of WSN as it mainly affects the overall functioning of the network. A commonly employed energy-efficient mechanism is clustering which groups the nodes into several groups of clusters. Earlier works reported that clustering is treated as an NP hard issue which can be addressed by soft computing techniques. In this way, this article focuses on the design of Quantum Tunicate Swarm Algorithm Based Energy Aware Clustering (QTSA-EAC) scheme for WSN. The presented QTSA-EAC technique mainly attempts to effectively manage the available energy among the nodes in WSN. In addition, the QTSA is derived by the incorporation of quantum computing concepts as to the traditional TSA. Moreover, the QTSA-EAC technique derives a fitness function with the minimization of total energy consumption in the networks. The inclusion of multiple parameters in the cluster head (CH) selection process helps to accomplish energy efficiency and maximum lifetime of WSN. The performance assessment of the QTSA-EAC technique is performed and the results reported that the presented model is effective, improves lifetime, reduce energy exploitation, and delay over the other methods.