WSN Security Research Articles

Towards robust security in WSN: a comprehensive analytical review and future research directions

Towards robust security in WSN: a comprehensive analytical review and future research directions

Enhancing agricultural wireless sensor network security through integrated machine learning approaches

AbstractWireless sensor network (WSN) works with a collection of multiple sensor nodes to fetch the data from the deployed environment to fulfill the application whether it is agricultural monitoring, industrial monitoring, etc. The agricultural region can be monitored by deploying sensor nodes to multiple verticals where continuous human presence is not feasible. These devices are equipped with limited resources and are easily vulnerable to various cyber‐attacks. The attacker can hack the sensor nodes to steal critical information from WSN devices. The cluster heads in the WSN play a vital role in the process of routing data packets and attackers launch malicious codes through sender nodes to hack or damage the cluster heads to shut down the entire deployed network of agricultural regions. This research paper proposes a framework to improve the security of WSNs by providing a shield to the cluster heads of the network using machine learning techniques. The experimental study of the paper includes the comparative analysis of three machine learning techniques decision tree classifier, Gaussian Naïve Bayes, and random forest classifier for predicting WSN attacks like flooding, gray hole, blackhole, and TDMA that are deployed to support the proposed WSN security framework on the attack dataset. The random forest classifier achieves an accuracy of 98%, Precision of 97.6%, Recall of 97.6%, and F1 score of 97.8% which is the maximum among the deployed machine learning techniques.

Cryptographic image-based data security strategies in wireless sensor networks

There is need to develop and create new data protection mechanisms aimed at the compensating for the lack of security of WSNs. This paper introduces new cryptographic image-based techniques aimed at improving data security in WSNs. The solution also integrates imaging processing techniques with advanced cryptographic principles to merge a two-layered security architecture. This work provides a new WSN-specific encryption algorithm that delivers low energy consumption and smaller computational burden. Likewise, this is connected to an image-based authentication approach which employs steganographic methods in the information hiding technique. Intensive simulations allow the approach that supports methodology, naming increased security metrics obtained without decreasing in network performance. This study seeks to fill the gap in current practice in WSN security and provides a foundation for future research on image-based techniques integrated with cryptographic algorithms aiming at more secure data protection under limited resources.

Trust management based multidimensional secure cluster with RSA cryptography algorithm in WSN for secure data transmission

WSNs are now widely used for information gathering and transmission using WSN. Due to its low cost and simple communication, this type of network is widely used in many applications. Although hierarchical routing protocols may handle a variety of applications, choosing a Cluster Head (CH) and balancing network overload are difficult problems. This recommended strategy provides LEACH Protocol based on Novel Trust Management with Cryptographic RSA algorithm (NTM-LEACH-RSA) to extend the lifetime of network and to consume less energy. Here the proposed methodology includes two aspects for improving Security in WSN. Using the suggested NTM-LEACH technique, cluster formation and cluster head election are carried out in the first phase. Here, the threshold function value, the distance and density between nearby nodes, and the trust value are used to elect the cluster head. Based on the energy domain and the distance domain, the threshold function value is estimated in this case. The RSA cryptography technique is employed in the second phase to protect data transmission and guarantee data integrity. By using simulation tools, the proposed NTM-LEACH-RSA methodology's performance analysis is estimated. In comparison to other algorithms currently in use, it also offers higher performance results.

An Intelligent Prairie Dog Optimization (IPDO) and Deep Auto-Neural Network (DANN) based IDS for WSN Security

An Intelligent Prairie Dog Optimization (IPDO) and Deep Auto-Neural Network (DANN) based IDS for WSN Security

Detection of unique delete attack in wireless sensor network using gradient thresholding‐long short‐term memory algorithm

SUMMARYWireless sensor network (WSN) is widely used in many fields, including agriculture, military, healthcare, monitoring, and surveillance. WSN application increases day by day due to growth in embedded and internet technologies. However, data security in WSN is challenging, and different types of attacks are increasing. Traditional intrusion detection methods analyze and identify attacks such as Denial of Service, anomaly detection, wormhole, sybil, and blackhole. Traditional methods never addressed the application layer's novel attack, such as the delete attack. Unique DELETE attack (DA) forms in the application layer and targets web servers and applications. Since unique DA use uniform resource locator requests, distinguishing them from legitimate traffic becomes difficult. The unique DA classify as unique (or) single, multiple, and repeated unique DELETE attacks; for detecting the unique DA types, gradient thresholding‐long short‐term memory (GT‐LSTM) algorithm is proposed using packet per second and traffic rate data in WSN nodes. GT‐LSTM algorithm detects unique DA through different thresholding at the training option layer in LSTM. Different gradient thresholding values in LSTM reduce the exploding gradients which fail to detect the unique DA nodes. Gradient thresholding in LSTM layers lies 1 to 3 for detecting unique DELETE attack nodes. The proposed method reduces detection time, improves accuracy, and identifies the hidden node that performs a unique DA in WSN. The unique DELETE Attack identification and performance through the proposed GT‐LSTM is analyzed in the NS2 simulation environment and the test bed of WSN. Forms the experimental and simulation results, GT‐LSTM performs better than fuzzy, KNN, and linear regression‐based intruder detection systems. The proposed algorithm achieves 99% accuracy in detecting the DELETE attack nodes in WSN.

Retraction Note to: Trust aware localized routing and class based dynamic block chain encryption scheme for improved security in WSN

Retraction Note to: Trust aware localized routing and class based dynamic block chain encryption scheme for improved security in WSN

E2DA: Energy Efficient Data Aggregation and End-to-End Security in 3D Reconfigurable WSN

This paper deals with energy consumption and security limitations in the reconfigurable WSN’s in order to improve the network lifetime with end-to-end data privacy. The network consists set of nodes placed in distributed environment such that each node performs a reconfiguration task to support users requirements. We proposed novel solutions that improved network lifetime through efficient reconfigurable routing and less network traffic. We proposed an in-network task to eliminate duplicate packets at the node level using hashing distance computation (HDC). Further, we introduced power-efficient reconfigurable cell-by-cell golden sector-based emperor penguin colony (CbC GSEPC) for trust-based routing. In terms of data confidentiality in the energy-constrained environment, a lightweight key expandable cryptography method was proposed for end-to-end confidentiality. Additionally, a reading-based dual validation (RbDV) audits the information at sink level for intrusion detection and isolates suspicion nodes. The proposed and existing works simulated with NS-3.26 and the results show that the proposed work’s average energy consumption is 5.82% lower than the existing 2D-WSN while offering end-to-end confidentiality and node reconfiguration opportunity.

A Data-Driven WSN Security Threat Analysis Model Based on Cognitive Computing

In this paper, we use cognitive computing to build a WSN security threat analysis model using a data-driven approach and conduct an in-depth and systematic study. In this paper, we develop a simulation platform (OMNeT++-based WSN Security Protocol Simulation Platform (WSPSim)) based on OMNeT++ to make up for the shortcomings of current WSN simulation platforms, improve the simulation capability of WSN security protocols, and provide a new technical means for designing and verifying security protocols. The WSPSim simulation platform is used to simulate and analyze typical WSN protocols and verify the effectiveness of the platform. In this paper, we mainly analyze the node malicious behavior by listening and judging the communication behavior of the nodes, and the current trust assessment is given by the security management nodes. When the security management node is rotated, its stored trust value is used as historical trust assessment and current trust assessment together to participate in the integrated trust value calculation, which improves the reliability of node trust assessment; to increase the security and reliability of the management node, a trust value factor and residual energy factor are introduced in the security management node election in the paper. According to the time of management node election, the weights of both are changed to optimize the election. Using the WSPSim simulation platform, a typical WSN protocol is simulated and analyzed to verify the effectiveness of the platform. In this paper, the simulation results of the LEACH protocol with an MD5 hash algorithm and trust evaluation mechanism and typical LEACH protocol as simulation samples are compared; i.e., the correctness of the simulation platform is verified, and it is shown that improving the security of the protocol and enhancing the security and energy efficiency of wireless sensor networks provide an effective solution.

Secure Multimodal Authentication Scheme for Wireless Sensor Networks

In the current era, it is necessary to device authorization and authentication techniques to secure resources in information technology. There are several methods to substantiate authorization and authentication. User authentication is essential for authenticating user access control in WSNs. Biometric recognition error, lack of anonymity and vulnerability to attacks, user verification problem, revocation problem and disclosure of session key by the gateway node are some of the security flaws encountered. In this study, a Multimodal Authentication Scheme for Wireless Sensor Networks (WSN-MAS) is proposed to authenticate legitimate users. The main objective is the fusion of fingerprint and iris biometric features at feature level to enable additional accuracy to verify and match user identity with stored templates. In this paper, multimodal biometric features are used for authentication to improve performance, reduce system error rates to achieve better security in WSN.

Efficient Authentication Algorithm for Secure Remote Access in Wireless Sensor Networks

Wireless sensor networks convey mission critical data that calls for adequate privacy and security protection. To accomplish this objective, numerous intrusion detection schemes based on machine learning approaches have been developed. In addition, authentication and key agreements techniques have been developed using techniques such as elliptic curve cryptography, bilinear pairing operations, biometrics, fuzzy verifier and Rabin cryptosystems. However, these schemes have either high false positive rates, high communication, computation, storage or energy requirements, all of which are not ideal for battery powered sensor nodes. Moreover, majority of these algorithms still have some security and privacy challenges that render them susceptible to various threats. In this paper, a WSN authentication algorithm is presented that is shown to be robust against legacy WSN privacy and security attacks such as sidechannel, traceability, offline guessing, replay and impersonations. From a performance perspective, the proposed algorithm requires the least computation overheads and average computation costs among its peers.

Ensuring the Security in WSN using a Novel Approach against Sink Hole Attacks

Ensuring the Security in WSN using a Novel Approach against Sink Hole Attacks

RETRACTED ARTICLE: An improved source location privacy protection using adaptive trust sector-based authentication with honey encryption algorithm in WSN

A wireless sensor network is a set of sensor nodes used to identify the environment and the corresponding object. It collects all the data of the situation and transmits this detected data to the central node through a wireless network. However, some challenges are encountered in wireless sensor networks i.e., the efficient deployment of sensor nodes in an environment. Some of the issues are limited sources of energy, limited transmission bandwidth, short coverage, data distribution, data persistence, faulty node, and data security redundancy. The Discovery Configuration Protocol (DCP) has been signed for a period of time to monitor the applications. It is required for alternate use, which is very important to recreate the correct data source. Recently, Source Location Privacy (SLP) security at the WSN has attracted a way to prevent opponents from pursuing a backtracking strategy to capture the data source. Delivery of messages from different source nodes to sink nodes is done through an end-to-end location privacy process. With location-based services, data must be retrieved by users who do not have information about the data’s location. So, introduce a proposed Adaptive Trust Sector-Based Authenticated System (ATSAS), which is meant to evaluate the trust confidence value of each node with the help of agent sinks node. When the joining nodes discover their neighbors, they exchange information about the number of single-hop neighbors. The updated confidence value of the node is formed in the network algorithm. The first stage is done using the Honey Encryption (HE) for message authentication and packet encryption to provide security in WSN. These encryptions are making Distribution-Transforming Encoder (DTE) for space of the un-encrypted plain text message into the seed space of n-bit string. The output encryption point is the input to feedback for key generation. To the next level, both direct and indirect observations, such as its neighbor’s trust value, are calculated based on two sources of information. This protocol thereby increases secure communication in a hierarchical WSN. The trust rate control of the network at the source of the packet, which helps drive the time control mechanism. Such Network Control Point (NCP) system development methods provide security and reduce the occurrence of overload on distributed sensor nodes. The theoretical analysis and test results demonstrate that the proposed method improves security, reduces directional attacks, and increases the network’s longevity.

Improving Energy Efficiency in Internet of Things using Artificial Bee Colony Algorithm

Background: With the advent of IoT, the deployment of batteries with a limited lifetime in remote areas is a major concern. In certain conditions, the network lifetime gets restricted due to limited battery constraints. Subsequently, the collaborative approaches for key facilities to reduce the constraint demands of the current security protocols. Objective: This work covers and combines a wide range of concepts linked by IoT based on security and energy efficiency. Specifically, this study examines the WSN energy efficiency problem among IoT devices and security for the management of threats in IoT through collaborative approaches and finally outlines the future. The concept of energy-efficient key protocols which clearly cover heterogeneous IoT communications among peers with different resources has been developed. Because of the low capacity of sensor nodes, the energy efficiency in WSNs has been an important concern. Methods: In this paper, we present an algorithm for Artificial Bee Colony (ABC) which reviews security and energy consumption to discuss their constraints in the IoT scenarios. Results: The results of a detailed experimental assessment are analyzed in terms of communication cost, energy consumption and security, which prove the relevance of a proposed ABC approach and a key establishment. Conclusion: The validation of DTLS-ABC consists of designing an inter-node cooperation trust model for the creation of a trusted community of elements that are mutually supportive. Initial attempts to design the key methods for management are appropriate individual IoT devices. This gives the system designers, an option that considers the question of scalability.

Utilizing Blockchain Technology to Improve WSN Security for Sensor Data Transmission

This paper proposes a method for improving the data security of wireless sensor networks based on blockchain technology. Blockchain technology is applied to data transfer to build a highly secure wireless sensor network. In t... | Find, read and cite all the research you need on Tech Science Press

Semantic‐Based Sports Music Information Fusion and Retrieval in Wireless Sensor Networks

The wireless sensor network has developed rapidly in recent years. It is formed by the intersection of multiple disciplines. It integrates embedded technology, sensor technology, distributed technology, wireless communication technology, and modern networks. It is a brand new information acquisition platform. The characteristics of sensor networks determine that information fusion technology is a hot spot in the research of wireless sensor networks. Information fusion can achieve high performance and low cost in terms of energy and communication, which is of great significance to the research of sensor networks. This paper is aimed at studying the semantic‐based sports music information fusion and retrieval research in wireless sensor networks. WSNs may face various attacks including eavesdropping attacks, replay attacks, Sybil attacks, and DOS attacks. Therefore, they are designing sensor network solutions. It is necessary to consider the network security issues. This article summarizes and analyzes the existing WSN security data fusion solutions for this issue and compares them by classification. This paper proposes methods and theories such as the spatial correlation detection algorithm, CBA algorithm, FTD algorithm, and DFWD algorithm, which enriches the research of information fusion and retrieval in wireless sensor networks, which is of exploratory significance, and it also establishes this problem. The model was studied, and reliable data was obtained. The experimental results of this paper show that when using these methods to diagnose faults in WSN, the correct rate of model diagnosis is higher than 77%.

RETRACTED ARTICLE: Trust aware localized routing and class based dynamic block chain encryption scheme for improved security in WSN

The modern wireless sensor network has great impact in the development of various domains of applications. The presence of malicious nodes introduces various threats and challenges to the network services. Different algorithms have been proposed towards the data security but not achieved the expected performance. Towards performance hike, a novel trust aware localized routing and class based dynamic encryption scheme has been presented. The method first discovers the route to reach the destination and transmit the data packet. But the localized nature of each hop in the route estimates the trust measure for each neighbor according to their prior involvement in data transmission and number of retransmission of the same packets with other neighbor, number of successful transmission. By identifying the values of those parameters, the value of trusted data forwarding support (TDFS) is measured. According to the TDFS value of several routes, a route with the specific neighbor only selected for route selection. On the other side, the method maintains and classifies the data being transmitting into number of classes. Further, the method uses different signature and encryption schemes for various classes. The data has been encrypted with class specific scheme and key before transmission. The method generates a block chain where each block contains the part of encrypted data and represented by a hash and pointer to the next block. The same has been reversed to produce original data from the encrypted key. The method introduces higher performance data security and improves the overall network performance.

Key Distribution and Management in WSN Security: A State of the Art

Offering efficient key management scheme (KMS) in WSN faces many challenges that will significantly impact the design and implementation of security protocols for WSN. The goal of KMS is to provide an effective environment in which the sensor node can communicate in a secure manner. It should be able to resolve the issue of generate, allocate the cryptographic keys in WSN in an efficient and effective manner. Hence, the methods for trustworthy allocation and management of these keys are very important for security of WSN. Many KMSs have been developed in recent years. However inherent characteristics of a WSN make incorporating security a great challenge. This paper presents a comprehensive review of current state-of-the-art of KMS designed for WSN security and compare with respect to several evaluation metrics. This paper also investigates the security requirements, goals and challenges of KMS based on existing literature reviews. We also attempt to provide insight in to potential research trends in the area of WSN security and outline the approaches that are likely to play a very important role.

A Systemic view of One-Pass Cryptographic Key Distribution Techniques for WSNs

The availability and use of cheaper and smaller sensors has brought an evolution in the field of Wireless Sensor Networks. The changes occurring in the environment can be observed, recorded through the large-scale deployment of sensor nodes that can build-up the much-required information system. Also, they are able to monitor and congregate data about the living organisms therein. In near future, millions more devices are expected to be connected. We focus upon the security services required by WSNs that are most challenging as compared to other networks. First, we introduce the commercially used motes with the comparison of technical and implementation related issues. Second, we analysed the variants of existing one-pass key management protocols for the resource constrained devices. Our aim is to provide a new direction to WSN Security through a restricted key distribution mechanism.

A Survey On Security In Wireless Sensor Network

With the global use of wireless sensor network technology in different fields and for different purposes such as health care monitoring, earth sensing, air pollution monitoring, military operations monitoring or surveillance system monitoring, a problem arises. Problem that could negatively impact previously started activities and observations if not handled in a right way. Authors of this paper discuss various vulnerabilities and security threads in different applications of WSN in the real world, such as intrusion, node capture attack, black hole attack or selective forwarding attack. Potential countermeasures are proposed formatted as protocols or architectures for secure transfer of data between friendly nodes, compromises on security measures with the goal of achieving secure and reliable connection. This paper could be used as a general representation of WSN security issue with which WSN engineers are faced on a daily basis.