Wireless Network Security Research Articles

Wireless sensor network security: A recent review based on state-of-the-art works

Wireless sensor networks (WSNs) are a major part of the telecommunications sector. WSN is applied in many aspects, including surveillance battlefields, patient medical monitoring, building automation, traffic control, environmental monitoring, and building intrusion monitoring. The WSN is made up of a vast number of sensor nodes, which are interconnected through a network. However, despite the growing usage of applications that rely on WSNs, they continue to suffer from restrictions, such as security issues and limited characteristics due to low memory and calculation power. Security issues lead to a lack of communication between sensors, wasting more energy. The need for efficient solutions has increased, especially with the rise of the Internet of Things, which relies on the effectiveness of WSNs. This review focuses on security issues by reviewing and addressing diverse types of WSN assaults that happened on each layer of the WSN that were published in security issues in the previous 3 years. As a consequence, this paper gives a taxonomy of security threats for each layer and different algorithmic solutions that numerous researchers who seek to counter this attack have explored. This study also presents a framework for constructing an intrusion detection system in the WSN by emphasising the drawbacks of each approach suggested by researchers to defend against specific forms of assault. In order to diminish the impact of this attack, this summary shows which attacks the majority of researchers have dealt with as well as which ones they have not yet addressed in their academic work.

Blockchain-Based Secure Localization against Malicious Nodes in IoT-Based Wireless Sensor Networks Using Federated Learning

Wireless sensor networks are the core of the Internet of Things and are used in healthcare, locations, the military, and security. Threats to the security of wireless sensor networks built on the Internet of Things (IoT-WSNs) can come from a variety of sources. This study proposes secure attack localization and detection in IoT-WSNs to improve security and service delivery. The technique used blockchain-based cascade encryption and trust evaluation in a hierarchical design to generate blockchain trust values before beacon nodes broadcast data to the base station. Simulation results reveal that cascading encryption and feature assessment measure the trust value of nodes by rewarding each other for service provisioning and trust by removing malicious nodes that reduce localization accuracy and quality of service in the network. Federated machine learning improves data security and transmission by merging raw device data and placing malicious threats in the blockchain. Malicious nodes are classified through federated learning. Federated learning combines hybrid random forest, gradient boost, ensemble learning, K -means clustering, and support vector machine approaches to classify harmful nodes via a feature assessment process. Comparing the proposed system to current ones shows an average detection and classification accuracy of 100% for binary and 99.95% for multiclass. This demonstrates that the suggested approach works well for large-scale IoT-WSNs, both in terms of performance and security, when utilizing heterogeneous wireless senor networks for the providing of secure services.

Deep learning based physical layer security for terrestrial communications in 5G and beyond networks: A survey

The key principle of physical layer security (PLS) is to permit the secure transmission of confidential data using efficient signal-processing techniques. Also, deep learning (DL) has emerged as a viable option to address various security concerns and enhance the performance of conventional PLS techniques in wireless networks. DL is a strong data exploration technique which can be used to learn normal and abnormal behavior of 5G and beyond wireless networks in an insecure channel paradigm. Also, since DL techniques can successfully predict future new instances by learning from existing ones, they can successfully predict new attacks, which frequently involve mutations of earlier attacks. Thus, motivated by the benefits of DL and PLS, this survey provides a comprehensive review that overviews how DL-based PLS techniques can be employed for solving various security concerns in 5G and beyond networks. The survey begins with an overview of physical layer threats and security concerns in 5G and beyond networks. Then, we present a detailed analysis of various DL and deep reinforcement learning (DRL) techniques that are applicable to PLS applications. We present the specific use-cases of PLS design for each type of technique, including attack detection, physical layer authentication (PLA), and other PLS techniques. Then, we present an in-depth overview of the key areas of PLS where DL can be used to enhance the security of wireless networks, such as automatic modulation classification (AMC), secure beamforming, PLA, etc. Performance evaluation metrics for DL-based PLS design are subsequently covered. Finally, we provide insights to the readers about various challenges and future research trends in the design of DL-based PLS for terrestrial communications in 5G and beyond networks.

Enhancing security & QoS of trust-enabled wireless networks using machine learning powered transformable blockchain sharding

Trust enabled wireless networks use temporal behaviour information of nodes in order to classify them into different trust categories. This information is utilized by the router for high performance communication that is optimized in terms of end-to-end delay, energy consumption, throughput, packet delivery ratio, and other quality of service (QoS) parameters. Establishing security in trust enabled wireless networks is a difficult task, because high trust nodes might be compromised by external or internal attacks, thereby disrupting normal communication. In order to perform this task, blockchain based security models are deployed. These models provide high transparency, comprehensive traceability, distributed processing, and data immutability, which makes them highly deployable for trust enabled networks. Blockchain models enforce compulsive verification of data before communication, which makes them resilient to DDoS, MITM, denial of service, and other data-based attacks. In order to enforce these checks, each of the block is hashed, and the hash values are compared with every existing block in the chain. These checks include hash uniqueness, and hash pattern validations; the later of which is decided by the network designer(s). As the length of blockchain increases, computational complexity of adding a new block (a.k.a. blockchain mining) increases exponentially, which adds to the end-to-end delay, and energy consumption of wireless nodes, which is a drawback of these models. To avoid this, sidechains & blockchain sharding models are developed. These models work by dividing the existing blockchain into multiple parts (based on a certain pre-set criteria), and then use the parts for high speed and low power mining. But again, due to increase in number of sidechains, the computational complexity of managing these chains, and locating data blocks within them increases exponentially. Moreover, in any practical wireless network, there is a need to communicate modifiable data, which is not supported by current blockchain implementations. In order to resolve these issues, this text proposes a transformable blockchain sharding model, which is managed via a light weight meta heuristic method for high-speed data access. The proposed model aims at reducing computational complexity of sidechain maintenance with the help of directed acyclic graphs (DAGs) for storing of hash ranges. The model also incorporates a transformable blockchain solution, wherein the block structure is designed to incorporate selectively mutable as well as non-mutable information. Both the mutable and non-mutable information is encrypted using high performance elliptic curve cryptosystem, which makes it highly secure against network attacks. The proposed model showcases 15% improvement in network lifetime, 8% reduction in end-to-end delay, 22% reduction in computational complexity, and 18% improvement in network throughput when compared with various blockchain and sidechain based wireless networks, thereby assisting in development of a high QoS and highly secure wireless network.

A survey on network admission control solution in 6LoWPAN using cryptographic mechanism

This paper introduces a robust network admission control (NAC) solution tailored specifically for 6LoWPAN Wireless Sensor Networks (WSN), aiming to enhance the overall security infrastructure. By implementing stringent measures, this solution not only safeguards legitimate nodes but also fortifies the network against potential security threats originating from unauthorized nodes attempting to communicate with both legitimate nodes and the Internet. The solution enhances security through innovative features for administrative nodes, including node presence detection and robust authentication. It incorporates data filtering to swiftly identify and discard unauthorized frames, strengthening network resilience. Established protocols like Neighbor Discovery and DSDV facilitate seamless integration. This strategic utilization minimizes the reliance on additional control messages, thereby optimizing the network's efficiency and resource utilization. The solution utilizes cryptographic methods, particularly the XOR algorithm, to enhance data security in wireless sensor networks. This algorithm ensures authenticity, integrity, and freshness of transmitted data frames, providing robust protection against manipulation and bolstering network security. The proposed network admission control solution addresses security risks in 6LoWPAN WSN and integrates advanced features for a strong and efficient overall security infrastructure in wireless sensor networks.

Cryptographic Algorithm for Enhancing Data Security in Wireless IoT Sensor Networks

Wireless IoT Sensor Network can handle audio, video, text, etc., through the interconnection of ubiquitous devices. The entertainment and application-centric network relies on its autonomous nodes for handling large streams of multimedia data. Security breaches and threats due to insider attacks reduce the data handling and distribution capacity of the nodes. For addressing the insider attacks problem, Session-Critical Distributed Authentication Method (SCDAM) is proposed. The proposed method relies on short-lived concealed authentication based on an improved elliptic curve cryptography (ECC) algorithm. In this authentication, the session time and the interrupts are accounted for, providing end-to-end authentication. The session keys are distributed before and after each interrupt from which the shared data is authenticated. This authentication process uses a linear hash process, ensuring non-repetition of keys in the consecutive sessions. This proposed authentication method is capable of providing improved sessions, less data distribution loss, and complexity.

Разработка моделей скрытного воздействия на инфраструктуру беспроводных сетей с помощью сигналоподобных помех и оценка их устойчивости к обнаружению

Introduction: The article discusses scenarios in which, according to the 802.11 standard, deauthentication frames should be sent from a user or access point. The developed hardware and software complex records such interaction and then broadcasts it as interference. The object of research is IEEE 802.11 wireless networks, the development of models for the covert effect of signal-like interference using USRP on the physical data transmission medium. The subject of the study is the development of signs of detection of DoS effects by these models of signallike interference. The hardware basis is the equipment of National Instruments USRP NI 2901, and the software basis is NI LabVIEW 2018, with which the configuration and management of USRP equipment takes place. The results of the study can be applied when setting up automatic network administration systems (IDS/IPS systems), which will allow timely detection of the impact, increasing the security of wireless communication networks.

ОЦІНКА ЗАХИЩЕНОСТІ БЕЗДРОТОВИХ МЕРЕЖ У МІСЬКОМУ СЕРЕДОВИЩІ З УРАХУВАННЯМ ВИКОРИСТАННЯ ПРОТОКОЛІВ БЕЗПЕКИ

This paper presents the results of a study of assessing the level of security of wireless networks in an urban environment on the example of Kyiv. An analysis of factors affecting the level of security, in particular encryption, authentication and integrity, which affect the level of the mechanism for protecting wireless network traffic, in particular the types of protocols WER, WPA, WPA2 and WPA3, depending on the attack models, is carried out. Protocol vulnerabilities are shown in the context of different protocol configurations. The security advantage of one type of protocol over another is determined. Based on the data from public databases, the current number of wireless networks and the corresponding shares of security protocols on a global scale are determined. An automated study of wireless network security based on the Wardriving methodology in the urban environment of Kyiv was conducted, which was used to obtain data on the types of security protocols in a passive mode. The scan results showed the absence of the use of both the outdated WEP protocol and the newest WPA3 protocol. As a result of scan data processing, the shares of different types of security protocols were determined. Moreover, the scanning methodology allowed us to obtain a wider range of security protocol types than the classic values of WEP, WPA, WPA2 or WPA3, and options for using standards that provide encryption, authentication and integrity. Based on a two-stage procedure, an interval scale for assessing the security level of each type of protocol was built. At the first stage, the protocols were grouped by certain levels of protection, and then ranked within the allocated interval according to the advantages of the standards used, which allowed us to obtain an ordinal scale for assessing the security level of a protocol type. Next, the expert assessment of each type of protocol was determined, which allows for the transition to an interval assessment scale. Based on this scale and the determined shares of protocol types in this sample of scans, an assessment of the level of security of networks in the urban environment of Kyiv was obtained.

УДОСКОНАЛЕННЯ МЕТОДУ ВИЯВЛЕННЯ ТА ЛОКАЛІЗАЦІЇ НЕЛЕГАЛЬНИХ ТОЧОК ДОСТУПУ ДО БЕЗДРОТОВОЇ МЕРЕЖІ ОБ'ЄКТІВ ІНФОРМАЦІЙНОЇ ДІЯЛЬНОСТІ

Extensive use of mobile devices has led to increased Internet connections and the deployment of new wireless LANs. According to the latest Cisco research, by 2023, 66% of the world's population will be Internet users worldwide. More than 28 billion devices will be connected to the global network. In the last two decades, we have witnessed the birth and development of a technology that has significantly changed our work and life - IEEE 802.11, also known as Wi-Fi. Wi-Fi is a favorite way to connect to the Internet because of its ease of use and flexibility. To connect to a wireless network, you only need to be within range. That is, consumers and businesses will increasingly rely on mobile networks. However, it should be noted that each new opportunity of digitalization also gives new opportunities to cybercriminals and therefore, the problem of security of wireless networks today is one of the main problems of IT technologies. The inevitable proliferation of wireless networks and the growing traffic in these networks can lead to many information security incidents. The main threats are aimed at interception, breach of confidentiality and integrity of transmitted data, attacks on the availability of transmission channel nodes and their substitution. The article analyzes the existing methods of detecting unauthorized access points to information. The method of detection and localization of unauthorized access points to information circulating in the wireless network at the objects of information activities has been improved. Natural modeling of detection of unauthorized interference in the information wireless network of the enterprise was carried out. Full-scale simulation confirmed the accuracy of localization of an unauthorized point of access to information in the Wi-Fi network – up to 2 m. This will allow timely detection and localization of unauthorized access points to information in the wireless network of enterprises and institutions.

Covert Communications: A Comprehensive Survey

Information security has always been a critical issue in wireless networks. Apart from other secure techniques, covert communication emerges as a potential solution to security for wireless networks owing to its high-security level. In covert communication networks, the transmitter hides the transmitted signals into environmental or artificial noise by introducing randomness to avoid detection at the warden. By eliminating the existence of transmitted signals at the warden, information security can be preserved more solidly than other secure transmission techniques, i.e., without noticing the existence. Due to the promising security protection, covert communication has been successfully utilized in tremendous wireless communication scenarios. However, fundamental challenges in its practical implementation still exist, e.g., the effectiveness of randomness utilization, the low signal-to-interference-plus-noise ratio at legitimate users, etc. In this survey, we demonstrate a comprehensive review concentrating on the applications, solutions, and future challenges of covert communications. Specifically, the covert principle and research categories are first introduced. Then, the applications in the networks with different topologies and the effective covert techniques in the existing literature are reviewed. We also discuss the potential implementation of covert communications in future networks and the open challenges.

An Efficient and Secured Triple-Layered Wireless Sensor Network with Machine Learning Techniques

Replacement of physical labor and repetitive tasks by the agents is an attractive issue in the Smart Environment (SE). SE is distinguished by its ability to be controlled from a distance, to facilitate the connection between devices through middleware, to gather and share data from sensors, to improve the intelligence of devices, and to make decisions. To be effective, SE design must make use of information and networks that already exist in the actual world. Effective SE design is complicated by several difficulties, including monitoring, data collecting, assessment, evaluation, prediction of important data, and meaningful presentation. For SE, the most important step is gathering information from a variety of sensors in various locations. Wireless sensor networks provide an underlying architecture for the coordinated collection of data from many sensors that have common characteristics (WSN). An essential aspect of sensor networks is their inability to function in the currently complicated environment for wireless network security. In the realm of remote sensor businesses, cryptology is an essential part of safety measures. Several of the prevalent cryptographic methods have significant flaws that prevent them from being fully reliable. In this paper, we provide a unified, three-stage cryptographic procedure that combines public-key and secret-key techniques for maximum security. Due to consideration of Public-key management and high degree of security, Rijndael Encryption Approach (REA), Horst Feistel's Encryption Approach (HFEA), and the more sophisticated Rivest-Shamir-Adleman (e-RSA). Time spent in both execution and decoding of the suggested approach was utilized to rank the quality of displays. The suggested set of rules uses a single evaluation boundary or computation time, which is different from the methodologies used before. Low Encryption Time (LET) and Low Unscrambling Time (LDT) values of 1.12 and 1.26 were observed on texts ranging in size from 6 to 184 MB, respectively. Comparisons show that the suggested hybrid form is 2.9% more efficient than AES+RSA, 1.36 times more efficient than ECC+RSA+MD-5, 1.36 times more efficient than AES+ECC, and 1.36 times more efficient than AES+ECC+RSA+MD-5.

Lightweight Symmetric Encryption and Attribute Based Encryption Method to Increase Information Safety in Wireless Sensor Network

Direct data transmission in a wireless sensor network raises the data transfer cost. In addition, the lifetime of sensor networks is shortened because of the rise in energy required for data exchange. As a result, data aggregation is utilized in WSN to lessen the burden of transmission costs and lengthen the useful life of the sensor networks. The sensor nodes and their collected data are vulnerable to destruction because they are broadcasting in a hostile environment. Therefore, data security is a major topic of study for WSN. Due to the limited resources of the sensor network, conventional wireless network security measures are ineffective. With Speck encryption and CP-ABE, the proposed Lightweight Secured remote Health monitoring System (LSHS) can protect health data and restrict who can access it while using less power. Lightweight block ciphers are optimal for protecting medical records, according to the research. Using the LSHS, we evaluate how well-known lightweight block ciphers like AES, Simon, and Speck perform. Both encrypting and decrypting with the Speck technique require less processing time. Therefore, medical records are encrypted using the Speck algorithm.

Detection of Hello Flood Attacks Using Fuzzy-Based Energy-Efficient Clustering Algorithm for Wireless Sensor Networks

Clustering is one among the most important strategies to improve the lifetime of wireless sensor networks (WSNs). The frequent occurrence of clustering and the subsequent interchange of data overload the sensor nodes and result in wasting power. WSNs are susceptible to attacks because of their resource-constrained nature and large applications in critical military areas. The objective of the threats to the security of wireless sensor networks is to compromise the network by seizing information for misuse. Security features have become a major concern in these types of networks as it is important to protect sensitive data from unauthorized users. This paper aims to present an enriched clustering strategy to minimize the overhead caused by clustering, by formulating an effective cluster update schedule. It also focuses on the attacks that occur during an exchange of initialization messages with neighbors. Clustering of the network is carried out on the basis of the energy of sensor nodes. The nodes that are the heads of the cluster nodes are determined according to the characteristics of energy factors; hence, the role is frequently switched among the nodes of the cluster. To formulate the next cluster update schedule, a fuzzy inference system is employed, and this uses the energy factor of the node, the distance the node is placed from the sink, and the number of member nodes of the cluster. A mechanism is included during an exchange of initialization messages that detects any malicious node pretending to be a neighbor node. The proposed algorithm is evaluated using simulation, and it is found to produce an improved lifetime of 1700 time units. It is shown to conserve the energy of sensor nodes and protect them from unauthorized nodes posing as legitimate neighbors.

SOFTWARE AND HARDWARE STAND AS A MODERN TOOL FOR TEACHING STUDENTS TO CONFIGURE WIRELESS NETWORKS

Goal. Theoretical justification and development of a software and hardware stand in order to train future information security specialists in setting up modern wireless networks.
 Work methodology or method. The study is based on scientific regulations of the practice-oriented learning organization. The competence-based approach was used as its methodological base, theoretical (comparison, analysis, generalization, concretization, modeling) methods were used. The development and implementation of a software and hardware stand in the educational process was carried out at Tyumen State University in 2021-2022 with the involvement of students from the “Computer Security” direction of training.
 Results. The authors have developed and applied in the educational process a software and hardware laboratory stand that combines virtualization tools for software and hardware components of a computer network.
 The stand is used to study the modern infrastructure of a computer network which is used in enterprises and companies by students of the “Computer Security” specialization. It can also be used while teaching modern wireless networks configuration for students of the directions: “Mathematical support and administration of information systems”, “Computer science and computer technology”, “Software engineering”.
 On the basis of the stand a cycle of laboratory works was developed for senior students of the “Computer security” specialization as part of the study of the “Wireless computer networks security” discipline.
 Scope of results. The results of the study can be applied in the field of training future IT-specialists in the higher education system.

Wireless Sensor Network Security Analysis for Data and Aggregation

Data security is critical in wireless sensor networks (WSNs) because communication signals are highly available due to data transmission in free space. Attacks ranging from passive eavesdropping to active snooping are more common on these networks. This paper proposes secure data transfer using data encryption based on the improved Rivest–Shamir–Adleman (RSA) with Diffie–Hellman (DH) key exchange algorithm (IRSA-DH). For this purpose, the adaptive distance-based agglomerative hierarchical (ADAH)-based clustering method is used. Then the cluster head (CH) is selected using the improved weight-based rain optimization (IWRO) to improve the network’s lifespan. This study aims to design a secure group communication method for WSNs. In order to generate and distribute the key to the group, the RSA and DH and key exchange algorithm had been hybridized with the Key Management Center (KMC). For safe communication between users, the key exchange technique is investigated. The performance measures such as throughput, packet loss ratio (PLR), packet delivery ratio (PDR), latency, energy consumption, end-to-end delay (EED) and network lifetime are analyzed and compared with the existing approaches.

Inverse Reinforcement Learning: A New Framework to Mitigate an Intelligent Backoff Attack

The recent advances in Deep Learning have a significant impact on the security of wireless networks, such as intelligent attackers which are able to successfully exploit a possibly unknown defense mechanism simply by interacting with it. Their capacity of adapting to standard defense mechanisms, such as statistical tests, makes them a significant threat. In this article, we develop two intelligent defense mechanisms using inverse reinforcement learning tools, that can be used to enhance the capabilities of current defense mechanisms. We test our proposal on a backoff attack setup against an intelligent attacker, obtaining very significant gains in the defense performance.

Performance analysis of RSMA-based cognitive networks with random distribution of eavesdroppers

Due to the pace of various emerging wireless communication technologies and new application services innovation, network information security, and capacity requirements have become a hot issue of concern. In order to improve network security performance and transmission capacity, researchers have proposed cognitive wireless network and physical layer security as potential solution. Most of the current research work focuses on the assumption that the location of the eavesdropping node is fixed. Starting from the physical layer security and based on the random geometry theory, this paper studies the security performance of cognitive wireless networks under the scenario of random distribution of eavesdropping nodes based on rate splitting multiple access, proposes a system model, and deduces the closed form solutions of connection interruption probability and security interruption probability of secondary users in the cognitive wireless network. The results show that the security interruption probability is related to the density and security of eavesdropping nodes. Finally, the correctness of the formulas is verified by simulation analysis.

Secure wireless network system based on deep reinforcement learning network

In order to improve the security of the secure wireless network system, this paper studies the security of the wireless network system based on the deep reinforcement learning network. Moreover, this paper divides the entire network into a domain structure, and each domain structure includes ordinary nodes, council nodes, key nodes, and dynamic gateway nodes. The key node selects the dynamic gateway node in the domain, and after the dynamic gateway node processes the message, it is forwarded to the gateway node in the adjacent domain. In addition, this paper studies the application of multi-objective optimization in trust management mechanism in secure routing. Furthermore, this paper builds a secure wireless network system based on the deep reinforcement learning network based on the deep reinforcement learning network, and builds a system architecture. Finally, this paper tests the secure wireless network system based on deep reinforcement learning network through simulation experiments. The research results show that the safety factor of the system is relatively high.

Ensuring Security and Energy Efficiency of Wireless Sensor Network by Using Blockchain

With the advancement of new technology, security is the biggest issue nowadays. To solve security problems, blockchain technology will be used. In recent work, most of the work has been done on homogeneous systems, but in our research, the primary focus is on the security of wireless sensor networks using blockchain. Over the last few decades, the Internet of Things (IoT) has been the most advancing technology due to the number of intelligent devices and associated technologies that have rapidly grown in every field of the world, such as smart cities, education, agriculture, banking, healthcare, etc. Many of the applications are developing by using IoT technologies for real-time monitoring. Because of storage capacity or low processing power, smart devices or gadgets are vulnerable to attack as existing cryptography techniques or security are insufficient. In this research work, firstly, we review and identify the privacy and security issues in the IoT system. Secondly, there is a solution for the security issues, which is resolved by blockchain technology. We will check the wireless sensor network to see how data work on distributed or decentralized network architecture. Wireless sensor network clustering technique was introduced by researchers for network efficiency because when the workload spreads, the system will work faster and more efficiently. A cluster comprises a number of nodes, and the cluster head manages the local interactions between the nodes in the cluster (CH). In general, cluster members connect with the cluster head, and the cluster head aggregates and fuses the data acquired in order to save energy. Before approaching the sink, the cluster heads may additionally create another layer of clusters among themselves. The clustering concept divides data traffic into several groups similar to the other data points in the same data point. In contrast, this data point is dissimilar from other data points in another group. All results are presented at the end of this study paper, in which we will see the network or nodes’ performance in the specific area of the network, how it works, and how efficient it is. Likewise, Blockchain also works in a distributed manner.

Certificateless multi-source signcryption with lattice

Network coding can improve network transmission performance and reduce data transmission delay. However, the nodes in network are vulnerable to pollution attacks. Previous network coding schemes are based on difficult problems in number theory and cannot resist the quantum computing attacks. Hence, certificateless multi-source signcryption with lattice (LCL-MSSC) is devised for network coding, it uses common public key to verify the combination ciphertext from different source node users. Based on learning with errors and inhomogeneous small integer solution problems, LCL-MSSC is unforgeable under the adaptive chosen-message attacks and indistinguishable under the adaptive chosen-ciphertext attacks; in addition, it can resist the pollution attacks and quantum computing attacks. Efficient LCL-MSSC has broad application prospect in UAV wireless communication network, mobile wireless network, wireless sensor network or cyberspace security.