Wireless Security Research Articles

Friendly-jamming schemes to secure ultra-reliable and low-latency communications in 5G and beyond communications

The security vulnerabilities are becoming the major obstacle to prevent the wide adoption of ultra-reliable and low latency communications (URLLC) in 5G and beyond communications. Current security countermeasures based on cryptographic algorithms have a stringent requirement on the centralized key management as well as computational capabilities of end devices while it may not be feasible for URLLC in 5G and beyond communications. In contrast to cryptographic approaches, friendly jamming (FJ) as a promising physical layer security method can enhance wireless communications security while it has less resource requirement on end devices and it can be applied to the full distribution environment. In order to protect wireless communications, FJ signals are introduced to degrade the decoding ability of eavesdroppers who maliciously wiretap confidential information. This article presents a state-of-the-art survey on FJ schemes to enhance network security for IoT networks with consideration of various emerging wireless technologies and different types of networks. First, we present various secrecy performance metrics and introduce the FJ method. The interference caused by FJ signals on legitimate communication is the major challenge of using FJ schemes. In order to overcome this challenge, we next introduce the integration of FJ schemes with various communication technologies, including beamforming, multiple-input multiple-output, full duplex, and relay selection. In addition, we also integrate FJ schemes with different types of communication networks. Finally, a case study of FJ schemes is illustrated and future research directions of FJ schemes have been outlined.

Security-Aware Planning of Packet-Over-Optical Networks in Consideration of OTN Encryption

The fast development of cloud computing and Big Data applications has promoted virtualization technologies such as network function virtualization (NFV), which in turn dramatically increased the amount of sensitive data being transmitted over the optical networks for datacenter interconnections (DCIs). To ensure the physical-layer security in DCIs, people have developed optical transport network (OTN) encryption technologies, i.e., leveraging high-speed encryption cards (ECs) to encrypt OTN payload frames. Although experimental studies have confirmed the benefits of ECs in terms of line-speed processing, low latency, and small encryption overhead, the problem of how to utilize them to build a secure packet-over-optical network with high cost-effectiveness has not been explored yet. In this paper, we study how to realize cost-effective and security-aware multilayer planning in a packet-over-optical network that covers both trusted and untrusted zones, in consideration of OTN encryption. We first formulate an integer linear programming (ILP) model to minimize the total capital expenditure (CAPEX) of the multilayer planning, which includes the costs of OTN linecards (LCs), ECs, and bandwidth resources, and solve the optimization exactly. Then, we prove the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NP</i> -hardness of the multilayer planning, and to reduce the time complexity, we propose a column generation (CG) model and design a more time-efficient approximation algorithm based on it. Our simulation results confirm the performance and advantages of our CG-based proposal, i.e., it is much more time-efficient than solving the ILP directly, and outperform the existing heuristic in terms of total CAPEX and costs of used LCs and ECs.

Reputation-Based Federated Learning for Secure Wireless Networks

The dilemma between the ever-increasing demands for data processing, and the limited capabilities of mobile devices in a wireless communication system calls for the appearance of federated learning (FL). As a distributed machine learning (ML) method, FL executes in an iterative manner by distributing the global model parameters and aggregating the local model parameters, which avoids the transmission of huge raw data and preserves data privacy during the training process. However, since FL cannot control the local training and transmission process, this gives malicious users the opportunity to deteriorate the global aggregation. We adopt a reputation model based on beta distribution function to measure the credibility of local users, and propose a reputation-based scheduling policy with user fairness constraint. By taking into account the impact of wireless channel conditions and malicious attack features, we derive tractable expressions for the convergence rate of FL in a wireless setting. Moreover, we validate the superiority of the proposed reputation-based scheduling policy via numerical analysis and empirical simulations. The results show that the proposed secure wireless FL framework can not only distinguish malicious users from normal users but also effectively defend against several typical attack types featured in attack intensity and attack frequency. The analysis also reveals that the effect of average attack intensity on the convergence performance of FL is dominated by the percentage of malicious user equipments (UEs), and imposes even greater negative effect on the convergence performance of FL as the percentage of malicious UEs increases.

Anonymous Authentication and Key Agreement Scheme Combining the Group Key for Vehicular Ad Hoc Networks

Vehicular ad hoc network (VANET) is a multihop mobile wireless communication network that can realize many vehicle-related applications through multitop communication. In the open wireless communication environment, security and privacy protection are important contents of VANET research. The most basic method of VANET privacy protection is anonymous authentication. Even through, there are many existing schemes to provide anonymous authentication for VANETs. Many existing schemes suffer from high computational cost by using bilinear pairing operation or need the assistance of the trust authorities (TAs) during the authentication process or rely on an ideal tamper-proof device (TPD), which requires very strong security assumption. In this study, an anonymous authentication and key negotiation scheme by using private key and group key is proposed, which is based on pseudonym using the nonsingular elliptic curve. In this scheme, there is no third party trust center to participate in the authentication, there is no need to query the database, and there is no need of the local database to save the identity information of many vehicles, which reduce the storage space and the authentication time compared with other schemes. The proposed scheme only needs realistic TPDs. In the proposed scheme, TPDs do not need to preinstall the system key as many other schemes do; hence, the failure of a single TPD does not affect the security of the entire system. The security of the scheme is proved under the random oracle model. Compared with the related schemes using bilinear pairings, the computational cost and communication cost of the proposed scheme are reduced by 82% and 50%, respectively.

Performance evaluation of cooperative mobile communication security using reinforcement learning

In wireless networks, there are many channel impairments including shadowing, path loss, and fading. Due to the shadowing, path loss, and fading, the direct transmission between the sender and the receiver may not attain acceptable signal quality. In that case, the cooperative communication has shown attractive solutions because it can use an alternate route to the destination. Cooperative communication increases the stability of the channel by cooperative spatial diversity. Quite recently, the advancement in the cellular network has resulted in new security requirements and challenges. Cooperative communications can increase spectral efficiency, power efficiency, and reliability; however, it is often vulnerable to eavesdroppers. Hence, inspired by the need for safe wireless mobile networks, the objective of the research is to increase the secrecy capacity of the wireless networks when there are moving cooperative communication devices. The technique proposed to enhance the wireless network security is organized by reinforcement learning which learns the transmit parameters according to the interaction of the transmitter, receiver, relay-node, and the eavesdropper devices. The simulation results have shown that the proposed technique has enhanced the secrecy level of the legitimate receiver.

Real-Time Video Streaming and Control of Cellular-Connected UAV System: Prototype and Performance Evaluation

Unmanned aerial vehicles (UAVs) play an increasingly important role in military, public, and civilian applications, where providing connectivity to UAVs is crucial for its real-time control, video streaming, and data collection. Considering that cellular networks offer wide area, high speed, and secure wireless connectivity, cellular-connected UAVs have been considered as an appealing solution to provide UAV connectivity with enhanced reliability, coverage, throughput, and security. Due to the nature of UAVs mobility, the throughput, reliability and End-to-End (E2E) delay of UAVs communication under various flight heights, video resolutions, and transmission frequencies remain unknown. To evaluate these parameters, we develop a cellular-connected UAV testbed based on the Long Term Evolution (LTE) network with its uplink video transmission and downlink control&command (CC) transmission. We also design algorithms for sending control signal and controlling UAV. The indoor experimental results provide fundamental insights for the cellular-connected UAV system design from the perspective of transmission frequency, adaptability, and link outage, respectively.

An Energy-Efficient Compressed Sensing-Based Encryption Scheme for Wireless Neural Recording

This paper presents a compressed sensing (CS) based encryption scheme for wireless neural recording. An ultrahigh efficiency was achieved by leveraging CS for simultaneous data compression and encryption. CS enables sub-Nyquist sampling of neural signals by taking advantage of their intrinsic sparsity, while the CS process simultaneously encrypts the data with the sampling matrix being the cryptographic key. To share the key over an insecure wireless channel, we implemented an elliptic-curve cryptography (ECC) based key exchanging protocol. Local key shuffle and updating were adopted to eliminate the risks of potential information leakage. CS was executed in an application-specific integrated circuits (ASIC) fabricated in 180nm CMOS technology. Mixed-signal circuits were designed to optimize the power efficiency of the matrix-vector multiplication (MVM) of the CS operation. The ECC was implemented in a low-power Cortex-M0 based microcontroller (MCU). To be protected from timing attacks, the implementation avoided possible data-dependent branches. A wireless neural recorder prototype has been developed to demonstrate the proposed scheme. The prototype achieved an 8× data rate reduction and a 35× power saving compared with conventional implementation. The overall power consumption of ASIC and MCU was 442μW during the encrypted wireless transmission. The average correlated coefficient between the reconstructed signals and the uncompressed signals was 0.973, while the ciphertext-only attacks (CoA) achieved no better than 0.054 over 200,000 attacks. This work demonstrates a promising data compression and encryption scheme that can be used in a wide range of low-power signal recording systems with security requirements.

Wireless Sensor Network Design Using Multihop Based on Arduino and NRF24L01+

The development of communication networks is very useful in daily activities such as wireless data communication, monitoring and system security. In this case, a wireless sensor network technology is known, which is very suitable when applied to a system with a large number of nodes and spread over a large enough area at a low cost. This wireless sensor network is a wireless communication network that supports communication between sensor nodes in a considerable distance by placing several sensors in an area. Generally, this Wsn consists of a sensor node and a server node in the form of a personal computer. The data from the reading of the CO gas value will be sent directly from the sensor node to the node server. This device is built using the nRF24L01 module and the CO gas sensor using the MQ-7 sensor. This wireless sensor network communication system is built using multihop. From the activities it can be concluded that the success of sending data is influenced by the distance and number of nodes working on a topology, with the amount of data sent which is influenced by long distances and the large number of nodes, not all data is successfully received because of the large number of data collisions from each node.

Expectation Maximization Method for Effective Detection and Tracking of Object Using Machine Learning Technique for Secure Wireless Communication

Object detection is one of the most important computer vision tasks that is used synonymous to object recognition which comprises the mission of identifying the class of the object as well as locating its presence. The main difficulty in the recognition is that there is no single integrated system for detecting the shape or size of objects. Again, the difficulty still persists for the moving object detection due to the varying frames size and speed. Extracting the frames is a more trivial procedure. When frames are extracted the information about the true size, position, orientation of the moving object may be altered. Hence it necessitates to develop an automated object orientation, location identification algorithms to solve the above said problem. To avoid the above circumstances, the proposed work uses the machine learning technique with latest procedures containing different training parameters. This work concentrates on the procedures for the identification of an exact machine learning technique to train the features, which were extracted from the Expectation Maximization (EM) based segmentation process. Before segmentation intensity estimation and clustering procedures were implemented. The image obtained after preprocessing stages is segmented for generating the exemplars and given to a Back Propagation Neural network. Based on the proposed Intensity based clustering and EM based segmentation and feature extraction procedures, the moving object is detected. Hue, Saturation, Gradient Intensity values and GLCM features are extracted and Precision and Recall were used to evaluate the proposed algorithm. Precision was found to be 0.982, Recall is 0.876. accuracy of Back propagation was found to be 96.28%.The experimental results obtained in this proposed work proves the novelty in terms of the computational performance and detection performance.

Adaptive Detection of Direct-Sequence Spread-Spectrum Signals Based on Knowledge-Enhanced Compressive Measurements and Artificial Neural Networks.

The direct-sequence spread-spectrum (DSSS) technique has been widely used in wireless secure communications. In this technique, the baseband signal is spread over a wider bandwidth using pseudo-random sequences to avoid interference or interception. In this paper, the authors propose methods to adaptively detect the DSSS signals based on knowledge-enhanced compressive measurements and artificial neural networks. Compared with the conventional non-compressive detection system, the compressive detection framework can achieve a reasonable balance between detection performance and sampling hardware cost. In contrast to the existing compressive sampling techniques, the proposed methods are shown to enable adaptive measurement kernel design with high efficiency. Through the theoretical analysis and the simulation results, the proposed adaptive compressive detection methods are also demonstrated to provide significantly enhanced detection performance efficiently, compared to their counterpart with the conventional random measurement kernels.

Correction to: Opposition Based Joint Grey Wolf‑Whale Optimization Algorithm Based Attribute Based Encryption in Secure Wireless Communication

Correction to: Opposition Based Joint Grey Wolf‑Whale Optimization Algorithm Based Attribute Based Encryption in Secure Wireless Communication

Analysis and application of endogenous wireless security principle for key generation

The open and broadcast nature of wireless channels leads to the inherent security problem of information leakage in wireless communication. We can utilize endogenous security functions to resolve this problem. The fundamental solution is channel-based mechanisms, like physical layer secret keys. Unfortunately, current investigations have not fully exploited the randomness of wireless channels, making secret key rates not high. Consequently, user data can be encrypted by reducing the data rate to match the secret key rate. Based on the analysis of the endogenous wireless security principle, we proposed that the channel-based endogenous secret key rate can nearly match the maximum data rate in the fast-fading environments. After that, we validated the proposition in an instantiation system with multiple phase shift keying (MPSK) inputs from the perspectives of both theoretical analysis and simulation experiments. The results indicate that it is possible to accomplish the onetime pad without decreasing the data rate via channel-based endogenous keys. Besides, we can realize high-speed endogenously secure transmission by introducing independent channels in the domains of frequency, space, or time. The conclusions derived provide a new idea for wireless security and promote the application of the endogenous security theory.

A Security Defect Diagnosis Method of Wireless Network based on Modal Symmetry Algorithm

In order to enhance the security of wireless networks and enhance the ability of data acquisition, processing and transmission, the security defects of wireless networks are diagnosed based on the modal symmetry algorithm. According to the amplitude of the defective signals collected by wireless network sensors, the average value of the signals collected by the centrosymmetric sensors is linearly subtracted, and the asymmetric modal information and the asymmetric modal amplitude of the axial position of wireless networks are obtained. On the basis of the original defect vibration signal graded by variational mode, several eigenmode components are obtained, and then the ranking entropy of each modal component is calculated. The ranking entropy is input as eigenvector to support vector machine classifier to complete the classification and recognition of wireless network security defects. The experimental results show that this method can accurately diagnose the security defects of wireless networks in different locations. The more complex the wireless network is, the higher the accuracy of the diagnosis results is and the shorter the time consuming results are. After the defect diagnosis, the wireless network data acquisition, data processing and transmission capabilities have been enhanced.

Formal security proof for a scheme on a topological network

Key assignment and key maintenance in encrypted networks of resource-limited devices may be a challenging task, due to the permanent need of replacing out-of-service devices with new ones and to the consequent need of updating the key information. Recently, Aragona et al. proposed a new cryptographic scheme, ECTAKS, which provides a solution to this design problem by means of a Diffie-Hellman-like key establishment protocol based on elliptic curves and on a prime field. Even if the authors proved some results related to the security of the scheme, the latter still lacks a formal security analysis. In this paper, we address this issue by providing a security proof for ECTAKS in the setting of computational security, assuming that no adversary can solve the underlying discrete logarithm problems with non-negligible success probability.

Users’ attitude on perceived security of enterprise systems mobility: an empirical study

Purpose This study/ paper aims to empirically examine the user attitude on perceived security of enterprise systems (ES) mobility. Organizations are adopting mobile technologies for various business applications including ES to increase the flexibility and to gain sustainable competitive advantage. At the same time, end-users are exposed to security issues when using mobile technologies. The ES have seen breaches and malicious intrusions thereby more sophisticated recreational and commercial cybercrimes have been witnessed. ES have seen data breaches and malicious intrusions leading to more sophisticated cybercrimes. Considering the significance of security in ES mobility, the research questions in this study are: What are the security issues of ES mobility? What are the influences of users’ attitude towards those security issues? What is the impact of users’ attitude towards security issues on perceived security of ES mobility? Design/methodology/approach These questions are addressed by empirically testing a security model of mobile ES by collecting data from users of ES mobile systems. Hypotheses were evolved and tested by data collected through a survey questionnaire. The questionnaire survey was administered to 331 users from Chinese small and medium-sized enterprises (SME). The data was statistically analysed by tools such as correlation, factor analysis, regression and the study built a structural equation model (SEM) to examine the interactions between the variables. Findings The study results have identified the following security issues: users’ attitude towards mobile device security issues; users’ attitude towards wireless network security issues; users’ attitude towards cloud computing security issues; users’ attitude towards application-level security issues; users’ attitude towards data (access) level security issues; and users’ attitude towards enterprise-level security issues. Research limitations/implications The study results are based on a sample of users from Chinese SMEs. The findings may lack generalizability. Therefore, researchers are encouraged to examine the model in a different context. The issues requiring further investigation are the role of gender and type of device on perceived security of ES mobile systems. Practical implications The results show that the key security issues are related to a mobile device, wireless network, cloud computing, applications, data and enterprise. By understanding these issues and the best practices, organizations can maintain a high level of security of their mobile ES. Social implications Apart from understanding the best practices and the key issues, the authors suggest management and end-users to work collaboratively to achieve a high level of security of the mobile ES. Originality/value This is an empirical study conducted from the users’ perspective for validating the set of research hypotheses related to key security issues on the perceived security of mobile ES.

Overloaded Wireless MIMO Switching for Information Exchanging through Untrusted Relay in Secure Wireless Communication

Overloaded Wireless MIMO Switching for Information Exchanging through Untrusted Relay in Secure Wireless Communication

FSS Design for Improving Transmission of Microwave Signals and Wireless Security in Modern Buildings

A fractal frequency selective surface (FSS) has been presented for hard coated energy saving glass (ESG) used in modern building architecture. Without FSS, the presence of coating on ESG surface blocks the transmission of useful radio frequency (RF)/microwave signals. The FSS consists of two self-similar cross dipole elements designed in the coating to provide a low-pass response from 0 GHz to 2.1 GHz with two additional band-stop responses at 2.45 GHz and 5.25 GHz. An average transmission loss of less than 2 dB has been achieved in the low-pass band while attenuations of 36 dB and 30 dB have been achieved for 2.45 GHz and 5.25 GHz wireless local area network (WLAN) bands, respectively, providing required security. The low-pass response improves the transmission of useful RF/microwave signals. However, the amount of removed coating due to FSS design is relatively higher, but heat loss has been minimized by pasting an inexpensive thin solar film on the back side of glass. This thin film has provided additional thermal insulation with almost no blockage to transmission of useful RF/microwave signals. A detailed parametric analysis has been done and their effect on FSS structure has been described. An equivalent circuit model has also been presented for the proposed FSS structure. A finite prototype containing 7 × 7 elements have been constructed and evaluated. The measured results have been found to be in good agreement with the simulated results. The proposed FSS design is an excellent candidate for WLAN security.

Cellular Automata based Cryptography Model for Reliable Encryption Using State Transition in Wireless Network Optimizing Data Security

Authors propose a hardware based approach for reliable encryption in wireless network using Cellular Automata (CA). Distinct layers of encryption have been utilized in proposed model for enhancing data security. Transmitter and receiver modules are designed for performing state transition based encrypted activities. Transmitter module is required for capturing environmental turbulences (noise) from a specific geographical location and send encrypted signal to receiver module through wireless network. Receiver module analyses received signal after decryption for desired activities based on real time situations. Different hardware components are selected and compared based on market study targeting efficient construction of proposed modules. Time complexity and code break complexity are measured using different key lengths, keysets, and data sizes for proposed CA based encryption scheme achieving unique results in hardware based cryptography system. Encryption key length, index, and keyset are required for computing code break complexity in design model. Large data size is effectively managed to calculate protection ratio and reliability factor for realizing efficient protectiveness and accuracy. Comparative study between existing encryption technique and proposed CA based encryption technique is established based on time complexity and code break complexity.

Opposition Based Joint Grey Wolf-Whale Optimization Algorithm Based Attribute Based Encryption in Secure Wireless Communication

At present times, medical image security becomes a hot research topic in the healthcare sector. This paper presents an efficient lightweight image encryption model based on the Dynamic key generating Attribute based encryption (ABE) method with Opposition based joint Grey Wolf-Whale Optimization Algorithm (OjGW-WOA). The proposed encryption method undergoes certain pre-encryption steps like rotation and random column addition steps. Once the pre-encryption steps are done, ABE with OjGW-WOA is incorporated, where the optimal key is generated based on entropy value. In addition, the oppositional based learning concept is introduced to enhance the convergence rate and searching process of GWO and WOA algorithms. Next, the proposed encryption method is designed with a dynamic key generating model that generates updated keys during every time period. Therefore, during decryption, two-level key verification is done. At the first decryption stage, the key corresponding to that particular time period is required, then the original key is generated from that key and then employed for decrypting the original data. The proposed method is simulated using MATLAB tool and a detailed comparative results analysis is carried out. The performance of the proposed work is validated with the aid of performance metrics like Peak Signal to Noise Ratio (PSNR), number of changing pixel rate (NPCR) and unified averaged changed intensity (UACI). The experimental results stated that the presented model has resulted to a higher PSNR of 62.29 dB, NPCR of 99.23%, and UACI of 23.67%.

Smart Navigation with Static Polygons and Dynamic Robots

Due to the last increase in data and information technology, the need to use robots in many life areas is increased. There is a great diversity in this field, depending on the type of task required, as the robot enters the parcels of air, land, and water. In this paper, a robot's mission designed to move things is concentrated, relying on line-tracing technology that makes it easy to track its path safely, the RFID is distributed in its approach. When the robot reads the RFID tag, it stops until it raises the load from above, the robot continues its path toward the target. When an obstacle obstructs the robot path, the robot deviates and returns after a while to its previous approach. All this technology is implemented using a new algorithm which is programmed using the visual basic program. The robot designed to transfer the stored material is used according to a site known as an identifier that is identified by the RFID value, where the robot is programmed through a microcontroller and a unique store program that determines the current location and the desired location, then is given the task for the robot to do it as required. The robot is controlled using an ATmega controller to control other parts connected to the electronic circuit, the particular infrared sensor, and ultrasound to avoid potential obstacles within the robot's path to reach the target safely. In addition to this, the robot is made up of an RFID sensor to give unique to each desired target site. Through the console, it is possible to know the link indicated by the target. The H-bridge is also used to obtain a particular command and guide the robot as needed to move freely in all directions and a DC motor which is unique for moving wheels at the desired speed, and Bluetooth for programmable and secure wireless transmission and reception with all these parts through a unique program that also uses application inventory. The robot has proven to be a great success in performing the required task through several tests that have been practically performed.