Wireless Security Research Articles

PMCDM: Privacy-preserving multiresolution community detection in multiplex networks

Multiplex networks can effectively represent network data with communications generated by sensors across multiple platforms in Internet of Things (IoTs). Multiresolutional community detection (MCD) in multiplex networks is essential to understanding the functional modules of complex systems in IoTs, consequently the studies on MCD have attracted much attention in recent years. However, most existing works require full access to the communications of systems in IoTs, which are sensitive and private. To overcome this requirement, in this paper, we propose a privacy-preserving MCD framework (called PMCDM) for multiplex networks, aiming to detect the community structures at multiple resolution levels while preserving the link and weight privacy of the systems in IoTs. PMCDM first encrypts the sensitive link and weight information of multiplex networks using the differential privacy and homomorphic encryption techniques, respectively, and subsequently devises a multi-greedy algorithm (called DH-Louvain) for MCD on the encrypted networks by optimizing a weighted modularity density. Extensive experiments on both the eleven LFR benchmark and the ten real-world multiple networks show that PMCDM can effectively detect the multiresolutional community structures of these networks while preserving the network privacy.

Simultaneous and independent control of phase and polarization in terahertz band for functional integration of multiple devices

The control of phase and polarization in terahertz (THz) range is very valuable for wireless communication, biomedicine, and security inspection. Recently, metasurfaces composed of sub-wavelength artificial structures are proposed for the control of THz waves. However, it is still a challenge to realize simultaneous and independent control of the wavefront and polarization distribution in the THz band, although which has been achieved in the optical band by using several metasurfaces. Here, metallic waveguide arrays (MWAs) are proposed to manipulate both the wavefront of two orthogonal polarization components and the phase difference between them so as to attain independent spatial distributions of the phase and polarization direction. By using the compact MWAs, the functional integration of multiple THz devices is attained, including the integration of a lens with a quarter-wave plate, a half-wave plate, and vector beam generators, respectively. The corresponding control efficiency can even be comparable with that of a commercial lens just for THz focusing. The functional integration of multiple devices makes the MWAs very significant in promoting the miniaturization of THz systems and reducing the insertion loss of functional devices, owing to the remarkable decrease of the number and size of required devices.

Considerations for Radio Frequency Fingerprinting across Multiple Frequency Channels.

Radio Frequency Fingerprinting (RFF) is often proposed as an authentication mechanism for wireless device security, but application of existing techniques in multi-channel scenarios is limited because prior models were created and evaluated using bursts from a single frequency channel without considering the effects of multi-channel operation. Our research evaluated the multi-channel performance of four single-channel models with increasing complexity, to include a simple discriminant analysis model and three neural networks. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models can lead to a deterioration in performance from MCC > 0.9 (excellent) down to MCC < 0.05 (random guess), indicating that single-channel models may not maintain performance across all channels used by the transmitter in realistic operation. We proposed a training data selection technique to create multi-channel models which outperform single-channel models, improving the cross-channel average MCC from 0.657 to 0.957 and achieving frequency channel-agnostic performance. When evaluated in the presence of noise, multi-channel discriminant analysis models showed reduced performance, but multi-channel neural networks maintained or surpassed single-channel neural network model performance, indicating additional robustness of multi-channel neural networks in the presence of noise.

Optimization of a Deep Learning Algorithm for Security Protection of Big Data from Video Images.

With the rapid development of communication technology, digital technology has been widely used in all walks of life. Nevertheless, with the wide dissemination of digital information, there are many security problems. Aiming at preventing privacy disclosure and ensuring the safe storage and sharing of image and video data in the cloud platform, the present work proposes an encryption algorithm against neural cryptography based on deep learning. Primarily, the image saliency detection algorithm is used to identify the significant target of the video image. According to the significant target, the important region and nonimportant region are divided adaptively, and the encrypted two regions are reorganized to obtain the final encrypted image. Then, after demonstrating how attackers conduct attacks to the network under the ciphertext attack mode, an improved encryption algorithm based on selective ciphertext attack is proposed to improve the existing encryption algorithm of the neural network. Besides, a secure encryption algorithm is obtained through detailed analysis and comparison of the security ability of the algorithm. The experimental results show that Bob's decryption error rate will decrease over time. The average classification error rate of Eve increases over time, but when Bob and Alice learn a secure encryption network structure, Eve's classification accuracy is not superior to random prediction. Chosen ciphertext attack-advantageous neural cryptography (CCA-ANC) has an encryption time of 14s and an average speed of 69mb/s, which has obvious advantages over other encryption algorithms. The self-learning secure encryption algorithm proposed here significantly improves the security of the password and ensures data security in the video image.

A Low-Power, High-Bandwidth Wireless Communication System for Industrial IoT Applications

In anticipation for an automated future, the Internet of Things (IoT) has rapidly connected more gadgets. Thus, IoT applications' performance requirements present new challenges. Power consumption, service quality, localization, security, and exact wireless channel propagation modelling and characterization are potential issues. When connecting separate sensors wirelessly, the latter is crucial. Channel modelling varies by location because environmental factors affect wireless signal range and quality. Wireless communication technologies are widely used for disaster victim and responder tracking and machine health monitoring in networked manufacturing. Data communication in such systems must be real-time or risk financial losses or human lives. Facilitating real-time medium access via license-free bands in uncontrolled situations is difficult because all communicating stations must be synchronized. (real and nonreal-time). In open communication, medium access protocols cannot filter out unmonitored station traffic.Real-time data collection and analysis improve system efficiency, preventative maintenance, and energy savings. Modulation systems, antenna designs, and power management are just a few of the various ways that must be considered throughout system design and development. IIoT applications also have power, security, and dependability issues. A Low-Power, High-Bandwidth Wireless Communication System for Industrial IoT Applications has a bright future thanks to artificial intelligence and machine learning, 5G networks, new low-power communication technologies, improved security, and blockchain technology. Without this technology, IIoT growth is impossible.

MDOPE: Efficient multi-dimensional data order preserving encryption scheme

Nowadays, tremendous information technology industries resort to cloud servers to store data with an outsourcing approach to extend their storage and computation power. This, however, also leads to privacy and security issues of unprotected data against curious cloud servers. The most common solution currently is to encrypt the data before uploading it. The problem is that encrypted data is out of control and users also cannot transfer the searching job to cloud serves anymore. Specifically, the order preserving encryption (OPE) provides an efficient solution to the order of plaintexts. Existing OPE schemes focus on single-dimensional data, and fail to effectively process multi-dimensional data. In this paper, we propose a multi-dimensional data order preserving encryption scheme MDOPE allowing fine-grained multi-dimensional range queries. Our scheme constructs query indexes for each dimension of the data based on the order preserving encryption network. In particular, the proposed scheme ensures that no external entity, including the cloud server, can obtain additional information other than the order of ciphertexts during the whole query process.

Improving Physical Layer Security in IRS-Aided WPCN Multicast Systems via Stackelberg Game

This paper investigates an intelligent reflecting surface (IRS) aided secure wireless powered communication network (WPCN), where a transmitter first harvests energy from a power station (PS), and then uses the collected energy to transmit information to multiple internet of things (IoT) devices in the form of multicast in the presence of multiple eavesdroppers. An IRS is deployed to enhance the efficiency of wireless energy transfer (WET) and secure wireless information transfer (WIT). Considering that the PS and transmitter belong to different service providers, we model this energy interaction through a Stackelberg game and propose an IRS-aided energy trading and secure communication (IRS-ETSC) scheme, in which the transmitter needs to pay an energy price as an incentive for the PS energy service. Specifically, the transmitter as the leader can control the energy price, WET time, two-stage phase shifts, and beamforming vector, while the PS as the follower can adjust the transmit power. To solve the non-convex leader game problem, we propose a two-step approach to decompose the original problem into two subproblems. The first subproblem can be solved independently by an efficient alternating optimization (AO) based algorithm, in which the closed-form optimal beamforming vector and energy phase shifts are alternately optimized. Then, the second subproblem is relaxed by semidefinite relaxation (SDR) and solved by an iterative algorithm based on block coordinate descent (BCD), where the optimal energy price, optimal WET time, and suboptimal information phase shifts can be obtained by golden section method and successive convex approximation (SCA) respectively. Both subproblems can converge to a stationary point. Numerical results show that compared with the traditional non-IRS scheme, the proposed IRS-ETSC scheme achieves utility improvement for both the PS and transmitter.

Intelligent Prediction and Rural Financial Development Based on Abnormal Detection of Sensor Data.

Wireless sensor network is a multisensor wireless network system, which consists of multiple sensors and is configured independently. Because the network generates a large amount of data, the frequency, performance, and computing power of sensor nodes are limited, and they are particularly vulnerable to harsh environments and malicious attackers. This leads to the occurrence of malicious nodes, emergencies, and abnormal data in the sensor network system. Failures can also have a significant impact on sensor network services. The two main functions of wireless sensor network security are abnormal node detection and data anomaly detection. These two directions are mutually independent and complementary. Therefore, under the promotion of the rural revitalization strategy and the precision poverty alleviation strategy, China has increased its agricultural efforts. At this stage, all localities focus on the construction of rural financial systems to ensure that scattered farmers and rural small and micro-enterprises receive comprehensive financial services. The establishment of a rural financial system based on “intelligent forecasting” can improve financial development theories and build new ideas for rural financial development. And, the balance between realization and profitability, and then, through the use of Internet technology to make traditional financial institutions more effective in providing financial services, new online financial platforms can use them to make up for the existing shortcomings of traditional financial institutions as much as possible. In this article, through the research on the intelligent prediction of sensor data anomaly detection, it is applied to the development of rural finance and promotes the development of rural finance.

Lightweight and High-Performance Data Protection for Edge Network Security

To strengthen the security of edge network data and reduce network latency, in this paper, we combine an advanced reduced instruction set computing machine (ARM) and a field programmable gate array (FPGA) to propose a lightweight ARM-FPGA computing architecture for edge network data security protection and acceleration. Firstly, the access control lists are set through FPGA to authorize and filter illegal data, thereby reducing the transmission and processing of invalid data on the network. Secondly, based on the principles of dynamization, diversification, and randomization, the initial random key is generated using a pseudo-random number generator and a scrambling factor, and the hash of the data packet value updates the key to ensure “one frame, one key.” Then, an ARM microprocessor is used to monitor the working status of the system in real-time. If an abnormality is found, different disturbance factors are activated using key management to change the system running status and restore the stability of the system. Finally, pipeline technology and critical path optimization on FPGA are used to parallelize the underlying encryption algorithm and data compression algorithm to achieve high-speed memory communication and meet the performance requirements of different networks. The experimental and analysis results show that the computing architecture designed in this paper has high network encryption performance and can effectively prevent data leakage. In addition, the effectiveness of the architecture in terms of network delay and network load is verified.

6G Technologies – How Can It Help Future Green Business Model Innovation

In the last few years businesses have been motivated and pushed by governments and global society on innovating and developing Green Business Models. However, Reconfiguring, designing and developing green business models to become efficient and valuing Green Business Models have shown to be much more complex than expected. It includes balancing monetary and non monetary value formulas of business models in symbiosis. Not just for the single business – but for businesses in their entire value network. This includes security challenges related to securing that green business models really are green – and not based on greenwashing. As green business models demand in long term perspective a very open business model innovation approach, it calls for stronger and new security technologies. Protection of IPR’s of Business Models and businesses competences, so they are not one to one copied with out giving value back to “the Business Model designer” and the rightful original owner of the business models is a major security challenge related to green business models. Green Business Models and Green business Model Innovation calls therefore for new and more advanced security approach, technologies and understanding. Previous business model innovation security practice and systems cannot fully offer these solutions – but 6G of wide-area wireless security technologies – as an umbrella – gives hope and can potentially play major role with new security technologies supported by AI, AR and blockchain technologies. This evolvement is highly and urgent needed to support the success of our society’s green transformation. The paper document through Nordic green business model cases some of the above mention security challenges that green business models and green business model innovation stand in front of and need to innovate solutions for. The paper discuss and propose how 6G and related technologies could help.

The role of artificial intelligence and machine learning in wireless networks security: principle, practice and challenges

The role of artificial intelligence and machine learning in wireless networks security: principle, practice and challenges

A Secure and Efficient Wireless Charging Scheme for Electric Vehicles in Vehicular Energy Networks

To address the limited driving range of electric vehicles (EVs) and promote EVs’ penetration, vehicular energy networks (VENs) have emerged and opened possibility to charge EVs in motion via dynamic wireless power transfer (DWPT) technology. However, security and efficiency concerns arise due to the untrusted operating environment and EVs’ selfish charging/discharging behaviors. Existing trust models rely on the personal recommendations from neighboring EVs to identify malicious entities in VENs, which may cause potential privacy breaches and data misuse for recommenders. Besides, it is challenging to optimally schedule EVs’ energy behaviors by considering complex interactions among three energy entities (i.e., energy nodes, charging EVs, and discharging EVs). To this end, by leveraging blockchain technology and game theory, this paper proposes a secure and efficient wireless charging scheme to address these issues in VENs. Firstly, a blockchain-based fine-grained access control mechanism with traceability and auditability is presented to enable EV users to fully control and audit their personal rating data usage during trust management by logging data activities and issuing access tokens into decentralized ledgers. In this manner, the privacy of recommenders can be preserved by fully controlling the access and usage of personal rating data. Furthermore, by introducing cooperative wireless energy transfer mode, a hierarchical game-based energy scheduling algorithm is developed to optimize the strategies of three energy parties tier by tier, while considering their cooperation and competition. Finally, extensive simulations are conducted, which demonstrate that the proposed scheme can effectively improve users’ utility and security of energy transmission for EVs, compared with existing representative approaches.

Active Reconfigurable Intelligent Surface Aided Secure Transmission

Reconfigurable Intelligent Surface (RIS) draws great attentions in academic and industry due to its passive and low power consumption nature, and has currently been used in physical layer security to enhance the secure transmission. However, due to the existence of “double fading” effect on the reflecting channel link between transmitter and user, RIS helps achieve limited secrecy performance gain compared with the case without RIS. In this correspondence, we propose a novel active RIS design to enhance the secure wireless transmission, where the reflecting elements in RIS not only adjust the phase shift but also amplify the amplitude of signals. To solve the non-convex secrecy rate optimization based on this design, an efficient alternating optimization algorithm is proposed to jointly optimize the beamformer at transmitter and reflecting coefficient matrix at RIS. Simulation results show that with the aid of active RIS design, the impact of “double fading” effect can be effectively relieved, resulting in a significantly higher secrecy performance gain compared with existing solutions with passive RIS and without RIS design.

Door Lock Security System Using Recent Technology

Abstract: In terms of house security, the door is pivotal. To keep the hearthstone secure, the proprietor will keep the door locked at all times. Still, owing to a rush when leaving the house, the proprietor may forget to lock the door, or they may be doubtful if they’ve closed the door or not. Wireless security grounded operation have fleetly increased due to the dramatic enhancement of ultramodern technologies. Numerous access control systems were designed and/or enforced grounded on different types of wireless communication technologies by different people. Radio Frequency identification (RFID) is a contactless technology that’s extensively used in several diligences for tasks like access control system, book shadowing in libraries, tollgate system, forced chain operation, and so on. For enforcing this design, we will be using Arduino mega 2560 pro mini, a fingerprint sensor, Keypad module. ESP-32 CAM module, RFID sensor, solenoid lock and ESP8266. We have also created an application for monitoring and controlling the security features of the door lock. We can also open the door through mobile fingerprint. Keywords: Arduino mega 2560 pro mini, ESP32-CAM, ESP8266, Fingerprint sensor, Keypad module, RFID sensor.

A Network Communication Frequency Routing Protocol of Coal Mine Safety Monitoring System Based on Wireless Narrowband Data Communication Network

In recent years, the coal industry has been expanding the scale and output of coal mining in China, yet the safety in production is faced with great challenge. Communication system in coal mines plays a significant role in production safety, and wireless narrowband data communication network technology is a new-type advantageous measure to construct wireless network security monitoring system for coal mining. Here, a coal mine monitoring signal transmission method based on bus technology and wireless data transmission technology suitable for coal mines is proposed. The corresponding monitoring system is designed, and the system is able to collect the gas concentration and mechanical operation status of the mines. Wireless sensor network nodes are used for the RF communication module. The communication performance of this system in coal and rock medium and the roadway along the goaf is simulated, and the quantitative relationship between the attenuation coefficient of different communication frequencies and the effective communication distance is obtained. Hence, the results show that the protocol has good performance in terms of route establishment, maintenance, and data transmission hop count for the positioning of coal mine employees.

Analysis and Evaluation of Wireless Network Security with the Penetration Testing Execution Standard (PTES)

The use of computer networks in an agency aims to facilitate communication and data transfer between devices. The network that can be applied can be using wireless media or LAN cable. At SMP XYZ, most of the computers still use wireless networks. Based on the findings in the field, it was found that there was no user management problem. Therefore, an analysis and audit of the network security system is needed to ensure that the network security system at SMP XYZ is safe and running well. In conducting this analysis, a tool is needed which will be used as a benchmark to determine the security of the wireless network. The tools used are Penetration Testing Execution Standard (PTES) which is one of the tools to become a standard in analyzing or auditing network security systems in a company in this case, namely analyzing and auditing wireless network security systems. After conducting an analysis based on these tools, there are still many security holes in the XYZ wireless SMP that allow outsiders to illegally access and obtain vulnerabilities in terms of WPA2 cracking, DoS, wireless router password cracking, and access point isolation so that it can be said that network security at SMP XYZ is still not safe

LT Codes with Double Encoding Matrix Reorder Physical Layer Secure Transmission

In traditional wireless sensor networks, information transmission usually uses data encryption methods to prevent information from being stolen illegally. However, once the encryption methods are leaked, eavesdropping nodes can easily obtain information. LT codes are rateless codes; if it is attacked by random channel noise, the decoding process will change and the decoding overhead will also randomly change. When it is used for physical layer communication of wireless sensor networks, it ensures that the destination node recovers all the information without adding the key, while the eavesdropping node can only obtain part of the information to achieve wireless information security transmission. To reduce the intercept efficiency of eavesdropping nodes, a physical layer security (PLS) method of LT codes with double encoding matrix reorder (DEMR-LT codes) is proposed. This method performs two consecutive LT code concatenated encoding on the source symbol, and part of the encoding matrix is reordered according to the degree value of each column from large to small, which reduces the probability of eavesdropping nodes recovering the source information. Experimental results show that compared with other LT code PLS schemes, DEMR-LT codes only increase the decoding overhead by a small amount. However, it can effectively reduce the intercept efficiency of eavesdropping nodes and improve information transmission security.

The COVID-19 pandemic and remote working did not improve WLAN security

In this article, we present an analysis of the COVID-19 pandemic’s effects on Wireless Local Area Network (WLAN) security and abundance in Southwest Finland. We hypothesised that the drastic increase in telecommuting caused by the pandemic would encourage many to update obsolete WLAN devices, improving the state of WLAN security and increasing WLAN deployment in the survey region. To test our hypotheses, data from seven WLAN surveys carried out between February 2020 and October 2021 was analysed. Surprisingly, although the results show a 50.2% increase in WLAN deployment during the second and fourth waves of the pandemic, this had no significant effect on WLAN security in the survey region. The survey data shows little change in the number of unencrypted networks and networks configured with vulnerable encryption protocols. While most of the located networks were encrypted with the secure WPA2 protocol, the number of networks configured with the newest WPA3 has not notably increased.

Safe Exploration in Wireless Security: A Safe Reinforcement Learning Algorithm With Hierarchical Structure

Most safe reinforcement learning (RL) algorithms depend on the accurate reward that is rarely available in wireless security applications and suffer from severe performance degradation for the learning agents that have to choose the policy from a large action set. In this paper, we propose a safe RL algorithm, which uses a policy priority-based hierarchical structure to divide each policy into sub-policies with different selection priorities and thus compresses the action set. By applying inter-agent transfer learning to initialize the learning parameters, this algorithm accelerates the initial exploration of the optimal policy. Based on a security criterion that evaluates the risk value, the sub-policy distribution formulation avoids the dangerous sub-policies that cause learning failure such as severe network security problems in wireless security applications, e.g., Internet services interruption. We also propose a deep safe RL and design four deep neural networks in each sub-policy selection to further improve the learning efficiency for the learning agents that support four convolutional neural networks (CNNs): The Q-network evaluates the long-term expected reward of each sub-policy under the current state, and the E-network evaluates the long-term risk value. The target Q and E-networks update the learning parameters of the corresponding CNN to improve the policy exploration stability. As a case study, our proposed safe RL algorithms are implemented in the anti-jamming communication of unmanned aerial vehicles (UAVs) to select the frequency channel and transmit power to the ground node. Experimental results show that our proposed schemes significantly improve the UAV communication performance, save the UAV energy and increase the reward compared with the benchmark against jamming.

Feasibility Study for Well pattern Encryption in Complex Fractured Block Reservoirs--Taking the Liu 90 South Fault Block in the Jidong Oilfield as an example

Jidong oilfield belongs to complex fault block reservoir, and the development has now entered into high water-cut stage. when using Well pattern encryption technology to stabilize production, it is necessary to study the feasibility of Well pattern encryption to ensure a better economic benefit. In this paper, we use theoretical analysis method, consider the influence of oil price on the calculation, improve the economic limit Well pattern density calculation formula, calculate the economic limit Well pattern density under different recovery rates, make recovery rate prediction for different Well pattern density scenarios by combining with Sherkachov's formula, and use the curve intersection method to determine the Well pattern density at the break-even point, so as to determine the economic feasibility of Well pattern encryption. The example calculations show that the use of well network encryption alone does not meet the development requirements of the Liu 90 South block and has no significant economic benefits, so a combination of two-three methods is needed to further improve the recovery rate. Numerical simulation prediction results show that the two-three combination method can improve the recovery rate by 14.54%, accumulate 28.88×104t of oil increase and increase revenue by 678,245,000 yuan.