Physical Layer Information Research Articles

A practical regular LDPC coded scheme for physical-layer information security

A practical regular LDPC coded scheme for physical-layer information security

A Reliable Physical Layer Key Generation Scheme Based on RSS and LSTM Network in VANET

With the rapid development of information and communication technology, Vehicular AD hoc Networks (VANET) has attracted more and more attention. In order to provide traffic safety services, vehicles frequently share information related to road traffic, such as vehicle motion data and traffic flow data. Reliable key generation is the basis of VANET security system construction. At present, most key generation schemes rely on a trusted third-party, so there are security risks. Traditional key agreement protocols have high overhead, and is not suitable for the latency-sensitive requirements of VANET. The physical layer security technology extracts the fingerprint of the wireless channel and the identity of the device, and generates the key quickly and in real time without the third party distribution. A physical layer key generation scheme based on Received Signal Strength (RSS) is proposed to realize Vehicle-to-Vehicle (V2V) secure communications. Firstly, a network model based on Long Short-Term Memory (LSTM) network and Kalman Filtering is proposed to effectively enhance the reciprocity of physical layer information in dynamic environment. Secondly, a lossless quantization scheme is proposed, which achieves a lower bit disagreement rate and a higher bit generation rate. Thirdly, the inconsistent bits are corrected by fuzzy extractor, the confidentiality of the key exchange process is enhanced by zero knowledge proof, and the security of the key is improved by using hash function for privacy amplification. Finally, the experimental results show that the proposed scheme has great improvements in data correlation, bit disagreement rate, bit generation rate and bit distribution randomness.

Weighted Voting in Physical Layer Authentication for Industrial Wireless Edge Networks

Edge computing (EC) is an essential component of large-scale intelligent manufacturing systems for Industry 4.0, which promises to provide a pre-processing platform for the massive data generated by the terminals and guarantee lower delay and more security compared to directly processing data in cloud computing. Nevertheless, access authentication is a crucial security issue of current EC systems, and thus this paper presents a solution to enhance the access authentication accuracy by exploiting the physical layer information. Our method employs a weighted voting scheme for channel state information (CSI) based authentication using a single sample which include sample segmentation, grouping, and weighted voting, and finally achieves the fast and low complexity secure-access requirement of the EC system without increasing the individual devices' sample size and computational complexity. Experimental results utilizing public datasets and field-measured datasets demonstrate that the proposed weighted voting method has higher accuracy and robustness than existing methods.

Eliminating the Barriers: Demystifying Wi-Fi Baseband Design and Introducing the PicoScenes Wi-Fi Sensing Platform

The research on Wi-Fi sensing has been thriving over the past decade but the process has not been smooth. Three barriers always hamper the research: 1) unknown baseband design and its influence; 2) inadequate hardware; and 3) the lack of versatile and flexible measurement software. This article tries to eliminate these barriers through the following work. <i>First</i>, we present an in-depth study of the baseband design of the Qualcomm Atheros AR9300 (QCA9300) NIC. We identify a missing item of the existing channel state information (CSI) model, namely, the CSI distortion, and identify the baseband filter as its origin. We also propose a distortion removal method. <i>Second</i>, we reintroduce both the QCA9300 and software-defined radio (SDR) as powerful hardware for research. For the QCA9300, we unlock the arbitrary tuning of both the carrier frequency and bandwidth. For SDR, we develop a high-performance software implementation of the 802.11a/g/n/ac/ax baseband, allowing users to fully control the baseband and access the complete physical-layer information. <i>Third</i>, we release the PicoScenes software, which supports concurrent CSI measurement from multiple QCA9300, Intel Wireless Link (IWL5300), and SDR hardware. PicoScenes features rich low-level controls, packet injection, and software baseband implementation. It also allows users to develop their own measurement plugins. <i>Finally</i>, we report state-of-the-art results in the extensive evaluations of the PicoScenes system, such as the &#x003E;2-GHz available spectrum on the QCA9300, concurrent CSI measurement, and up to 40 and 1 kHz CSI measurement rates achieved by the QCA9300 and SDR. PicoScenes is available at <uri>https://ps.zpj.io</uri>.

Cross layer design with weighted sum approach for extending device sustainability in smart cities

IoT associates with MEMS technology and various other technologies to connect smart devices globally. Providing reliable interaction between the smart devices and maintaining the battery sustainability of smart devices are the major demand since most of the IoT devices are run by a battery source. Device sustainability is the prime concern in most the IoT applications such as smart cities, e-health, smart grid, etc. Thus, we have come up with a cross layer design that improves the device sustainability and lifetime of the IoT networks in smart cities. In the proposed design, physical layer and data link layer information is utilized by the network layer to explore the energy efficient communication among the IoT devices, since 70% - 80% of device energy is utilized for its communication. Cross-layer design can be an optimal solution to enhance the modalities of the wireless network. The Weighted sum approach is used in the proposed model which is an effective computation method to analyze and identify the routing metrics that are associated with energy efficiency. Based on the routing metric analysis (Table 2) it is found that a particular combination of routing metrics performs effective power utilization (by attaining optimal transmission power) and achieves sustained device lifetime. From the obtained results, it is noticed that the MTPM + ETP + ND routing metric combination outperforms all the other combinations, and designing the cross-layer mechanism with the weighted sum approach computation gives better network performance without compromising the device lifetime. In smart cities applications, the device scalability is huge, since frequent battery replacement is a very difficult task. Therefore, we come up with an efficient network model that is more suitable to maintain device sustainability in smart cities.

SecurePilot: Improving Wireless Security of Single-Antenna IoT Devices

With the arrival of the Internet of Things era, IoT devices and the services built on them make our lives more convenient and also raise public concerns on their vulnerability to attacks. Recent literature advocates physical-layer solutions to help IoT devices detect attacks instead of using sophisticated cryptographic methods. However, there is still no satisfying solutions for IoT devices with a single antenna and sparse traffic. Thus, we introduce SecurePilot to fill this gap. SecurePilot is an unsupervised and plug-and-play solution which works without an attacker’s knowledge in advance. It leverages the strengths of two orthogonal physical-layer information, propagation signatures and device signatures embedded in pilot signals to enable effective attack detection. It could work on single-antenna IoT devices with sparse traffic and also work compatibly with communication protocols. The experimental results show that SecurePilot can successfully detect 99.6% of attacks, triggering false alarms on 3.1% of legitimate traffic in a typical office environment.

AIR-FI: Leaking Data from Air-Gapped Computers Using Wi-Fi Frequencies

This paper presents a new attack allowing attackers to exfiltrate data from isolated, air-gapped computers via Wi-Fi frequencies. We show that malware in a compromised air-gapped computer can generate signals in the Wi-Fi frequency bands. The signals are generated through the memory buses - no special hardware is required. Sensitive data can be modulated and secretly exfiltrated on top of the signals. We show that nearby Wi-Fi-capable devices (e.g., smartphones, laptops, and IoT devices) can intercept these signals, decode them, and send them to the attacker over the Internet. We utilized the physical layer information exposed by the Wi-Fi chips to extract the signals. We further implemented the transmitter and receiver and discussed design considerations and implementation details. We evaluated this covert channel in terms of bandwidth and distance and presented a set of countermeasures. Our evaluation shows that data can be exfiltrated from air-gapped computers to nearby Wi-Fi receivers located meters away at bit rates of 16&#x00A0;b/sec.

Spoofing Attack Detection Using Machine Learning in Cross-Technology Communication

Cross-technology communication (CTC) technique can realize direct communication among heterogeneous wireless devices (e.g., WiFi, ZigBee, and Bluetooth in the 2.4 G ISM band) without gateway equipment for forwarding, which makes heterogeneous wireless communication more convenient and greatly reduces communication costs. However, compared with the traditional homogeneous network model, CTC technique also makes it easier to implement spoofing attacks in heterogeneous networks. WiFi devices with long communication distances and sufficient energy supply can directly launch spoofing attacks against ZigBee devices, which brings severe security concerns for heterogeneous wireless communications. In this paper, we focus on the CTC spoofing attack, especially spoofing attacks from WiFi to ZigBee and propose a machine learning-based method to detect spoofing attacks for heterogeneous wireless networks by using physical-layer information. First, we model the received signal strength (RSS) data of legitimate ZigBee devices to construct a one-class support vector machine (OSVM) classifier for detecting CTC spoofing attacks depending on the obtained training samples. Then, we simulated CTC spoofing attacks in a live testbed and evaluated the performance of our detection method. Results show that our approach is highly effective in spoofing detection. Even if the distance between the legitimate ZigBee device and WiFi attacker is near each other (i.e., less than 2 m) and does not require a large number of samples, the detection rate and precision of our method are both over 90%. Finally, we employ the OSVM classifier to obtain samples of spoofing attacks and then explore using SVM to further improve the performance of the classifier.

Secret Key Establishment Using Modified Quantization Log For Vehicular Ad-Hoc Network

Traditional cryptographic approaches such as symmetric and asymmetric cryptography are commonly employed to solve network security issues. The Secret Key Generation (SKG) system has the advantage of extracting secret keys from a wireless channel's physical layer information. It allows two wireless devices within the transmission range to extract a shared symmetric key without the use of a fixed key distribution infrastructure, allowing vehicular ad hoc networks to exchange information (VANET). This study aims to create a secure data communication system on the Vehicular Ad-Hoc Network using RSS Key Generation. Starting from the Modified Quantization Log, the results of the Modified Quantization Log show that the average KDRM between Alice and Bob is the average KDRM between Alice and Bob is 9.4%; meanwhile, the average KGR is 71.4 bps. This shows that the number of bit mismatches after the Modified Quantization Log process between the two valid users is already small, because they have used the pre-processing process in front of them, namely using the Kalman Filter and from the results of the BCH Code to be matched again so that it becomes the key. The next process is Universal Hash which is tested with the NIST test. The NIST Test parameters used are approximately entropy, frequency, block frequency, longest run, cumulative sum forward, and cumulative sum reverse. The existing results are appropriate; namely, the threshold in p whose value is above 0.01 is achieved. From the results of the Average Approximate Entropy, it is found that the largest value is obtained by the 40k10ms scheme, which is 0.7352.

Energy and Collision Aware WSN Routing Protocol for Sustainable and Intelligent IoT Applications

Wireless Sensor Network (WSN) has wide range of applications including next generation intelligent IoT applications. Sensor nodes in WSNs don’t allow replacing batteries as phenomenon under consideration is not frequently accessible or inaccessible. Resource constrained WSN nodes run on batteries with limited capacity. For long running of the WSNs, energy consumption on each node and lifetime of overall network is a concern for IoT applications. To prolong lifetime of WSNs, use of energy efficient method is necessary and a challenging task. Most of the on-demand routing protocols use metrics like number of hops for the selection of path from the source node to the destination node. Purely hop count-based metrics leads to frequent broken paths as well as more energy consumption and results into reduced lifetime of IoT applications. Method proposed in this paper is a cross layer variant of AODV by replacing hop count metric with link quality and collision count. To establish a path, proposed method fetches link quality information from Physical layer and collision information from MAC layer to aid Network layer for making intelligent routing decisions using ZScore method. Using this information, proposed routing metric caters to select stable and sustainable routing path. Method proposed in this paper is implemented in well-known network simulator, NS-2 by incorporating necessary changes into existing physical and MAC layers as well as AODV protocol. A comparative analysis with existing methods is an indicator of improved performance in terms of energy efficiency, network lifetime, path stability and delay.

WITHDRAWN: A novel RSS based light weight digital certificate and key generation scheme for coherent communication of IoT devices

The Internet-of-Things (IoT) will connect different types of cyber physical systems that are supported by different wireless transmission technologies, e.g., Wi-Fi, ZigBee, etc. However, the security protocols of those wireless technologies cannot be implemented to support seamless and secure IoT communications. Moreover, security protocols need to be light-weighted since some IoT devices have limited computation resources. In this research work, we propose a light weight physical-layer security-based authentication and key generation scheme The Internet-of-Things (IoT) will connect different types of cyber physical systems that are supported by different wireless transmission technologies, e.g., Wi-Fi, ZigBee, etc. However, the security protocols of those wireless technologies cannot be implemented to support seamless and secure IoT communications. Moreover, security protocols need to be light-weighted since some IoT devices have limited computation resources. In this research work, we propose a light weight physical-layer security-based authentication and key generation scheme to bridge different transmission technologies in IoT communications. In the studied scenario, a group certificate is generated based on physical-layer information, i.e., Received Signal Strength (RSS) for all legitimate IoT devices in a network. The group certificate is to support mutual authentication between any pair of IoT devices within the network. Furthermore, the proposed scheme also generates a session key for the authenticated pair of IoT devices for other purposes of security features. The proposed scheme also addresses the issue of access control for new IoT devices with a short-term session key generation process. Security analysis is provided to show the efficacy of the proposed scheme against eavesdropping and replay attacks. A tested based experiment is conducted to further demonstrate the RSS based value generation and distribution.

Cross Layer Relay Selection in Device-to-Device Communication

Cross layer optimization for relay assisted wireless communication is important as it caters for parameters in more than one layer thereby a more holistic insight to the performance of proposed algorithms is realised. Due to the nature of the wireless channel, the availability of perfect channel state information may not be guaranteed. Moreover for relay selection algorithms, where mobile user equipment are used as relays, optimizing a relay defined utility can motivate relaying. This work proposes a cross layer stable matching based relay selection algorithm for relay assisted device-to-device communication. The cross layer parameter defined by this work is a function of data rate at the physical layer and queueing state information at the media access control sub-layer. The selection problem is modelled as an optimization problem for which stable matching is used to suitably allocate relay-enabled user equipment to source-destination pairs. To evaluate the performance of the proposed algorithm, spectral efficiency, energy efficiency and fairness were used as performance metrics. The proposed cross layer algorithm was compared with the best source-relay selection algorithm, best relay-destination selection algorithm and a random selection algorithm. Unlike other works, our proposed algorithm is channel uncertainty aware. The proposed cross layer selection algorithm was shown through simulations to offer improved spectral efficiency performance of 16% over the random selection algorithm. Furthermore, there was a fairness improvement of 0.01 and 0.02 over the best source—relay and the best relay—destination selection algorithms respectively.

Information Security Technology of Wireless Communication Physical Layer Based on Airspace Technology

Due to the characteristics of the broadcast function of the wireless communication network, the problem of information security has become very serious. And because the traditional upper-layer encryption technology is accompanied by the advancement of computer technology and eavesdropping technology, it has become more and more far from being able to meet the needs of modern society for information security. The multi-antenna beamforming technology in the airspace technology is a technology that can effectively increase the strength of the legal signal and suppress the eavesdropping signal. Therefore, it has become the most important technology in the physical layer security of our country and deserves our attention. Therefore, this article aims to study the wireless communication physical layer information security technology based on airspace technology. Based on the analysis of the basic theory of physical layer security, the current status of physical layer security research and the airspace physical layer security technology, the artificial noise auxiliary technology is promoted and applied to security identification. Taking the speed of maximizing the safe frequency spectrum as the design goal, an algorithm for joint optimization of information noise beam and artificial noise beam is proposed. The simulation results show that this algorithm can effectively improve the security and stability of the system, and it can also solve the eavesdropping problem.

Fusion of Channel State Information and Received Signal Strength for Indoor Localization Using a Single Access Point

In recent years, indoor localization systems based on fingerprinting have had significant advances yielding high accuracies. Those approaches often use information about channel communication, such as channel state information (CSI) and received signal strength (RSS). Nevertheless, these features have always been employed separately. Although CSI provides more fine-grained physical layer information than RSS, in this manuscript, a methodology for indoor localization fusing both features from a single access point is proposed to provide a better accuracy. In addition, CSI amplitude information is processed to remove high variability information that can negatively influence location estimation. The methodology was implemented and validated in two scenarios using a single access point located in two different positions and configured in 2.4 and 5 GHz frequency bands. The experiments show that the methodology yields an average error distance of about 0.1 m using the 5 GHz band and a single access point.

Provisioning in Multi-Band Optical Networks

Multi-band (MB) optical transmission promises to extend the lifetime of existing optical fibre infrastructures, which usually transmit within the C-band only, with C+L-band being also used in a few high-capacity links. In this work, we propose a physical-layer-aware provisioning scheme tailored for MB systems. This solution utilizes the physical layer information to estimate, by means of the generalized Gaussian noise (GGN) model, the generalized signal-to-noise ratio (GSNR). The GSNR is evaluated assuming transmission up to the entire low-loss spectrum of optical fiber, i.e., from 1260 to 1625 nm. We show that MB transmission may lead to a considerable reduction of the blocking probability, despite the increased transmission penalties resulting from using additional optical fiber transmission bands. Transponders supporting several modulation formats (polarization multiplexing - PM - quadrature phase shift keying - PM-QPSK -, PM 8 quadrature amplitude modulation - PM-8QAM -, and PM-16QAM) from Oto L-band are considered. An increase of the accommodated traffic with respect to the C-band transmission only case, ranging from about four times with S+C+L-band and up to more than six times when transmitting from E to L-band is reported.

Lightpath routing and wavelength assignment for static demand in translucent optical networks

Translucent optical networks use sparsely located regenerator nodes to increase the optical reach, otherwise limited by the physical layer impairments. Routing in translucent networks often causes the lightpath to traverse a fiber more than once, requiring the use of multiple wavelengths on a fiber for the same lightpath. Most of the routing and wavelength assignment (RWA) algorithms for static demand in translucent networks (termed static RWA) require loop-free routes for shortest path routing and also are agnostic to traffic load. In this paper, we address the problem of static RWA in translucent networks without using physical layer information and show how to route lightpaths on paths with a loop (i.e., not a simple path). We propose integer linear programming formulation to get the exact solutions to the static RWA problem. This work is the first one to optimally solve the static RWA problem for non-simple paths, providing the lower bound on the number of wavelengths and regeneration needed for static lightpath establishment when regeneration facilities are limited. We propose a heuristic algorithm based on the concept of Wardrop equilibrium, to adaptively equalize the mean delay along all the lightpath routes from source to destination. The proposed heuristic can not only accommodate the correlation between feasible lightpath routes but also account for the fact that alternate routes correspond to different levels of choice randomness. Wavelength assignment is done using graph coloring with branch-and-price method. Numerical results demonstrate that the proposed heuristic reduces the number of regenerators and wavelengths required to satisfy a given demand.

Tagora: A Collision-Exploitative RFID Authentication Protocol Based on Cross-Layer Approach

Radio-frequency identification (RFID) system, successfully adopted in many industrial applications, suffers from security issues due to the inherent weakness of wireless communication, such as eavesdropping, replay attack, impersonation attack, and traceability issues. A lot of research efforts based on cryptographic primitives have been conducted in a decade, however, most of the existing security protocols depending on cryptosystems are not feasible to be applied due to the minimalist design of passive tags. A lightweight cryptographic authentication is one of the practical solutions, but it has traceability issues from physical layer information. The other approach is to use the properties of the physical layer of RFID systems. However, since the physical-layer characteristics cannot be intentionally updated, they are vulnerable to situations where an adversary actively obtains authentic data for traceability attacks or replay attacks. Therefore, to resist the security threats, we propose Tagora , a cross-layer authentication protocol, which is the first integration work of two-layer approaches that harness the unpredictable properties of tag’s collision responses at both the physical and application layers. Our protocol design is composed of a collision recovery algorithm with a random offset scheme and phase encryption in the physical layer, and authentication process based on a challenge–response mechanism in the application layer. We evaluate Tagora in terms of the untraceability and reliability, and also provide security analysis on how Tagora can defend against plausible attacks while meeting security requirements.

Secure Cooperative Transmission for Mixed RF/FSO Spectrum Sharing Networks

This paper is concerned with the secrecy rate based optimization problems in a mixed radio frequency (RF) / free space optical (FSO) spectrum sharing network, wherein multiple single-antenna secondary users (SUs) are connected to a decode and forward (DF) single-antenna relay through RF links and the relay is connected with the secondary destination through an FSO link. The RF and FSO channels are assumed to follow Rayleigh and Gamma-Gamma distributions with the effect of pointing errors, respectively. The three schemes, i.e., direct transmission, single-user cooperative jamming and multi-user cooperative beamforming jamming, are proposed to improve the physical-layer information security in the presence of a single-antenna eavesdropper. The mutual interference between the primary and secondary networks is considered. The problems are to jointly optimize the SU transmit power and jamming power for the best secrecy performance under both the RF and FSO dominant cases. Such problems are nonconvex. The Dinkelbach approach is adopted to solve the optimization in the direct transmission and single-user cooperative jamming schemes and a two-level optimization approach with semi-definite relaxation (SDR) is applied to obtain the solution for the multi-user cooperative beamforming scheme. Moreover, the SDR optimality is proved by Karush-Kuhn-Tucker conditions analysis. Simulation results are provided, and the results show that the proposed multi-user cooperative beamforming jamming can attain the higher achievable secrecy rate than the zero-forcing beamforming scheme and other two suboptimal designs.

Channel State Information Based Indoor Localization Error Bound Leveraging Pedestrian Random Motion

Indoor pedestrian motion detection based on the Wi-Fi Received Signal Strength (RSS) has been commonly deployed in recent years. However, the Channel State Information (CSI) based indoor localization methods can be selected to achieve higher localization accuracy since it contains the finer-grained physical-layer information of the signal. Lack of theoretical analysis of the CSI-based error bound that leverages the pedestrian motion posses a challenge to investigate the ideal performance. In this circumstance, this paper proposes the Cramer-Rao Lower Bound (CRLB) concept to derive out the indoor localization error bound leveraging the pedestrian motion that depends on the constructed signal propagation model by considering the relationship between the localization accuracy and the path loss, shadow fading, and multipath effect. Through the experimental comparison, this paper analyzes the difference between the actual localization error and the derived localization error bound, and the impact of different experimental parameters on the localization performance is analyzed, as well as discusses the influence of the asynchronous effect between the transmitter and the receiver on the performance of the proposed localization error bound. The experimental results show that the derived error bound has the same trend as the actual error, which validate our theoretical analysis.

TagSort: Accurate Relative Localization Exploring RFID Phase Spectrum Matching for Internet of Things

The radio frequency identification (RFID) technologies, which have been widely adopted in different Internet of Things (IoT) applications, are the fundamental building block for achieving smart factories, smart logistics, smart stores, etc. Besides knowing the ID of tags, the relative location information of different tags is of great importance since it contains the spatial relationship among different tags, which is essential for many object localization applications beyond the capacity of absolute localization approaches. In this article, we propose TagSort , an RFID-based sorting system that exploits the physical layer information, i.e., the phase of RFID wireless signals to achieve the relative localization of different tags. Several novel filtering and peak detection algorithms are proposed to achieve accurate and robust detection of the order of tags. Extensive evaluation shows promising results (over 95% accuracy) and make TagSort a promising system for future RFID sorting systems, thus enabling a variety of IoT applications and services.