Security Hardening of Intelligent Reflecting Surfaces Against Adversarial Machine Learning Attacks

Next-generation communication networks, also known as NextG or 5G and beyond, are the future data transmission systems that aim to connect a large amount of Internet of Things (IoT) devices, systems, applications, and consumers at high-speed data transmission and low latency. Fortunately, NextG networks can achieve these goals with advanced telecommunication, computing, and Artificial Intelligence (AI) technologies in the last decades and support a wide range of new applications. Among advanced technologies, AI has a significant and unique contribution to achieving these goals for beamforming, channel estimation, and Intelligent Reflecting Surfaces (IRS) applications of 5G and beyond networks. However, the security threats and mitigation for AI-powered applications in NextG networks have not been investigated deeply in academia and industry due to being new and more complicated. This paper focuses on an AI-powered IRS implementation in NextG networks along with its vulnerability against adversarial machine learning attacks. This paper also proposes the defensive distillation mitigation method to defend and improve the robustness of the AI-powered IRS model, i.e., reduce the vulnerability. The results indicate that the defensive distillation mitigation method can significantly improve the robustness of AI-powered models and their performance under an adversarial attack.

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Doppler Spectrum Measurement Platform for Narrowband V2V Channels

This paper describes the implementation of a Doppler spectrum measurement platform for narrowband frequency-dispersive vehicle-to-vehicle (V2V) channels. The platform is based on a continuous-wave (CW) channel sounding approach widely used for path-loss and large-scale fading measurements, but whose effectiveness to measure the Doppler spectrum of V2V channels is not equally known. This channel sounding method is implemented using general-purpose hardware in a configuration that is easy to replicate and that enables a partial characterization of frequency-dispersive V2V channels at a fraction of the cost of a dedicated channel sounder. The platform was assessed in a series of field experiments that collected empirical data of the instantaneous Doppler spectrum, the mean Doppler shift, the Doppler spread, the path-loss profile, and the large-scale fading distribution of V2V channels under realistic driving conditions. These experiments were conducted in a highway scenario near San Luis Potosí, México, at two different carrier frequencies, one at 760MHz and the other at 2,500MHz. The transmitting and receiving vehicles were moving in the same direction at varying speeds, ranging from 20 to 130km/h and dictated by the unpredictable traffic conditions. The obtained results demonstrate that the presented measurement platform enables the spectral characterization of narrowband V2V channels and the identification of their Doppler signatures in relevant road-safety scenarios, such as those involving overtaking maneuvers and rapid vehicles approaching the transmitter and receiver in the opposite direction.

*Published in the IEEE Vehicular Society Section within IEEE Access.

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Evolutionary Sleep Scheduling in Software-Defined Networks

The redundant design of communication networks leads to under-utilization of idle devices, which have been reported to consume a significant portion of energy. Thus, it demands a sleep scheduling scheme to improve energy efficiency of communication networks. In this paper, we formulate the optimal sleep scheduling problem from the perspective of routing, which aggregates the traffic loads to fewer active devices by route selection and put the idle devices into sleep to save energy. We then design a genetic algorithm to find out near-optimal sleep scheduling solution, which facilitates the implementation in software-defined networks. Simulation results over network instants from the online database survivable network design library show that our proposed genetic sleep scheduling algorithm outperforms the existing schemes in saving energy.

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Design and Implementation of a Two-Wheel and Hopping Robot With a Linkage Mechanism

Wheeled robots exhibit fast and stable motion on a flat road but lack the ability to overcome the obstacles and rough terrains. To address this shortage, a two-wheel hopping robot is proposed by combining the wheel locomotion and bounce movement. A gear train and a four-bar linkage are employed for jumping. In particular, the take-off angle is dependent on the link length of the four-bar linkage, thus providing versatile flight trajectories. Therefore, the dependency of the hopping performance on the four-bar linkage can be maximized. A four-bar linkage with the same length is used for the specific trajectory and balance control of the inverted pendulum model of the prototype. Dynamics analyses and simulations have been conducted to verify the robot design and its parameters. By jumping tests, the hopping performance is compared with other robots in a quantitative manner. The experimental results show that the wheeled hopping robot has the advantages of light mass and jumping height efficiency..

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Active Plant Wall for Green Indoor Climate Based on Cloud and Internet of Things

An indoor climate is closely related to human health, well-being, and comfort. Thus, indoor climate monitoring and management are prevalent in many places, from public offices to residential houses. Our previous research has shown that an active plant wall system can effectively reduce the concentrations of particulate matter and volatile organic compounds and stabilize the carbon dioxide concentration in an indoor environment. However, regular plant care is restricted by geography and can be costly in terms of time and money, which poses a significant challenge to the widespread deployment of plant walls. In this paper, we propose a remote monitoring and control system that is specific to the plant walls. The system utilizes the Internet of Things technology and the Azure public cloud platform to automate the management procedure, improve the scalability, enhance user experiences of plant walls, and contribute to a green indoor climate.

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Stabilizing Graphically Extended Hand for Hand Tremors

Tremors, which refer the trembling or shaking of body parts, are caused by the involuntary contractions of muscles and are one of the most common movement disorders that often reduce individuals’ the levels of the hand functions and also affect their independent body movements adversely. “Extended Hand (EH)”is an augmented body technology, which visually extends the length of a user’s arm by a spatial augmented reality. It could facilitate individuals whose reaching areas are limited by body movement disorders to interact with distant objects. However, the technology is currently limited, because any trembling of the hands contacting with the touch panel of the EH system is amplified, causing EH to shake in the physical world as well. To make EH benefit individuals whose hands and body are disabled by tremors, we proposed methods for stabilizing the movements and gestures of the EH to allow EH controlled steadily by their trembling hands. We developed a hand tremor simulator by which trembling hands interacting with EH were imitated, and investigated the effectiveness of stabilization methods by conducting a series of pointing and grasping experiments. The stabilization method composed of Kalman filter and Hysteresis was confirmed to be effective in reducing the unstable translation and unstable stationary state of EH, and the method combining the stabilization of the distances from the fingertips to their centroid and the analysis of the change in low frequency components of the touching areas effectively enable trembling hands to control the EH gestures steadily.

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Anonymous Authentication Scheme for Smart Cloud Based Healthcare Applications

Many smart healthcare applications are adopting cloud to provide services to patients. However, the sensitive data can be disclosed to the authentication server/service provider. Therefore, security and privacy are crucial to its success and deployment at large scale. Patients don’t want to disclose their identities to the cloud server. One way to protect their identities from cloud server is anonymous authentication. The authentication process normally involves disclosing users’ private information, such as username and password to the authentication server. If the patient can be linked or tracked by the authentication server or malicious adversaries by their requests, their privacy can be breached. Most of the existing privacy preserving health care applications provides anonymity from the adversaries. However, very few of them provide anonymity from the authentication server. In this paper, we have proposed a system which provides complete privacy and anonymity to the users of health care applications from adversaries and the authentication server. In our proposed authentication scheme, we have utilized rotating group signature scheme based on Elliptic curve cryptography to provide anonymity to the patients. To add an extra layer of protection, we have used The Onion Router to provide privacy at the network layer. The performance of our scheme is evaluated by theoretical analysis which demonstrates that it resists various attacks and provides several attractive security features.

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IAPcloud: A Cloud Control Platform for Heterogeneous Robots

The cloud robotic technology makes multiple robots share resources and collaborate with each other more flexibly. Although this concept has been widely accepted by academia since it was put forward, it still faces many challenges in engineering. The main problems are that the functions of industrial robotic systems become more and more complex, and the programming language and computing environment of multiple vendor robots are significantly different, accordingly the cooperative control of different devices and the online testing become extremely difficult. Therefore, this paper proposes a new control platform for cloud robots, called IAPcloud, which has significant advantages in solving the problem of collaborative control among heterogeneous robots and their auxiliary devices, declining the programming difficulties of cloud robotic control systems and shortening the development and deployment cycle of the application. Finally, we verify the scientific and effectiveness of the IAPcloud platform by three cases, including the image recognition and tracking, the human–machine gobang game, and the online dynamic reconfiguration of control algorithms.

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High-Speed Image Velocimetry System for Rainfall Measurement

In this paper, a new image-based disdrometer is developed to survey the movement of free falling raindrops. The proposed high-speed image velocimetry (HSIV) system comprises a high-speed camera mounted on a lens with long depth of field, a backlight source using an array of blue LEDs, and a computation/control unit for image acquisition and analysis. Further image processing algorithms are produced for raindrop detection and raindrop tracking. The performance of the HSIV system is compared with that of a commercial PARSIVEL2 disdrometer during a local rainfall event within 12 h, while a tippingbucket rain gauge is also used to estimate the amount rainfall rate during that period. The data obtained from the proposed HSIV system are in good agreement with those of PARSIVEL2. Furthermore, the results of the HSIV system are closer than those of PARSIVEL2 to the actual rainfall, which is determined by the rain gauge. To validate the raindrop tracking algorithm, another experiment is conducted to compare the tracking results with the frame-by-frame visual observation from 2880 consecutive frames within 5 min. Experimental results suggest that the proposed HSIV system facilitates the measurement of the precipitation properties, fall velocity, equivolume diameter, raindrop concentration, and rainfall rate, to real-time monitoring of the rainfall with stable and reliable analysis.

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Underwater Localization Based on Grid Computation and Its Application to Transmit Beamforming in Multiuser UWA Communications

Underwater localization is a challenging problem and established technologies for terrestrial systems cannot be used, notably the Global Positioning System (GPS). In this paper, we propose an underwater localization technique and demonstrate how it can be effectively used for transmit beamforming in multiuser underwater acoustic (UWA) communications. The localization is based on pre-computation of acoustic channel parameters between a transmitter-receiver pair on a grid of points covering the area of interest. This is similar to the localization process using matched field processing, which is often based on processing a priori unknown signals received by an array of hydrophones. However, in our case, every receiver is assumed to have a single hydrophone, while an array of transducers transmit (pilot) signals known at a receiver. The receiver processes the received pilot signal to estimate the Channel State Information (CSI) and compares it with the CSI pre-computed on the grid; the best match indicates the location estimate. The proposed localization technique also enables an efficient solution to the inherent problem of informing a transmitter about the CSI available at the receiver for the purpose of transmit beamforming. The receiver only needs to send a grid point index to enable the transmitter to obtain the pre-computed CSI corresponding to the particular grid point, thereby significantly reducing transmission overheads. We apply this approach to a multiuser communication scenario with orthogonal frequency-division multiplexing (OFDM) and show that the proposed approach results in accurate localization of receivers and multiuser communications with a high detection performance.

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