Securing Cyber-Physical Social Interactions on Wrist-worn Devices

Since ancient Greece, handshaking has been commonly practiced between two people as a friendly gesture to express trust and respect, or form a mutual agreement. In this article, we show that such physical contact can be used to bootstrap secure cyber contact between the smart devices worn by users. The key observation is that during handshaking, although belonged to two different users, the two hands involved in the shaking events are often rigidly connected, and therefore exhibit very similar motion patterns. We propose a novel key generation system, which harvests motion data during user handshaking from the wrist-worn smart devices such as smartwatches or fitness bands, and exploits the matching motion patterns to generate symmetric keys on both parties. The generated keys can be then used to establish a secure communication channel for exchanging data between devices. This provides a much more natural and user-friendly alternative for many applications, e.g., exchanging/sharing contact details, friending on social networks, or even making payments, since it doesn’t involve extra bespoke hardware, nor require the users to perform pre-defined gestures. We implement the proposed key generation system on off-the-shelf smartwatches, and extensive evaluation shows that it can reliably generate 128-bit symmetric keys just after around 1s of handshaking (with success rate >99%), and is resilient to different types of attacks including impersonate mimicking attacks, impersonate passive attacks, or eavesdropping attacks. Specifically, for real-time impersonate mimicking attacks, in our experiments, the Equal Error Rate (EER) is only 1.6% on average. We also show that the proposed key generation system can be extremely lightweight and is able to run in-situ on the resource-constrained smartwatches without incurring excessive resource consumption

Shake-n-shack : enabling secure data exchange between Smart Wearables via handshakes

Since ancient Greece, handshaking has been commonly practiced between two people as a friendly gesture to express trust and respect, or form a mutual agreement. In this paper, we show that such physical contact can be used to bootstrap secure cyber contact between the smart devices worn by users. The key observation is that during handshaking, although belonged to two different users, the two hands involved in the shaking events are often rigidly connected, and therefore exhibit very similar motion patterns. We propose a novel Shake-n-Shack system, which harvests motion data during user handshaking from the wrist worn smart devices such as smartwatches or fitness bands, and exploits the matching motion patterns to generate symmetric keys on both parties. The generated keys can be then used to establish a secure communication channel for exchanging data between devices. This provides a much more natural and user-friendly alternative for many applications, e.g., exchanging/sharing contact details, friending on social networks, or even making payments, since it doesn't involve extra bespoke hardware, nor require the users to perform pre-defined gestures. We implement the proposed Shake-n-Shack 1 system on off-the-shelf smartwatches, and extensive evaluation shows that it can reliably generate 128-bit symmetric keys just after around 1s of handshaking (with success rate >99%), and is resilient to real-time mimicking attacks: in our experiments the Equal Error Rate (EER) is only 1.6% on average. We also show that the proposed Shake-n-Shack system can be extremely lightweight, and is able to run in-situ on the resource-constrained smartwatches without incurring excessive resource consumption

LEO Satellite-Enabled Grant-Free Random Access with MIMO-OTFS

This paper investigates joint channel estimation and device activity detection in the LEO satellite-enabled grant-free random access systems with large differential delay and Doppler shift. In addition, the multiple-input multiple-output (MIMO) with orthogonal time-frequency space modulation (OTFS) is utilized to combat the dynamics of the terrestrial-satellite link. To simplify the computation process, we estimate the channel tensor in parallel along the delay dimension. Then, the deep learning and expectation-maximization approach are integrated into the generalized approximate message passing with cross-correlation--based Gaussian prior to capture the channel sparsity in the delay-Doppler-angle domain and learn the hyperparameters. Finally, active devices are detected by computing energy of the estimated channel. Simulation results demonstrate that the proposed algorithms outperform conventional methods.Comment: This paper has been accepted for presentation at the IEEE GLOBECOM 2022. arXiv admin note: text overlap with arXiv:2202.1305

All-dielectric electromagnetically induced transparency-like metasurface with breaking symmetric

We investigate an all-dielectric metasurface to mimic the electromagnetically induced transparency-like phenomenon in the microwave. The unit cell is comprised of two hollow split ring resonators with different parameters, which form an asymmetric structure. The proposed metasurface acquires a high transmission efficiency at 17.17 GHz, which is caused by magnetic resonance. The corresponding physical mechanism is discussed and analyzed by the distributions of the electric and magnetic fields. The experiment result of the transmission spectra is well in agreement with the simulation data. The geometric parameter of hollow split ring resonators has deep influences on transmission spectra which leads to transparency peak variation. Concurrently, the imaginary parts of the effective permittivity and permeability for the proposed metasurface are presented to explain the low-loss property. Furthermore, the transparency peak is sensitive to the surrounding environment, which exhibits potential application in refractive index sensor

Poster abstract: an online approach for gait recognition on smart glasses

With the fast development and increasing population of the wearable devices involves in our daily life, the security of the privacy information on those devices is attracting significant attentions. One of the possible solution is to enable the devices to recognise the real owner with authentication system. Biometrics recognition is popular used for authentication systems. The biometrics used including faces, fingerprints, gait cycles and etc. Using gait cycles as the criteria for identities recognition is superior than other biometrics as the gait information can be collected by the IMU sensors which are most popular embedded on portable devices and they cannot be reproduced by the invaders. We propose, Securitas, the continuous authentication system exploits the information from IMU sensors on the smart glasses to distinguish different wearers

Beamspace precoding and beam selection for wideband millimeter-Wave MIMO relying on lens antenna arrays

Millimeter-wave (mmWave) multiple-input multiple-out (MIMO) systems relying on lens antenna arrays are capable of achieving a high antenna-gain at a considerably reduced number of radio frequency (RF) chains via beam selection. However, the traditional beam selection network suffers from significant performance loss in wideband systems due to the effect of beam squint. In this paper, we propose a phase shifter-aided beam selection network, which enables a single RF chain to support multiple focused-energy beams, for mitigating the beam squint in wideband mmWave MIMO systems. Based on this architecture, we additionally design an efficient transmit precoder (TPC) for maximizing the achievable sum-rate, which is composed of beam selection and beamspace precoding. Specifically, we decouple the design problems of beamspace precoding and beam selection by exploiting the fact that the beam selection matrix has a limited number of candidates. For the beamspace precoding design, we propose a successive interference cancellation (SIC)-based method, which decomposes the associated optimization problem into a series of subproblems and solves them successively. For the beam selection design, we propose an energy-max beam selection method for avoiding the high complexity of exhaustive search, and derive the number of required beams for striking an attractive trade-off between the hardware cost and system performance. Our simulation results show that the proposed beamspace precoding and beam selection methods achieve both a higher sum-rate and a higher energy efficiency than its conventional counterparts.<br/

Chronic Effects of Apelin on Cardiovascular Regulation and Angiotensin II-Induced Hypertension

Apelin, by stimulation of APJ receptors, induces transient blood pressure (BP) reduction and positive inotropic effects. APJ receptors share high homology with the Ang II type 1 receptor; thus, apelin was proposed to play a protective role in cardiovascular disease by antagonizing the actions of Ang II. In this regard, apelin and apelin-mimetics are currently being studied in clinical trials. However, the chronic effect of apelin in cardiovascular regulation has not been fully investigated. In the current study, blood pressure (BP) and heart rate (HR) were recorded using a telemetry implantation approach in conscious rats, before and during chronic subcutaneous infusion of apelin-13, using osmotic minipumps. At the end of the recording, the cardiac myocyte morphology was examined using H&E staining, and cardiac fibrosis was evaluated by Sirius Red in each group of rats. The results demonstrated that the chronic infusion of apelin-13 did not change either BP or HR. However, under the same condition, the chronic infusion of Ang II induced significant BP elevation, cardiac hypertrophy, and fibrosis. Co-administration of apelin-13 did not significantly alter the Ang II-induced elevation in BP, changes in cardiac morphology, and fibrosis. Taken together, our experiments showed an unexpected result indicating that the chronic administration of apelin-13 did not alter basal BP, nor did it change Ang II-induced hypertension and cardiac hypertrophy. The findings suggest that an APJ receptor biased agonist could be a better therapeutic alternative for treatment of hypertension

Joint Bayesian channel estimation and data detection for OTFS systems in LEO satellite communications

Lower earth orbit (LEO) satellites play an important role in the integration of space and terrestrial communication networks, which typically encounter high-mobility scenarios. It has been shown that orthogonal time frequency space (OTFS)modulation performs well in such high-mobility scenarios by transforming the time-varying channels into the delay-Doppler domain. In this paper, we develop a joint channel estimation and data detection algorithm for OTFS-based LEO satellitecommunications. Firstly, we adopt the powerful variational Bayesian inference (VBI) method for estimating the delay-Doppler channel vector, which contains the channel gain, the delay and the Doppler. Secondly, we exploit the unknown data symbols in an OTFS frame as ‘virtual pilots’ for improving the accuracy of channel estimation and detect them simultaneously. Our simulation results demonstrate that the proposed algorithm achieves improved channel estimation mean square error and bit error rate performance than its conventional counterparts

Estimation of dispersive high-doppler channels in the RIS-aided mmWave internet of vehicles

Reconfigurable intelligent surfaces (RISs) have emerged as a promising candidate for improving the spectraland energy- efficiency of millimeter-wave (mmWave) Internet of vehicles (IoV) communications, but the conception of their accurate channel estimation poses. Hence the existing estimation methods mainly focus on time-invariant channels, while ignoring the Doppler effect induced by the high-velocity vehicles, which will lead to significant performance degradation. In this paper, we investigate the problem of channel estimation in RIS-aided mmWave IoV systems considering the deleterious Doppler effect. Firstly, we derive the expression of the time-varying cascaded two-hop multiple-path channels, where each delay tap is subject to multiple paths instead of having a simple one-to-one correspondence. In order to decouple the paths, the problem is formulated in the delay-domain by a series of transformations and the cascaded two-hop channel can be estimated at each delay tap. Then we propose a pair of estimation strategies by considering different hardware constraints depending on the number of receiver antennas at the base station (BS). When a large receiver array is employed at the BS, we can exploit its high angular selectivity for distinguishing each resolvable path at a certain delay tap because they arrive from different directions. However, this cannot be achieved for small arrays, given their more limited angular resolution. Thus, the RIS reflection patterns are delicately designed for distinguishing multiple resolvable paths. After separating the paths, Doppler estimation can be performed by calculating the phase difference of the adjacent symbols. Our simulation results demonstrate the superior performance of the proposed methods within a wide range of Doppler shifts