Visible to the public Biblio

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2021-07-08
Li, Sichun, Jin, Xin, Yao, Sibing, Yang, Shuyu.  2020.  Underwater Small Target Recognition Based on Convolutional Neural Network. Global Oceans 2020: Singapore – U.S. Gulf Coast. :1—7.
With the increasingly extensive use of diver and unmanned underwater vehicle in military, it has posed a serious threat to the security of the national coastal area. In order to prevent the underwater diver's impact on the safety of water area, it is of great significance to identify underwater small targets in time to make early warning for it. In this paper, convolutional neural network is applied to underwater small target recognition. The recognition targets are diver, whale and dolphin. Due to the time-frequency spectrum can reflect the essential features of underwater target, convolutional neural network can learn a variety of features of the acoustic signal through the image processed by the time-frequency spectrum, time-frequency image is input to convolutional neural network to recognize the underwater small targets. According to the study of learning rate and pooling mode, the network parameters and structure suitable for underwater small target recognition in this paper are selected. The results of data processing show that the method can identify underwater small targets accurately.
2021-01-25
Zhan, Z., Zhang, Z., Koutsoukos, X..  2020.  BitJabber: The World’s Fastest Electromagnetic Covert Channel. 2020 IEEE International Symposium on Hardware Oriented Security and Trust (HOST). :35—45.

An air-gapped computer is physically isolated from unsecured networks to guarantee effective protection against data exfiltration. Due to air gaps, unauthorized data transfer seems impossible over legitimate communication channels, but in reality many so-called physical covert channels can be constructed to allow data exfiltration across the air gaps. Most of such covert channels are very slow and often require certain strict conditions to work (e.g., no physical obstacles between the sender and the receiver). In this paper, we introduce a new physical covert channel named BitJabber that is extremely fast and strong enough to even penetrate concrete walls. We show that this covert channel can be easily created by an unprivileged sender running on a victim’s computer. Specifically, the sender constructs the channel by using only memory accesses to modulate the electromagnetic (EM) signals generated by the DRAM clock. While possessing a very high bandwidth (up to 300,000 bps), this new covert channel is also very reliable (less than 1% error rate). More importantly, this covert channel can enable data exfiltration from an air-gapped computer enclosed in a room with thick concrete walls up to 15 cm.

Naz, M. T., Zeki, A. M..  2020.  A Review of Various Attack Methods on Air-Gapped Systems. 2020 International Conference on Innovation and Intelligence for Informatics, Computing and Technologies (3ICT). :1—6.

In the past air-gapped systems that are isolated from networks have been considered to be very secure. Yet there have been reports of such systems being breached. These breaches have shown to use unconventional means for communication also known as covert channels such as Acoustic, Electromagnetic, Magnetic, Electric, Optical, and Thermal to transfer data. In this paper, a review of various attack methods that can compromise an air-gapped system is presented along with a summary of how efficient and dangerous a particular method could be. The capabilities of each covert channel are listed to better understand the threat it poses and also some countermeasures to safeguard against such attack methods are mentioned. These attack methods have already been proven to work and awareness of such covert channels for data exfiltration is crucial in various industries.

Guri, M..  2020.  CD-LEAK: Leaking Secrets from Audioless Air-Gapped Computers Using Covert Acoustic Signals from CD/DVD Drives. 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC). :808—816.

Air-gapped networks are isolated from the Internet, since they store and process sensitive information. It has been shown that attackers can exfiltrate data from air-gapped networks by sending acoustic signals generated by computer speakers, however this type of covert channel relies on the existence of loudspeakers in the air-gapped environment. In this paper, we present CD-LEAK - a novel acoustic covert channel that works in constrained environments where loudspeakers are not available to the attacker. Malware installed on a compromised computer can maliciously generate acoustic signals via the optical CD/DVD drives. Binary information can then be modulated over the acoustic signals and be picked up by a nearby Internet connected receiver (e.g., a workstation, hidden microphone, smartphone, laptop, etc.). We examine CD/DVD drives and discuss their acoustical characteristics. We also present signal generation and detection, and data modulation and demodulation algorithms. Based on our proposed method, we developed a transmitter and receiver for PCs and smartphones, and provide the design and implementation details. We examine the channel and evaluate it on various optical drives. We also provide a set of countermeasures against this threat - which has been overlooked.

2021-01-20
Wang, H., Yang, J., Wang, X., Li, F., Liu, W., Liang, H..  2020.  Feature Fingerprint Extraction and Abnormity Diagnosis Method of the Vibration on the GIS. 2020 IEEE International Conference on High Voltage Engineering and Application (ICHVE). :1—4.

Mechanical faults of Gas Insulated Switchgear (GIS) often occurred, which may cause serious losses. Detecting vibration signal was effective for condition monitoring and fault diagnosis of GIS. The vibration characteristic of GIS in service was detected and researched based on a developed testing system in this paper, and feature fingerprint extraction method was proposed to evaluate vibration characteristics and diagnose mechanical defects. Through analyzing the spectrum of the vibration signal, we could see that vibration frequency of operating GIS was about 100Hz under normal condition. By means of the wavelet transformation, the vibration fingerprint was extracted for the diagnosis of mechanical vibration. The mechanical vibration characteristic of GIS including circuit breaker and arrester in service was detected, we could see that the frequency distribution of abnormal vibration signal was wider, it contained a lot of high harmonic components besides the 100Hz component, and the vibration acoustic fingerprint was totally different from the normal ones, that is, by comparing the frequency spectra and vibration fingerprint, the mechanical faults of GIS could be found effectively.

Zarazaga, P. P., Bäckström, T., Sigg, S..  2020.  Acoustic Fingerprints for Access Management in Ad-Hoc Sensor Networks. IEEE Access. 8:166083—166094.

Voice user interfaces can offer intuitive interaction with our devices, but the usability and audio quality could be further improved if multiple devices could collaborate to provide a distributed voice user interface. To ensure that users' voices are not shared with unauthorized devices, it is however necessary to design an access management system that adapts to the users' needs. Prior work has demonstrated that a combination of audio fingerprinting and fuzzy cryptography yields a robust pairing of devices without sharing the information that they record. However, the robustness of these systems is partially based on the extensive duration of the recordings that are required to obtain the fingerprint. This paper analyzes methods for robust generation of acoustic fingerprints in short periods of time to enable the responsive pairing of devices according to changes in the acoustic scenery and can be integrated into other typical speech processing tools.

Sato, Y., Yanagitani, T..  2020.  Giga-hertz piezoelectric epitaxial PZT transducer for the application of fingerprint imaging. 2020 IEEE International Ultrasonics Symposium (IUS). :1—3.

The fingerprint sensor based on pMUTs was reported [1]. Spatial resolution of the image depends on the size of the acoustic source when a plane wave is used. If the size of the acoustic source is smaller, piezoelectric films with high dielectric constant are required. In this study, in order to obtain small acoustic source, we proposed Pb(Zrx Th-x)O3 (PZT) epitaxial transducers with high dielectric constant. PbTiO3 (PTO) epitaxial films were grown on conductive La-SrTiO3 (STO) substrate by RF magnetron sputtering. Longitudinal wave conversion loss of PTO transducers was measured by a network analyzer. The thermoplastic elastomer was used instead of real fingerprint. We confirmed that conversion loss of piezoelectric film/substrate structure was increased by contacting the elastomer due the change of reflection coefficient of the substrate bottom/elastomer interface. Minimum conversion loss images were obtained by mechanically scanning the soft probe on the transducer surface. We achieved the detection of the fingerprint phantom based on the elastomer in the GHz.

2020-12-21
Han, K., Zhang, W., Liu, C..  2020.  Numerical Study of Acoustic Propagation Characteristics in the Multi-scale Seafloor Random Media. 2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP). :135–138.
There is some uncertainty as to the applicability or accuracy of current theories for wave propagation in sediments. Numerical modelling of acoustic data has long been recognized to be a powerful method of understanding of complicated wave propagation and interaction. In this paper, we used the coupled two-dimensional PSM-BEM program to simulate the process of acoustic wave propagation in the seafloor with distributed multi-scale random media. The effects of fluid flow between the pores and the grains with multi-scale distribution were considered. The results show that the coupled PSM-BEM program can be directly applied to both high and low frequency seafloor acoustics. A given porous frame with the pore space saturated with fluid can greatly increase the magnitude of acoustic anisotropy. acoustic wave velocity dispersion and attenuation are significant over a frequency range which spans at least two orders of magnitude.
2020-11-17
Radha, P., Selvakumar, N., Sekar, J. Raja, Johnsonselva, J. V..  2018.  Enhancing Internet of Battle Things using Ultrasonic assisted Non-Destructive Testing (Technical solution). 2018 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). :1—4.

The subsystem of IoMT (Internet of Military of Things) called IoBT (Internet of Battle of Things) is the major resource of the military where the various stack holders of the battlefield and different categories of equipment are tightly integrated through the internet. The proposed architecture mentioned in this paper will be helpful to design IoBT effectively for warfare using irresistible technologies like information technology, embedded technology, and network technology. The role of Machine intelligence is essential in IoBT to create smart things and provide accurate solutions without human intervention. Non-Destructive Testing (NDT) is used in Industries to examine and analyze the invisible defects of equipment. Generally, the ultrasonic waves are used to examine and analyze the internal defects of materials. Hence the proposed architecture of IoBT is enhanced by ultrasonic based NDT to study the properties of the things of the battlefield without causing any damage.

2020-08-03
Al-Emadi, Sara, Al-Ali, Abdulla, Mohammad, Amr, Al-Ali, Abdulaziz.  2019.  Audio Based Drone Detection and Identification using Deep Learning. 2019 15th International Wireless Communications Mobile Computing Conference (IWCMC). :459–464.
In recent years, unmanned aerial vehicles (UAVs) have become increasingly accessible to the public due to their high availability with affordable prices while being equipped with better technology. However, this raises a great concern from both the cyber and physical security perspectives since UAVs can be utilized for malicious activities in order to exploit vulnerabilities by spying on private properties, critical areas or to carry dangerous objects such as explosives which makes them a great threat to the society. Drone identification is considered the first step in a multi-procedural process in securing physical infrastructure against this threat. In this paper, we present drone detection and identification methods using deep learning techniques such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and Convolutional Recurrent Neural Network (CRNN). These algorithms will be utilized to exploit the unique acoustic fingerprints of the flying drones in order to detect and identify them. We propose a comparison between the performance of different neural networks based on our dataset which features audio recorded samples of drone activities. The major contribution of our work is to validate the usage of these methodologies of drone detection and identification in real life scenarios and to provide a robust comparison of the performance between different deep neural network algorithms for this application. In addition, we are releasing the dataset of drone audio clips for the research community for further analysis.
Iula, Antonio, Micucci, Monica.  2019.  Palmprint recognition based on ultrasound imaging. 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). :621–624.
Biometric recognition systems based on ultrasound images have been investigated for several decades, and nowadays ultrasonic fingerprint sensors are fully integrated in portable devices. Main advantage of the Ultrasound over other technologies are the possibility to collect 3D images, allowing to gain information on under-skin features, which improve recognition accuracy and resistance to spoofing. Also, ultrasound images are not sensible to several skin contaminations, humidity and not uniform ambient illumination. An ultrasound system, able to acquire 3D images of the human palm has been recently proposed. In this work, a recognition procedure based on 2D palmprint images collected with this system is proposed and evaluated through verification experiments carried out on a home made database composed of 141 samples collected from 24 users. Perspective of the proposed method by upgrading the recognition procedure to provide a 3D template able to accounts for palm lines' depth are finally highlighted and discussed.
2020-07-30
Tina, Sonam, Harshit, Singla, Muskan.  2019.  Smart Lightning and Security System. 2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU). :1—6.

As Electric Power is one of the major concerns, so the concept of the automatic lighting and security system saves the electrical energy. By using the automatic lightning, the consumption of electrical power can be minimized to a greater extent and for that sensors and microcontrollers can be designed in such a manner such that lights get ON/OFF based on motion in a room. The various sensors used for sensing the motion in an area are PIR motion sensor, IR Motion Sensor. An IR sensor senses the heat of an object and detects its motion within some range as it emits infrared radiations and this complete process can be controlled by microcontroller. Along with that security system can be applied in this concept by programming the microcontroller in such a way that if there is some movement in an area then lights must get ON/OFF automatically or any alarm must start. This chapter proposes the framework for the smart lightning with security systems in a building so that electrical power can be utilized efficiently and secures the building.

2020-03-18
Zhou, Xinyan, Ji, Xiaoyu, Yan, Chen, Deng, Jiangyi, Xu, Wenyuan.  2019.  NAuth: Secure Face-to-Face Device Authentication via Nonlinearity. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. :2080–2088.
With the increasing prevalence of mobile devices, face-to-face device-to-device (D2D) communication has been applied to a variety of daily scenarios such as mobile payment and short distance file transfer. In D2D communications, a critical security problem is verifying the legitimacy of devices when they share no secrets in advance. Previous research addressed the problem with device authentication and pairing schemes based on user intervention or exploiting physical properties of the radio or acoustic channels. However, a remaining challenge is to secure face-to-face D2D communication even in the middle of a crowd, within which an attacker may hide. In this paper, we present Nhuth, a nonlinearity-enhanced, location-sensitive authentication mechanism for such communication. Especially, we target at the secure authentication within a limited range such as 20 cm, which is the common case for face-to-face scenarios. Nhuth contains averification scheme based on the nonlinear distortion of speaker-microphone systems and a location-based-validation model. The verification scheme guarantees device authentication consistency by extracting acoustic nonlinearity patterns (ANP) while the validation model ensures device legitimacy by measuring the time difference of arrival (TDOA) at two microphones. We analyze the security of Nhuth theoretically and evaluate its performance experimentally. Results show that Nhuth can verify the device legitimacy in the presence of nearby attackers.
2020-01-13
Gou, Yue, Dai, Yu-yu.  2019.  Simulation Study on Wideband Transducer with Longitudinal-Flexural Coupling Vibration. 2019 13th Symposium on Piezoelectrcity, Acoustic Waves and Device Applications (SPAWDA). :1–4.
This paper designed a longitudinal bending coupled piezoelectric transducer. The transducer is composed of a rear metal block, a longitudinally polarized piezoelectric ceramic piece and a slotted round front cover. The longitudinal vibration of the piezoelectric oscillators drive the front cover to generate bending vibration to widen the operating frequency band while reducing the fluctuation of transmission voltage response. In this paper, the design method of this multimode coupled transducer is given, and the method is verified by numerical simulation. The results show that the analytical theory and numerical simulation results have good consistency. This longitudinal-flexural coupled vibration transducer widens the bandwidth while preserving the emission voltage response.
Kang, Lei, Feeney, Andrew, Somerset, Will, Dixon, Steve.  2019.  Wideband Electromagnetic Dynamic Acoustic Transducer as a Standard Acoustic Source for Air-coupled Ultrasonic Sensors. 2019 IEEE International Ultrasonics Symposium (IUS). :2481–2484.
To experimentally study the characteristics of ultrasonic sensors, a wideband air-coupled ultrasonic transducer, wideband electromagnetic dynamic acoustic transducer (WEMDAT), is designed and fabricated. Characterisation methods, including electrical impedance analysis, laser Doppler vibrometry and pressure-field microphone measurement, are used to examine the performance of the WEMDAT, which have shown that the transducer has a wide bandwidth ranging approximately from 47 kHz to 145 kHz and a good directivity with a beam angle of around 20˚ with no evident side lobes. A 40 kHz commercial flexural ultrasonic transducer (FUT) is then taken as an example to receive ultrasonic waves in a pitch-catch configuration to evaluate the performance of the WEMDAT as an acoustic source. Experiment results have demonstrated that the WEMDAT can maintain the most of the frequency content of a 5 cycle 40 kHz tone burst electric signal and convert it into an ultrasonic wave for studying the dynamic characteristic and the directivity pattern of the ultrasonic receiver. A comparison of the dynamic characteristics between the transmitting and the receiving processes of the same FUT reveals that the FUT has a wider bandwidth when operating as an ultrasonic receiver than operating as a transmitter, which indicates that it is necessary to quantitatively investigate the receiving process of an ultrasonic transducer, demonstrating a huge potential of the WEMDAT serving as a standard acoustic source for ultrasonic sensors for various air-coupled ultrasonic applications.
Durgapu, Swetha, Kiran, L. Venkateshwara, Madhavi, Valli.  2019.  A Novel Approach on Mobile Devices Fast Authentication and Key Agreement. 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN). :1–4.
Mechanism to-Rube Goldberg invention accord is normal habituated to for apartment phones and Internet of Things. Agree and central knowledge are open to meet an unfailing turning between twosome gadgets. In ignoble fracas, factual methodologies many a time eon wait on a prefabricated solitarily pronunciation database and bear the ill effects of serene age rate. We verifiable GeneWave, a brusque gadget inspection and root assention convention for item cell phones. GeneWave mischievous accomplishes bidirectional ingenious inspection office on the physical reaction meantime between two gadgets. To evade the resolution of interim in compliance, we overshadow overseas time fragility on ware gadgets skim through steep flag location and excess time crossing out. At zigzag goal, we success out the elementary acoustic channel reaction for gadget verification. We combination an extraordinary coding pointing for virtual key assention while guaranteeing security. Consequently, two gadgets heart signal couple choice and safely concur on a symmetric key.
2019-02-08
Zhou, Bing, Lohokare, Jay, Gao, Ruipeng, Ye, Fan.  2018.  EchoPrint: Two-Factor Authentication Using Acoustics and Vision on Smartphones. Proceedings of the 24th Annual International Conference on Mobile Computing and Networking. :321-336.

User authentication on smartphones must satisfy both security and convenience, an inherently difficult balancing art. Apple's FaceID is arguably the latest of such efforts, at the cost of additional hardware (e.g., dot projector, flood illuminator and infrared camera). We propose a novel user authentication system EchoPrint, which leverages acoustics and vision for secure and convenient user authentication, without requiring any special hardware. EchoPrint actively emits almost inaudible acoustic signals from the earpiece speaker to "illuminate" the user's face and authenticates the user by the unique features extracted from the echoes bouncing off the 3D facial contour. To combat changes in phone-holding poses thus echoes, a Convolutional Neural Network (CNN) is trained to extract reliable acoustic features, which are further combined with visual facial landmark locations to feed a binary Support Vector Machine (SVM) classifier for final authentication. Because the echo features depend on 3D facial geometries, EchoPrint is not easily spoofed by images or videos like 2D visual face recognition systems. It needs only commodity hardware, thus avoiding the extra costs of special sensors in solutions like FaceID. Experiments with 62 volunteers and non-human objects such as images, photos, and sculptures show that EchoPrint achieves 93.75% balanced accuracy and 93.50% F-score, while the average precision is 98.05%, and no image/video based attack is observed to succeed in spoofing.

2019-01-21
Shen, Sheng, Roy, Nirupam, Guan, Junfeng, Hassanieh, Haitham, Choudhury, Romit Roy.  2018.  MUTE: Bringing IoT to Noise Cancellation. Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication. :282–296.

Active Noise Cancellation (ANC) is a classical area where noise in the environment is canceled by producing anti-noise signals near the human ears (e.g., in Bose's noise cancellation headphones). This paper brings IoT to active noise cancellation by combining wireless communication with acoustics. The core idea is to place an IoT device in the environment that listens to ambient sounds and forwards the sound over its wireless radio. Since wireless signals travel much faster than sound, our ear-device receives the sound in advance of its actual arrival. This serves as a glimpse into the future, that we call lookahead, and proves crucial for real-time noise cancellation, especially for unpredictable, wide-band sounds like music and speech. Using custom IoT hardware, as well as lookahead-aware cancellation algorithms, we demonstrate MUTE, a fully functional noise cancellation prototype that outperforms Bose's latest ANC headphone. Importantly, our design does not need to block the ear - the ear canal remains open, making it comfortable (and healthier) for continuous use.

Belikovetsky, S., Solewicz, Y., Yampolskiy, M., Toh, J., Elovici, Y..  2018.  Digital Audio Signature for 3D Printing Integrity. IEEE Transactions on Information Forensics and Security. :1–1.

Additive manufacturing (AM, or 3D printing) is a novel manufacturing technology that has been adopted in industrial and consumer settings. However, the reliance of this technology on computerization has raised various security concerns. In this paper, we address issues associated with sabotage via tampering during the 3D printing process by presenting an approach that can verify the integrity of a 3D printed object. Our approach operates on acoustic side-channel emanations generated by the 3D printer’s stepper motors, which results in a non-intrusive and real-time validation process that is difficult to compromise. The proposed approach constitutes two algorithms. The first algorithm is used to generate a master audio fingerprint for the verifiable unaltered printing process. The second algorithm is applied when the same 3D object is printed again, and this algorithm validates the monitored 3D printing process by assessing the similarity of its audio signature with the master audio fingerprint. To evaluate the quality of the proposed thresholds, we identify the detectability thresholds for the following minimal tampering primitives: insertion, deletion, replacement, and modification of a single tool path command. By detecting the deviation at the time of occurrence, we can stop the printing process for compromised objects, thus saving time and preventing material waste. We discuss various factors that impact the method, such as background noise, audio device changes and different audio recorder positions.

Xie, P., Feng, J., Cao, Z., Wang, J..  2018.  GeneWave: Fast Authentication and Key Agreement on Commodity Mobile Devices. IEEE/ACM Transactions on Networking. 26:1688–1700.

Device-to-device communication is widely used for mobile devices and Internet of Things. Authentication and key agreement are critical to build a secure channel between two devices. However, existing approaches often rely on a pre-built fingerprint database and suffer from low key generation rate. We present GeneWave, a fast device authentication and key agreement protocol for commodity mobile devices. GeneWave first achieves bidirectional initial authentication based on the physical response interval between two devices. To keep the accuracy of interval estimation, we eliminate time uncertainty on commodity devices through fast signal detection and redundancy time cancellation. Then, we derive the initial acoustic channel response for device authentication. We design a novel coding scheme for efficient key agreement while ensuring security. Therefore, two devices can authenticate each other and securely agree on a symmetric key. GeneWave requires neither special hardware nor pre-built fingerprint database, and thus it is easyto-use on commercial mobile devices. We implement GeneWave on mobile devices (i.e., Nexus 5X and Nexus 6P) and evaluate its performance through extensive experiments. Experimental results show that GeneWave efficiently accomplish secure key agreement on commodity smartphones with a key generation rate 10× faster than the state-of-the-art approach.

Yu, Z., Du, H., Xiao, D., Wang, Z., Han, Q., Guo, B..  2018.  Recognition of Human Computer Operations Based on Keystroke Sensing by Smartphone Microphone. IEEE Internet of Things Journal. 5:1156–1168.

Human computer operations such as writing documents and playing games have become popular in our daily lives. These activities (especially if identified in a non-intrusive manner) can be used to facilitate context-aware services. In this paper, we propose to recognize human computer operations through keystroke sensing with a smartphone. Specifically, we first utilize the microphone embedded in a smartphone to sense the input audio from a computer keyboard. We then identify keystrokes using fingerprint identification techniques. The determined keystrokes are then corrected with a word recognition procedure, which utilizes the relations of adjacent letters in a word. Finally, by fusing both semantic and acoustic features, a classification model is constructed to recognize four typical human computer operations: 1) chatting; 2) coding; 3) writing documents; and 4) playing games. We recruited 15 volunteers to complete these operations, and evaluated the proposed approach from multiple aspects in realistic environments. Experimental results validated the effectiveness of our approach.

Lu, L., Yu, J., Chen, Y., Liu, H., Zhu, Y., Liu, Y., Li, M..  2018.  LipPass: Lip Reading-based User Authentication on Smartphones Leveraging Acoustic Signals. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications. :1466–1474.

To prevent users' privacy from leakage, more and more mobile devices employ biometric-based authentication approaches, such as fingerprint, face recognition, voiceprint authentications, etc., to enhance the privacy protection. However, these approaches are vulnerable to replay attacks. Although state-of-art solutions utilize liveness verification to combat the attacks, existing approaches are sensitive to ambient environments, such as ambient lights and surrounding audible noises. Towards this end, we explore liveness verification of user authentication leveraging users' lip movements, which are robust to noisy environments. In this paper, we propose a lip reading-based user authentication system, LipPass, which extracts unique behavioral characteristics of users' speaking lips leveraging build-in audio devices on smartphones for user authentication. We first investigate Doppler profiles of acoustic signals caused by users' speaking lips, and find that there are unique lip movement patterns for different individuals. To characterize the lip movements, we propose a deep learning-based method to extract efficient features from Doppler profiles, and employ Support Vector Machine and Support Vector Domain Description to construct binary classifiers and spoofer detectors for user identification and spoofer detection, respectively. Afterwards, we develop a binary tree-based authentication approach to accurately identify each individual leveraging these binary classifiers and spoofer detectors with respect to registered users. Through extensive experiments involving 48 volunteers in four real environments, LipPass can achieve 90.21% accuracy in user identification and 93.1% accuracy in spoofer detection.

Thoen, B., Wielandt, S., Strycker, L. De.  2018.  Fingerprinting Method for Acoustic Localization Using Low-Profile Microphone Arrays. 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN). :1–7.

Indoor localization of unknown acoustic events with MEMS microphone arrays have a huge potential in applications like home assisted living and surveillance. This article presents an Angle of Arrival (AoA) fingerprinting method for use in Wireless Acoustic Sensor Networks (WASNs) with low-profile microphone arrays. In a first research phase, acoustic measurements are performed in an anechoic room to evaluate two computationally efficient time domain delay-based AoA algorithms: one based on dot product calculations and another based on dot products with a PHAse Transform (PHAT). The evaluation of the algorithms is conducted with two sound events: white noise and a female voice. The algorithms are able to calculate the AoA with Root Mean Square Errors (RMSEs) of 3.5° for white noise and 9.8° to 16° for female vocal sounds. In the second research phase, an AoA fingerprinting algorithm is developed for acoustic event localization. The proposed solution is experimentally verified in a room of 4.25 m by 9.20 m with 4 acoustic sensor nodes. Acoustic fingerprints of white noise, recorded along a predefined grid in the room, are used to localize white noise and vocal sounds. The localization errors are evaluated using one node at a time, resulting in mean localization errors between 0.65 m and 0.98 m for white noise and between 1.18 m and 1.52 m for vocal sounds.

2019-01-16
Schneider, T., Schmidt, H..  2018.  NETSIM: A Realtime Virtual Ocean Hardware-in-the-loop Acoustic Modem Network Simulator. 2018 Fourth Underwater Communications and Networking Conference (UComms). :1–5.
This paper presents netsim, a combined software/hardware system for performing realtime realistic operation of autonomous underwater vehicles (AUVs) with acoustic modem telemetry in a virtual ocean environment. The design of the system is flexible to the choice of physical link hardware, allowing for the system to be tested against existing and new modems. Additionally, the virtual ocean channel simulator is designed to perform in real time by coupling less frequent asynchronous queries to high-fidelity models of the ocean environment and acoustic propagation with frequent pertubation-based updates for the exact position of the simulated AUVs. The results demonstrate the performance of this system using the WHOI Micro-Modem 2 hardware in the virtual ocean environment of the Arctic Beaufort Sea around 73 degrees latitude. The acoustic environment in this area has changed dramatically in recent years due to the changing climate.
Kimmich, J. M., Schlesinger, A., Tschaikner, M., Ochmann, M., Frank, S..  2018.  Acoustical Analysis of Coupled Rooms Applied to the Deutsche Oper Berlin. 2018 Joint Conference - Acoustics. :1–9.
The aim of the project SIMOPERA is to simulate and optimize the acoustics in large and complex rooms, with special focus on the Deutsche Oper Berlin as an example of application. Firstly, characteristic subspaces of the opera are considered such as the orchestra pit, the stage and the auditorium. Special attention is paid to the orchestra pit, where high sound pressure levels can occur, leading to noise related risks for the musicians. However, lowering the sound pressure level in the orchestra pit should not violate other objectives as the propagation of sound into the auditorium, the balance between the stage performers and the orchestra across the hall, and the mutual audibility between performers and orchestra members. For that reason, a hybrid simulation method consisting of the wave-based Finite Element Method (FEM) and the Boundary Element Method (BEM) for low frequencies and geometrical methods like the mirror source method and ray tracing for higher frequencies is developed in order to determine the relevant room acoustic quantities such as impulse response functions, reverberation time, clarity, center time etc. Measurements in the opera will continuously accompany the numerical calculations. Finally, selected constructive means for reducing the sound level in the orchestra pit will be analyzed.