The process of classifying audio data into several classes or categories is referred to as audio classification. The purpose of speaker recognition, one particular use of audio classification, is to recognize a person based on the characteristics of their speech. The phrase "voice recognition" refers to both speaker and speech recognition tasks. Speaker verification systems have grown significantly in popularity recently for a variety of uses, such as security measures and individualized help. Computers that have been taught to recognize individual voices can swiftly translate speech or confirm a speaker’s identification as part of a security procedure by identifying the speaker. Four decades of research have gone into speaker recognition, which is based on the acoustic characteristics of speech that differ from person to person. Some systems use auditory input from those seeking entry, just like fingerprint sensors match input fingerprint markings with a database or photographic attendance systems map inputs to a database. Personal assistants, like Google Home, for example, are made to limit access to those who have been given permission. Even under difficult circumstances, these systems must correctly identify or recognize the speaker. This research proposes a strong deep learning-based speaker recognition solution for audio categorization. We suggest self-augmenting the data utilizing four key noise aberration strategies to improve the system’s performance. Additionally, we conduct a comparison study to examine the efficacy of several audio feature extractors. The objective is to create a speaker identification system that is extremely accurate and can be applied in practical situations.

The goal of this project is to use hardware components built-in manufacturing faults as mobile phone IDs. We assessed the applicability of several I/O-related cell phone components, including sensors. Through this process, the focus was on creating hardware issue samples that could then be categorised using the device s speaker and microphone. In our technique, an audio sample was created by playing a known audio file via a mobile phone s speakers and then recording the sound using the same device. The impact of important variables on sample accuracy was examined using a variety of different sample groups. After collecting the samples, the frequency responses were extracted and classified. Data were categorised using a variety of classifiers, with certain label and sample group configurations achieving an accuracy of over 94.4\%. The conclusions of this article suggest that speaker and mike production faults may be exploited for device authentication.

In this paper, we present a platform based on a modular approach coupled with powerful algorithms for accurate detection and identification of chemical compounds. The system relies on multi-SAW (Surface Acoustic Wave) sensors that are functionalized differently, resulting in multi-responses that collectively constitute a fingerprint of the chemical compound. A prototype has been developed and the overall system, including the design of SAW module, the acquisition system, learning algorithms and online recognition of various compounds, has been tested and validated. The results showed a reliable and accurate system with a perfect score of 100\% recognition of DMMP.

This study presents a novel method of authentication in digital environment in which each element of authentication is linked to one another. Having multiple factors to authenticate and deriving co-relations among these increases the safety and security of the device. Types of behavioral and acoustic patterns which are to be considered are GPS, accelerometer, microphone \& speaker fingerprint, lip \& tongue movement sensing and pinna shape sensing. Pattern data from different sensors is compared and cross checked. Having multiple factors to authenticate and deriving co-relations among these increases the security of device. The main advantage of multi factor behavioral authentication is that the verification is done dynamically and continuously to provide real time security. All authentication activities are carried out in the background without the user being interrupted. Furthermore, because these authentication approaches do not involve the user, the user experience is enhanced along with the security of the device.

Audio fingerprinting is the method involved with addressing a sound sign minimally with the aid of isolating vital highlights of the sound substance a part of the good sized makes use of of acoustic fingerprinting includes substance-based sound healing broadcast watching and so forth it lets in gazing the sound free of its arrangement and with out the requirement for metadata it really works by using studying frequency styles and tracking down a fit internal its statistics set of tunes this utility tries to understand the songs through the use of a time-frequency graph primarily based on an audio fingerprint that is known as a spectrogram the software program utilizes a cell phone implicit microphone that assembles a concise instance of a legitimate that is played it analyzes the outside sound and seeks a comparable suit on a database in which thousands and thousands of songs are saved based totally on an acoustic fingerprint when the software reveals a in shape it retrieves records such as the album track name original music and so forth.

Research in underwater communication is rapidly becoming attractive due to its various modern applications. An efficient mechanism to secure such communication is via physical layer security. In this paper, we propose a novel physical layer authentication (PLA) mechanism in underwater acoustic communication networks where we exploit the position/location of the transmitter nodes to achieve authentication. We perform transmitter position estimation from the received signals at reference nodes deployed at fixed positions in a predefined underwater region. We use time of arrival (ToA) estimation and derive the distribution of inherent uncertainty in the estimation. Next, we perform binary hypothesis testing on the estimated position to decide whether the transmitter node is legitimate or malicious. We then provide closed-form expressions of false alarm rate and missed detection rate resulted from binary hypothesis testing. We validate our proposal via simulation results, which demonstrate errors’ behavior against the link quality, malicious node location, and receiver operating characteristic (ROC) curves. We also compare our results with the performance of previously proposed fingerprint mechanisms for PLA in underwater acoustic communication networks, for which we show a clear advantage of using the position as a fingerprint in PLA.

This paper reports the commercialized large area (20×30mm2), multi-functional, thin form-factor, ultrasound fingerprint technology for under display integration in mobile devices. This technology consists of a thin piezoelectric polymer ultrasonic transceiver layer deposited on highly scalable 2D pixel array fabricated using low temperature polysilicon (LTPS) thin film transistors (TFT) circuitry on glass substrate. The technology not only delivers a high quality under display fingerprint scanner for biometric authentication, but also enables multiple value-added features including heart rate monitor, ultrasound based passive stylus, force sensor, and a contact gesture sensor. The large sensing area removes the requirement for accurate finger placement and therefore provides a better user experience for fingerprint authentication. Larger sensing area is also used for multi-finger authentication for enhanced security. Furthermore, the integrated multifunctional sensing enriches the user experience in the scenarios of gaming, education, health indicator monitoring etc.

Partial discharge localization in power transformers is of utmost importance, requiring an effective evaluation method to identify the location of such events precisely. Antenna placement poses challenges within power transformers, as improper positioning can significantly affect localization precision. This paper introduces an evaluation of the fingerprinting method for ultra-high frequency partial discharge localization. The fingerprinting method, commonly employed in wireless localization systems, is utilized to assess the accuracy of partial discharge localization. The proposed method leverages fingerprinting analysis and received signal strength to evaluate partial discharge events in power transformers. Experimental partial discharge measurements are conducted on a power transformer model provided by Tesla Power Company. The results include the average received signal strength at each measurement position and the distance error of the partial discharge location determined using the fingerprinting method. This research contributes to assessing partial discharge in power transformers, offering valuable insights for enhancing their health and performance evaluation.

The two-factor authentication (2FA) has become pervasive as the mobile devices become prevalent. Existing 2FA solutions usually require some form of user involvement, which could severely affect user experience and bring extra burdens to users. In this work, we propose a secure 2FA that utilizes the individual acoustic fingerprint of the speaker/microphone on enrolled device as the second proof. The main idea behind our system is to use both magnitude and phase fingerprints derived from the frequency response of the enrolled device by emitting acoustic beep signals alternately from both enrolled and login devices and receiving their direct arrivals for 2FA. Given the input microphone samplings, our system designs an arrival time detection scheme to accurately identify the beginning point of the beep signal from the received signal. To achieve a robust authentication, we develop a new distance mitigation scheme to eliminate the impact of transmission distances from the sound propagation model for extracting stable fingerprint in both magnitude and phase domain. Our device authentication component then calculates a weighted correlation value between the device profile and fingerprints extracted from run-time measurements to conduct the device authentication for 2FA. Our experimental results show that our proposed system is accurate and robust to both random impersonation and Man-in-the-middle (MiM) attack across different scenarios and device models.

An efficient broadcast monitoring system is really needed in Myanmar music industry to solve the issues of copyright infringements and illegal benefit-sharing between artists and broadcasting stations. In this paper, a broadcast monitoring system is proposed for Myanmar FM radio stations by utilizing Mel Frequency Cepstral Coefficient (MFCC) based audio fingerprinting. The proposed system is easy to implement and achieves the correct and speedy music identification even for noisy and distorted broadcast audio streams. In this system, we deploy an audio fingerprint database of 4,379 songs and broadcast audio streams of 3 local FM channels of Myanmar to evaluate the performance of the proposed system. Experimental results show that the system achieves reliable performance.

The security of Energy Data collection is the basis of achieving reliability and security intelligent of smart grid. The newest security communication of Data collection is Zero Trust communication; The Strategy of Zero Trust communication is that don’t trust any device of outside or inside. Only that device authenticate is successful and software and hardware is more security, the Energy intelligent power system allow the device enroll into network system, otherwise deny these devices. When the device has been communicating with the Energy system, the Zero Trust still need to detect its security and vulnerability, if device have any security issue or vulnerability issue, the Zero Trust deny from network system, it ensures that Energy power system absolute security, which lays a foundation for the security analysis of intelligent power unit.

How can high-level directives concerning risk, cybersecurity and compliance be operationalized in the central nervous system of any organization above a certain complexity? How can the effectiveness of technological solutions for security be proven and measured, and how can this technology be aligned with the governance and financial goals at the board level? These are the essential questions for any CEO, CIO or CISO that is concerned with the wellbeing of the firm. The concept of Zero Trust (ZT) approaches information and cybersecurity from the perspective of the asset to be protected, and from the value that asset represents. Zero Trust has been around for quite some time. Most professionals associate Zero Trust with a particular architectural approach to cybersecurity, involving concepts such as segments, resources that are accessed in a secure manner and the maxim “always verify never trust”. This paper describes the current state of the art in Zero Trust usage. We investigate the limitations of current approaches and how these are addressed in the form of Critical Success Factors in the Zero Trust Framework developed by ON2IT ‘Zero Trust Innovators’ (1). Furthermore, this paper describes the design and engineering of a Zero Trust artefact that addresses the problems at hand (2), according to Design Science Research (DSR). The last part of this paper outlines the setup of an empirical validation trough practitioner oriented research, in order to gain a broader acceptance and implementation of Zero Trust strategies (3). The final result is a proposed framework and associated technology which, via Zero Trust principles, addresses multiple layers of the organization to grasp and align cybersecurity risks and understand the readiness and fitness of the organization and its measures to counter cybersecurity risks.

Under the situation of regular epidemic prevention and control, teleworking has gradually become a normal working mode. With the development of modern information technologies such as big data, cloud computing and mobile Internet, it's become a problem that how to build an effective security defense system to ensure the information security of teleworking in complex network environment while ensuring the availability, collaboration and efficiency of teleworking. One of the solutions is Zero Trust Network(ZTN), most enterprise infrastructures will operate in a hybrid zero trust/perimeter-based mode while continuing to invest in IT modernization initiatives and improve organization business processes. In this paper, we have systematically studied the zero trust principles, the logical components of zero trust architecture and the key technology of zero trust network. Based on the abstract model of zero trust architecture and information security technologies, a prototype has been realized which suitable for iOS terminals to access enterprise resources safely in teleworking mode.