Artykuły w czasopismach: „Voice biometrics”

1

Joshi, Amogh. "Future of Cybersecurity: A Study on Biometric Scans". International Journal for Research in Applied Science and Engineering Technology 9, nr 11 (30.11.2021): 1180–85. http://dx.doi.org/10.22214/ijraset.2021.38913.

Pełny tekst źródła

Streszczenie:

Abstract: Biometrics is a statistical analysis of people's unique behavioral characteristics. The technology is used for CYBERSECURITY. The basics of biometric authentication is that to stop security breaches by analyzing a person’s unique behavioral characteristics. The term biometrics is derived from the Greek word’s “bios” meaning life and “metricos” meaning to measure. It refers to measurements of physical and biological characteristics of the human body. In this paper, we have studied some biometric methods such as facial recognition, iris recognition, Retinal Recognition, voice recognition. Keywords: Biometrics, Cybersecurity, Biometric Scan, Retinal Scan, Iris Scan, Gait, Voice Recognition.

Style APA, Harvard, Vancouver, ISO itp.

2

Markowitz, Judith A. "Voice biometrics". Communications of the ACM 43, nr 9 (wrzesień 2000): 66–73. http://dx.doi.org/10.1145/348941.348995.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

3

K. P. Ajitha, Gladis, i D. Sharmila. "Systematic digital signal processing approach in various biometric identification". i-manager's Journal on Digital Signal Processing 10, nr 2 (2022): 7. http://dx.doi.org/10.26634/jdp.10.2.19290.

Pełny tekst źródła

Streszczenie:

Biometrics are unique physical characteristics, such as fingerprints, that can be used for automatic recognition. Biometric identifiers are often classified as physiological characteristics associated with body shape. The goal is to capture a piece of biometric data from that person. It could be a photograph of their face, a recording of their voice, or a picture of their fingerprints. While there are numerous types of biometrics for authentication, the six most common are facial, voice, iris, near-field communication, palm or finger vein patterns, and Quick Response (QR) code. Biometrics is a subset of the larger field of human identification science. This paper explores computational approaches to speaker recognition, face recognition, speech recognition, and fingerprint recognition to assess the overall state of digital signal processing in biometrics.

Style APA, Harvard, Vancouver, ISO itp.

4

D S, Dr Dinesh Kumar. "Human Authentication using Face, Voice and Fingerprint Biometrics". International Journal for Research in Applied Science and Engineering Technology 9, nr VII (15.07.2021): 853–62. http://dx.doi.org/10.22214/ijraset.2021.36381.

Pełny tekst źródła

Streszczenie:

Multimodal biometric approaches are growing in importance for personal verification and identification, since they provide better recognition results and hence improve security compared to biometrics based on a single modality. In this project, we present a multimodal biometric system that is based on the fusion of face, voice and fingerprint biometrics. For face recognition, we employ Haar Cascade Algorithm, while minutiae extraction is used for fingerprint recognition and we will be having a stored code word for the voice authentication, if any of these two authentication becomes true, the system consider the person as authorized person. Fusion at matching score level is then applied to enhance recognition performance. In particular, we employ the product rule in our investigation. The final identification is then performed using a nearest neighbour classifier which is fast and effective. Experimental results confirm that our approach achieves excellent recognition performance, and that the fusion approach outperforms biometric identification based on single modalities.

Style APA, Harvard, Vancouver, ISO itp.

5

Sable, Harsh, i Divya Bajpai Tripathy. "A Review on Comparative Analysis on Different Sort of Physiological and Behavioral Biometric Framework". International Journal of Advance Research and Innovation 9, nr 2 (2021): 1–9. http://dx.doi.org/10.51976/ijari.922101.

Pełny tekst źródła

Streszczenie:

Biometrics as the investigation of seeing an individual ward on their physical or conduct characteristics, biometric have now been conveyed in diverse business, ordinary resident and national security applications. Customarily the usage of biometrics devices has improved our capacity to give approved entry to material foundations. Biometric is the usage of a person's novel physiological, lead, and morphological trademark to give valuable person distinguishing proof. Biometric structures that are starting at now available today break down fingerprints, engravings, iris and retina models, and face. Mechanisms that are similar to biometrics anyway are not named such are lead systems, for instance, voice, imprint and keystroke mechanisms. These days biometrics is in effect effectively executed in numerous fields like measurable, security, recognizable proof and approval frameworks.

Style APA, Harvard, Vancouver, ISO itp.

6

Jansen, Fieke, Javier Sánchez-Monedero i Lina Dencik. "Biometric identity systems in law enforcement and the politics of (voice) recognition: The case of SiiP". Big Data & Society 8, nr 2 (lipiec 2021): 205395172110636. http://dx.doi.org/10.1177/20539517211063604.

Pełny tekst źródła

Streszczenie:

Biometric identity systems are now a prominent feature of contemporary law enforcement, including in Europe. Often advanced on the premise of efficiency and accuracy, they have also been the subject of significant controversy. Much attention has focussed on longer-standing biometric data collection, such as finger-printing and facial recognition, foregrounding concerns with the impact such technologies can have on the nature of policing and fundamental human rights. Less researched is the growing use of voice recognition in law enforcement. This paper examines the case of the recent Speaker Identification Integrated Project, a European wide initiative to create the first international and interoperable database of voice biometrics, now the third largest biometric database at Interpol. Drawing on Freedom of Information requests, interviews and public documentation, we outline the emergence and features of SiiP and explore how voice is recognised and attributed meaning. We understand Speaker Identification Integrated Project as constituting a particular ‘regime of recognition’ premised on the use of soft biometrics (age, language, accent and gender) to disembed voice in order to optimise for difference. This, in turn, has implications for the nature and scope of law enforcement, people's position in society, and justice concerns more broadly.

Style APA, Harvard, Vancouver, ISO itp.

7

Kumar Singha, Anjani, Anshu Singla i Rajneesh Kumar Pandey. "STUDY AND ANALYSIS ON BIOMETRICS AND FACE RECOGNITION METHODS". EPH - International Journal of Science And Engineering 2, nr 2 (27.06.2016): 29–34. http://dx.doi.org/10.53555/eijse.v2i2.145.

Pełny tekst źródła

Streszczenie:

Human Biometrics is a rising technology, which has been broadly used in forensics, safe access and top-security prison. A biometric system is primarily a pattern recognition system that recognizes a person by determining the verification by using his different biological features i.e. Fingerprint, retina-scan, iris scan, hand geometry, and face recognition are important physiological biometrics and behavioral trait are Voice recognition, keystroke-scan, and signature-scan. In this paper different biometrics techniques such as Iris scan, retina scan and face recognition techniques are discussed.

Style APA, Harvard, Vancouver, ISO itp.

8

Czyzewski, Andrzej. "Enhancing voice biometric security: Evaluating neural network and human capabilities in detecting cloned voices". Journal of the Acoustical Society of America 155, nr 3_Supplement (1.03.2024): A68. http://dx.doi.org/10.1121/10.0026827.

Pełny tekst źródła

Streszczenie:

This study assesses speaker verification efficacy in detecting cloned voices, particularly in safety-critical applications such as healthcare documentation and banking biometrics. It compares deeply trained neural networks like the Deep Speaker with human listeners in recognizing these cloned voices, underlining the severe implications of voice cloning in these sectors. Cloned voices in healthcare could endanger patient safety by altering medical records, causing inaccurate diagnoses and treatments. In banking, they threaten biometric security, increasing the risk of financial fraud and identity theft. The research reveals the neural network's superiority over human detection in pinpointing cloned voices, underscoring the urgent need for sophisticated AI-based security. The study stresses the importance of developing robust defenses against voice cloning attacks, which can have critical consequences in healthcare and fintech. This research is crucial for enhancing security in areas reliant on voice authentication, safeguarding confidential data, and preserving the integrity of vital services. The Polish National Center for Research and Development (NCBR) initially supported the project “BIOPUAP” (POIR.01.01.01-0092/19), which focused on digital banking. Subsequently, the project “ADMEDVOICE” (INFOSTRATEG4/0003/2022), also supported by the NCBR, conducted further research into voice cloning in the healthcare sector.

Style APA, Harvard, Vancouver, ISO itp.

9

Chinyemba, Melissa K., i Jackson Phiri. "Gaps in the Management and Use of Biometric Data: A Case of Zambian Public and Private Institutions". Zambia ICT Journal 2, nr 1 (29.06.2018): 35–43. http://dx.doi.org/10.33260/zictjournal.v2i1.49.

Pełny tekst źródła

Streszczenie:

The current physical and cybersecurity systems rely on traditional three-factor authentication to mitigate the threats posed by insider attacks. Key is the use of biometric information. Biometrics are a unique measurement and analysis of the unique physiological special traits such as voice, eye structure and others that can be used in the discipline of varying person identification. Biometry, which is the analysis of these biometrics is a complex process but guarantees identification and non-repudiation. If used to identify humans then several issues such as where is the biometric data stored? Who has access to it? And how does one ensure that such data satisfies the principle of availability. To achieve availability, secure transportation arises. To achieve transportation, non-repudiation, confidentiality and authentication, integrity arise. A storage and transport system is recommended to these challenges. In this paper, we explore the gaps into how public and private institution store and manage biometrics information. We benchmarked each organization again the ISO 30107 and ISO 24745. Our results show that while most companies are adopting and using biometrics systems, few have adopted the ISO biometrics standards that govern the storage and management of biometric information and hence creating security risk.

Style APA, Harvard, Vancouver, ISO itp.

10

Salama, Gerges M., Safaa El-Gazar, Basma Omar, Rana M. Nassar, Ashraf A. M. Khalaf, Ghada M. El-banby, Hesham F. A. Hamed, Walid El-shafai i Fathi E. Abd el-samie. "Cancelable biometric system for IoT applications based on optical double random phase encoding". Optics Express 30, nr 21 (28.09.2022): 37816. http://dx.doi.org/10.1364/oe.466101.

Pełny tekst źródła

Streszczenie:

The security issue is essential in the Internet-of-Things (IoT) environment. Biometrics play an important role in securing the emerging IoT devices, especially IoT robots. Biometric identification is an interesting candidate to improve IoT usability and security. To access and control sensitive environments like IoT, passwords are not recommended for high security levels. Biometrics can be used instead, but more protection is needed to store original biometrics away from invaders. This paper presents a cancelable multimodal biometric recognition system based on encryption algorithms and watermarking. Both voice-print and facial images are used as individual biometrics. Double Random Phase Encoding (DRPE) and chaotic Baker map are utilized as encryption algorithms. Verification is performed by estimating the correlation between registered and tested models in their cancelable format. Simulation results give Equal Error Rate (EER) values close to zero and Area under the Receiver Operator Characteristic Curve (AROC) equal to one, which indicates the high performance of the proposed system in addition to the difficulty to invert cancelable templates. Moreover, reusability and diversity of biometric templates is guaranteed.

Style APA, Harvard, Vancouver, ISO itp.

11

Gu, Datong, Minh Nguyen i Weiqi Yan. "Cross Models for Twin Recognition". International Journal of Digital Crime and Forensics 8, nr 4 (październik 2016): 26–36. http://dx.doi.org/10.4018/ijdcf.2016100103.

Pełny tekst źródła

Streszczenie:

Nowadays, Biometrics has become a popular tool in personal identification as it can use physiological or behavioral characteristics to identify individuals. Recent advances in information technology has increased the accuracy of biometric to another level, there is still a slew of problems existed, such as complex environment, aging and unique problems. Among many classes of identifications, recognizing twins is one of the most difficult tasks as they resemble each other. This affects the use of biometrics in general cases and raises potential risks of biometrics in access control. In this paper, the authors manage to distinguish twins using four different models, namely, face recognition, ear recognition, voice recognition and lip movement recognition. Their results show that voice recognition has the best performance in twin recognition with 100% accuracy. This is much higher than that of face recognition and ear recognition (with 58% and 53% respectively); and lip movement recognition that yields 76% accuracy.

Style APA, Harvard, Vancouver, ISO itp.

12

Gupta, Vikas, Shashikant Garade, Shriyash Kothekar, Darshana Meshram, Shraddha Wankhede i Prof Rajshri Pote. "An Investigative Study of Voice Functioned Smart Door Lock System". International Journal of Research Publication and Reviews 04, nr 01 (2023): 1920–24. http://dx.doi.org/10.55248/gengpi.2023.4154.

Pełny tekst źródła

Streszczenie:

This article discusses how speech recognition can improve security for persons and property while making door systems more accessible to people with impairments. Facial recognition, fingerprint scanning, and iris scanning are examples of popular biometric technologies. Based on features and qualities used to identify various people for the safety and security of their lives and property, these biometric identifiers are distinctive and one-of a-kind. Sadly, these biometrics are vulnerable to hacking. A pin or password can be cracked, a person's finger can be severed to perform a fingerprint scan, an eyeball can be removed to perform an iris scan, and a person's photo can be used to perform facial recognition. With the help of speech recognition biometrics technology, these obstacles can be reduced. Technology for voice biometrics is more precise, swifter, more practical. In order to give individuals a quick way to open their doors and simultaneously protect their safety and security, this research study intends to design a door access control system that makes use of voice recognition algorithms. The testing phase and the training phase are the two phases that make up the system. The attributes of a speech are extracted and stored in a database during the training phase. Using voice recognition algorithms and vocal models, the intents from a person's address would be derived during the testing phase. A user is given access if a match is detected.

Style APA, Harvard, Vancouver, ISO itp.

13

., Himanshi, Trisha Gulati i Yasha Hasija. "Biometrics in Healthcare". INTERNATIONAL JOURNAL OF ADVANCED PRODUCTION AND INDUSTRIAL ENGINEERING 3, nr 2 (15.04.2018): 13–17. http://dx.doi.org/10.35121/ijapie201804223.

Pełny tekst źródła

Streszczenie:

Biometrics is the discipline to measure physical human characteristics for the identification and authentication of an individual. Since ancient times, people have used voice, face, and other characteristics for the identification of an individual. With evolution, we take the individual characteristics like fingerprint scans, retina and iris images, etc., as inputs to the computer systems and then store or verify them with existing records. This report discusses biometrics and its recent roles found in the field of healthcare, medicine, genetics, and biotechnology. It includes the concept of biometrics, the system used for biometric recognition and its working, types of biometric systems, the different system algorithms applied, and system modules which are well illustrated with flow charts and block diagrams. Some of the health institutes in developed countries have started using biometric systems for checking patients and/or doctors. Biometry has enabled the proper organization and storage of the health records of individuals in medical institutes. Biometric authentication is also finding a distinct role in foiling medical claims fraud highlighting the advantages it. Even after processing via a very accurate biometric system, there is a chance of a false result due to some disease or injury to the body part subjected to biometry or faulty system leading to some error. There is also a possibility that the biometric system may harm our bodies. Moreover, biometric records need really tight system security to prevent any kind of misuse. Biometrics has a great potential to find a lot more uses in the field of healthcare. Many ideas are being proposed for implementation. In the future, biometrics can be used to detect potential disease and risks by using methods like adiposity measurement and Gas Discharge Visualization (GDV).

Style APA, Harvard, Vancouver, ISO itp.

14

Rajvanshi, Saumya, Shiv Chauhan i Savneet Kaur. "A New Wave in Biometric System: Systematic Study". CGC International Journal of Contemporary Technology and Research 4, nr 2 (5.08.2022): 300–305. http://dx.doi.org/10.46860/cgcijctr.2022.07.31.300.

Pełny tekst źródła

Streszczenie:

Biometric system is a technique used to identify a person using its personal identification methods. The main concept of biometric systems is to provide confidentiality and security to the user. A number of biometric systems are introduced but some systems are widely used and are famous because of their usage and security they provide. Physiological and Behavioral biometrics are the two types of biometric systems. Biometric systems include physiological biometrics like face recognition, fingerprint recognition, iris recognition and behavioral biometrics like signature recognition and voice recognition. All these recognition systems are discussed in this research paper. Biometric systems work on three levels: Enrollment, Verification, and Identification. Enrollment is the process in which patterns are captured from the user and stored in the database. Verification means to confirm that the sample entered by the user belongs to him or not. When the user wants to access the data then the user must use his/her biometrics so that the system checks that the person who wants to access the data is the real owner of the data or not. This process is identification. All three levels are the working levels of the Biometric System. In earlier years, biometrics were used only at ground levels to provide basic security to data but now the tables have turned. It is playing a major role in providing security to our data. Biometrics are not only used in day-to-day life in phone unlocking, phone assistants, attendance systems but also used at advanced levels like in airports, border security, cloud computing etc. In this research paper, we will discuss the future scope of biometric systems and how it could even change the future.

Style APA, Harvard, Vancouver, ISO itp.

15

Conti, J. P. "Look who's talking [voice biometrics]". Engineering & Technology 2, nr 1 (1.01.2007): 24–25. http://dx.doi.org/10.1049/et:20070101.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

16

Morgen, Bob. "Voice biometrics for customer authentication". Biometric Technology Today 2012, nr 2 (luty 2012): 8–11. http://dx.doi.org/10.1016/s0969-4765(12)70054-1.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

17

Jain, Rubal, i Chander Kant. "Attacks on Biometric Systems: An Overview". International Journal of Advances in Scientific Research 1, nr 7 (3.09.2015): 283. http://dx.doi.org/10.7439/ijasr.v1i7.1975.

Pełny tekst źródła

Streszczenie:

Biometrics is a pattern recognition system that refers to the use of different physiological (face, fingerprints, etc.) and behavioral (voice, gait etc.) traits for identification and verification purposes. A biometrics-based personal authentication system has numerous advantages over traditional systems such as token-based (e.g., ID cards) or knowledge-based (e.g., password) but they are at the risk of attacks. This paper presents a literature review of attack system architecture and makes progress towards various attack points in biometric system. These attacks may compromise the template resulting in reducing the security of the system and motivates to study existing biometric template protection techniques to resist these attacks.

Style APA, Harvard, Vancouver, ISO itp.

18

Milewski, Krzysztof, Szymon Zaporowski i Andrzej Czyżewski. "Comparison of the Ability of Neural Network Model and Humans to Detect a Cloned Voice". Electronics 12, nr 21 (30.10.2023): 4458. http://dx.doi.org/10.3390/electronics12214458.

Pełny tekst źródła

Streszczenie:

The vulnerability of the speaker identity verification system to attacks using voice cloning was examined. The research project assumed creating a model for verifying the speaker’s identity based on voice biometrics and then testing its resistance to potential attacks using voice cloning. The Deep Speaker Neural Speaker Embedding System was trained, and the Real-Time Voice Cloning system was employed based on the SV2TTS, Tacotron, WaveRNN, and GE2E neural networks. The results of attacks using voice cloning were analyzed and discussed in the context of a subjective assessment of cloned voice fidelity. Subjective test results and attempts to authenticate speakers proved that the tested biometric identity verification system might resist voice cloning attacks even if humans cannot distinguish cloned samples from original ones.

Style APA, Harvard, Vancouver, ISO itp.

19

Danish, Aafreen, Khushali Hedau, Diksha Ukey, Anisha Walde, Uzma Sohail Sheikh i Prof Akbar Nagani. "Fingerprint,Face and Voice Recognition Based Attendance Monitoring System". International Journal for Research in Applied Science and Engineering Technology 10, nr 4 (30.04.2022): 749–52. http://dx.doi.org/10.22214/ijraset.2022.41346.

Pełny tekst źródła

Streszczenie:

Abstract: In This project aims to record the attendance without manual intervention. In the area of technology that changes and modifies daily, use biometrics is the most popular and trending technology. Taking attendance manually for a class of almost 60-80 students can be a time-consuming task if thought of it in a long run Each person has a unique biometric feature such as fingerprint, face structure, voice detection etc. Keywords— Boimetrics, Fringerprint, Face Structure,Voice Detection.

Style APA, Harvard, Vancouver, ISO itp.

20

Booysens, Aimee, i Serestina Viriri. "Exploration of Ear Biometrics Using EfficientNet". Computational Intelligence and Neuroscience 2022 (31.08.2022): 1–14. http://dx.doi.org/10.1155/2022/3514807.

Pełny tekst źródła

Streszczenie:

Biometrics is the recognition of a human using biometric characteristics for identification, which may be physiological or behavioral. The physiological biometric features are the face, ear, iris, fingerprint, and handprint; behavioral biometrics are signatures, voice, gait pattern, and keystrokes. Numerous systems have been developed to distinguish biometric traits used in multiple applications, such as forensic investigations and security systems. With the current worldwide pandemic, facial identification has failed due to users wearing masks; however, the human ear has proven more suitable as it is visible. Therefore, the main contribution is to present the results of a CNN developed using EfficientNet. This paper presents the performance achieved in this research and shows the efficiency of EfficientNet on ear recognition. The nine variants of EfficientNets were fine-tuned and implemented on multiple publicly available ear datasets. The experiments showed that EfficientNet variant B8 achieved the best accuracy of 98.45%.

Style APA, Harvard, Vancouver, ISO itp.

21

Gupta, Ms Neha. "A New Wave in Biometric System: Systematic Study incorporated with Artificial Intelligence". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, nr 05 (10.05.2024): 1–5. http://dx.doi.org/10.55041/ijsrem33563.

Pełny tekst źródła

Streszczenie:

Biometric system is a technique used to identify a person using its personal identification methods. The main concept of biometric systems is to provide confidentiality and security to the user. A number of biometric systems are introduced but some systems are widely used and are famous because of their usage and security they provide. Physiological and Behavioral biometrics are the two types of biometric systems. Biometric systems include physiological biometric like face recognition, finger print recognition, ir is recognition and behavioral biometrics like signature recognition and voice recognition. All these recognition systems are discussed in this research paper. Biometric systems work on three levels: Enrollment, Verification, and Identification. Enrollment is the process in which patterns are captured from the user and stored in the database. Verification means to confirm that the sample entered by the user belongs to him or not. When the user wants to access the data then the user must use his/her biometrics that the systematic hacks that the person who wants to access the data is the real owner of the data or not. This process is identification. All three levels are the working levels of the Biometric System. In earlier years, biometrics was used only at ground levels to provide basic security to data but now the tables have turned. It is playing a major role in providing security to our data. Biometrics are not only used in day-to-day life in phone unlocking, phone assistants, attendance systems but also used at advanced levels like in airports, border security, cloud computing etc. In this research paper, we will discuss the future scope of biometric systems and how it could even change the future.

Style APA, Harvard, Vancouver, ISO itp.

22

Nagaraj, Srinivasan, G. V. S. P. Raju, G. Apparao i B. Kishore. "A Bio-Crypto Protocol for Password Protection Using ECC". Bulletin of Electrical Engineering and Informatics 4, nr 1 (1.03.2015): 67–72. http://dx.doi.org/10.11591/eei.v4i1.318.

Pełny tekst źródła

Streszczenie:

In information security the following security parameters like, integrity , non repudiation and confidentiality , authentication must be satisfied. To avoid thievery of organization resources it needs be secured in more efficient way and there is always demand for different levels of security attacks include virus , brute force and Eveadroper in business that organizations make use of voice biometrics an attractive low-cost. Voice biometrics is the cheapest among the other biometrics and used all levels for management to buy readily available metric and it is the way of identifying individuals remotely with high level of accuracy . In this work, we have been designed a new password- authentication approach that provides security using voice biometrics for authentication and uses the device itself into an authenticator which uses voice itself as its passwords and we are primarily interested in keys that can be temporally reproduced on the same device from the same user’s voice. Public and private keys are generated randomly from the user's voice and stored in the voice file(.wav).This Method uses voice recognition , include the operation of register( recording feature ) or voice prints and storing of one or more voice passwords into the database. It uses ECDSA to perform the authentication process that matching the voice sample with the database. The recognition, entity makes the database to decide that the sample is matched to perform an operation or not. Our proposed approach generates cryptographic keys from voice input itself and this algorithm developed an adhoc basis. It can effectively defend attacks specially brute force attack in system networks.

Style APA, Harvard, Vancouver, ISO itp.

23

Singh, Law Kumar, Munish Khanna, Shankar Thawkar i Jagadeesh Gopal. "Robustness for Authentication of the Human Using Face, Ear, and Gait Multimodal Biometric System". International Journal of Information System Modeling and Design 12, nr 1 (styczeń 2021): 39–72. http://dx.doi.org/10.4018/ijismd.2021010103.

Pełny tekst źródła

Streszczenie:

Biometrics is the science that deals with personal human physiological and behavioral characteristics such as fingerprints, handprints, iris, voice, face recognition, signature recognition, ear recognition, and gait recognition. Recognition using a single trait has several problems and multimodal biometrics system is one of the solutions. In this work, the novel and imperative biometric feature gait is fused with face and ear biometric features for authentication and to overcome problems of the unimodal biometric recognition system. The authors have also applied various normalization methods to sort out the best solution for such a challenge. The feature fusion of the proposed multimodal biometric system has been tested using Min-Max and Z-score techniques. The computed results demonstrate that Z-Score outperforms the Min-Max technique. It is deduced that the Z-score is a promising method that generates a high recognition rate of 95% and a false acceptance rate of 10%.

Style APA, Harvard, Vancouver, ISO itp.

24

Gold, Steve. "Voice biometrics, London, 28–29 november". Infosecurity 4, nr 8 (listopad 2007): 11. http://dx.doi.org/10.1016/s1754-4548(07)70187-0.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

25

Golden, Paul. "Voice biometrics – the Asia Pacific experience". Biometric Technology Today 2012, nr 4 (kwiecień 2012): 10–11. http://dx.doi.org/10.1016/s0969-4765(12)70112-1.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

26

., U. A. Kamalu. "IDENTITY AUTHENTICATION USING VOICE BIOMETRICS TECHNIQUE". International Journal of Research in Engineering and Technology 04, nr 12 (25.12.2015): 130–36. http://dx.doi.org/10.15623/ijret.2015.0412025.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

27

Yang, Hai, Yunfei Xu, Houjun Huang, Ruohua Zhou i Yonghong Yan. "Voice biometrics using linear Gaussian model". IET Biometrics 3, nr 1 (marzec 2014): 9–15. http://dx.doi.org/10.1049/iet-bmt.2013.0027.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

28

Bhirud, Priya, i Nandana Prabhu. "Performance Evaluation of Filters of Discrete Wavelet Transforms for Biometrics". International Journal of Informatics and Communication Technology (IJ-ICT) 3, nr 2 (1.08.2014): 97. http://dx.doi.org/10.11591/ijict.v3i2.pp97-102.

Pełny tekst źródła

Streszczenie:

<p>Biometrics associated with automated methods of identifying a person or verifying the identity of a person based on physiological or behavioral characteristics. Commonly used biometric features are facial features, fingerprints, voice, facial thermo grams, iris, posture/gait, palm print, hand geometry etc. Compared with other biometric characteristics iris is the most stable and hence the most reliable biometric characteristic over the period of a lifetime. This proposed work provides comparative study of various filters of Wavelet Transforms in terms of size and PSNR of images<em>.</em></p>

Style APA, Harvard, Vancouver, ISO itp.

29

Joseph Charles P, Preethi S,. "Survey Analysis on Secured user Authentication through Biometric Recognition". International Journal on Recent and Innovation Trends in Computing and Communication 11, nr 9 (5.11.2023): 2408–16. http://dx.doi.org/10.17762/ijritcc.v11i9.9296.

Pełny tekst źródła

Streszczenie:

Secured user authentication is the process of verifying the user authenticity. Biometric authentication is the human identification system employed to match the biometric characteristics of user for verifying the authenticity. Biometric identifiers are exclusive, making it harder to hack accounts using them. Common types of biometrics comprise the fingerprint scanning verifies authentication based on a user's fingerprints Face recognition and voice recognition are employed in real-time application for improving the security level in different application scenarios. Face recognition is a method of identifying or verifying the individual identity using their face expression. Voice recognition is the ability of machine to receive and interpret the dictation to understand. Many researchers carried out their research on different face and voice recognition methods. But, recognition accuracy was not improved with minimum time consumption by existing biometric recognition method. In this research, different recognition methods are reviewed using biometric recognition method for user authentication. The recognition methods are efficiently on human faces dataset with respect to performance metrics like recognition accuracy, error rate, and recognition time.

Style APA, Harvard, Vancouver, ISO itp.

30

Rahayu, Sri, Rukli Rukli i Andi Quraisy. "ANALISIS BIBLIOMETRIK TERHADAP FACE AND VOICE RECOGNITION". Khazanah Pendidikan 17, nr 2 (28.09.2023): 188. http://dx.doi.org/10.30595/jkp.v17i2.18485.

Pełny tekst źródła

Streszczenie:

Technology in the digital age like today, not only makes it easier for humans to interact remotely, but technology is now also widely used as a form of self-recognition. Automatic self-recognition systems are needed in today's information age. Automatic self-recognition can be done using body parts known as biometrics. Biometrics is a self-recognition technology that uses body parts or human behavior. There are several common biometric methods that are often used for self-identification, one of which is face and voice. Therefore, this research aims to find out the development of research with the theme of phase and voice recognition on artificial neural networks from 2019-2023. The type of research used is qualitative with bibliometric analysis. The research used as a search engine is Publish Or Perish (POP) with data collection done through Google Sholar indexed publications. The number of articles analyzed was limited to 200 data in the form of journals. This was done with the aim of narrowing the search for the field of artificial neuroscience, especially in the phase and voice recognition, but only 120 data were fulfilled. The results showed that the most connected topic was neural network. The results of this study can be utilized by future researchers to explore and develop the topic of phase and voice regocnition.

Style APA, Harvard, Vancouver, ISO itp.

31

Singh, Law Kumar, Munish Khanna i Hitendra Garg. "Multimodal Biometric Based on Fusion of Ridge Features with Minutiae Features and Face Features". International Journal of Information System Modeling and Design 11, nr 1 (styczeń 2020): 37–57. http://dx.doi.org/10.4018/ijismd.2020010103.

Pełny tekst źródła

Streszczenie:

Multimodal biometrics refers to the exploiting combination of two or more biometric modalities in an identification of a system. Fingerprint, face, retina, iris, hand geometry, DNA, and palm print are physiological traits while voice, signature, keystrokes, gait are behavioural traits used for identification by a system. Single biometric features like faces, fingerprints, irises, retinas, etc., deteriorate or change with time, environment, user mode, physiological defects, and circumstance therefore integrating multi features of biometric traits increase robustness of the system. The proposed multimodal biometrics system presents recognition based on face detection and fingerprint physiological traits. This proposed system increases the efficiency, accuracy and decreases execution time of the system as compared to the existing systems. The performance of proposed method is reported in terms of parameters such as False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate (EER) and accuracy is reported at 95.389%.

Style APA, Harvard, Vancouver, ISO itp.

32

Ferrag, Mohamed Amine, Leandros Maglaras i Abdelouahid Derhab. "Authentication and Authorization for Mobile IoT Devices Using Biofeatures: Recent Advances and Future Trends". Security and Communication Networks 2019 (5.05.2019): 1–20. http://dx.doi.org/10.1155/2019/5452870.

Pełny tekst źródła

Streszczenie:

Biofeatures are fast becoming a key tool to authenticate the IoT devices; in this sense, the purpose of this investigation is to summarise the factors that hinder biometrics models’ development and deployment on a large scale, including human physiological (e.g., face, eyes, fingerprints-palm, or electrocardiogram) and behavioral features (e.g., signature, voice, gait, or keystroke). The different machine learning and data mining methods used by authentication and authorization schemes for mobile IoT devices are provided. Threat models and countermeasures used by biometrics-based authentication schemes for mobile IoT devices are also presented. More specifically, we analyze the state of the art of the existing biometric-based authentication schemes for IoT devices. Based on the current taxonomy, we conclude our paper with different types of challenges for future research efforts in biometrics-based authentication schemes for IoT devices.

Style APA, Harvard, Vancouver, ISO itp.

33

Ahmed, Shoaib. "A Novel Approach Towards Biometric Recognition System Using Voice and Signature". Quaid-e-Awam University Research Journal of Engineering, Science & Technology 21, nr 2 (29.12.2023): 46–52. http://dx.doi.org/10.52584/qrj.2102.06.

Pełny tekst źródła

Streszczenie:

Recently, recognition systems have gained importance due to their vital role in security by identifying users while interacting with electronic devices to ensure reliability. The typical authentication systems based on PINs or passwords have revealed various issues of deceitful access. On the contrary, Biometrics can establish an apparent discrepancy between a genuine individual and a fraudulent imitator. Biometrics may be categorized as a Single Model or Multimodal System. Systems of Multimodal bio-metrics are used in Physical Access, Civil ID, Criminal ID, Network/PC Access, Kiosk/ATM, Retail/POS, Surveillance, e-commerce, and telephony. This paper proposes a novel and robust recognition system that uses voice and signatures as inputs to recognize the users. The proposed method uses (Mel Frequency Cepstral Coefficients) MFCC and (Vector Quantization) VQ as characteristic vectors to perform voice analysis, and Vertical Projection Profile (VPP), Horizontal Projection Profile (HPP), and Discrete Cosine Transform (DCT) features to design an offline signature identification system. In the design, a similarity score is obtained. False acceptance and rejection probabilities are measured based on the highest score for each uni-model system. Finally, both methods are merged to get an equal error rate, which is used to evaluate the effectiveness of the proposed approach. The results indicate that when compared with unimodal biometric systems, the proposed multi-model biometric system produces less EER, making the system more robust and reliable.

Style APA, Harvard, Vancouver, ISO itp.

34

Abd Aljabar, Raya W., i Nidaa F. Hassan. "Encryption VoIP based on Generated Biometric Key for RC4 Algorithm". Engineering and Technology Journal 39, nr 1B (25.03.2021): 209–21. http://dx.doi.org/10.30684/etj.v39i1b.1755.

Pełny tekst źródła

Streszczenie:

Voice over Internet Protocol (VoIP) calls are susceptible to interfere at many points by many attackers, thus encryption considered an important part in keeping VoIP. In this paper, Encryption VoIP based on Generated Biometric Key for RC4 Algorithm is proposed to encrypt the voice data before transmitting it over the network. The system uses a stream algorithm based on RC4 encryption with the new method of biometrics based Key generation technique. This system has generated complex keys in offline phase which is formed depend on features extracted using Linear Discernment Analysis (LDA) from face images. The experimental work shows that the proposed system offers secrecy to speech data with voice cipher is unintelligible and the recovered voice has perfect quality with MSR equal to zero and PSNR equal to infinity.

Style APA, Harvard, Vancouver, ISO itp.

35

Wirdiani, Ayu, Steven Ndung'u Machetho, I. Ketut Gede Darma Putra, Made Sudarma, Rukmi Sari Hartati i Henrico Aldy Ferdian. "Improvement Model for Speaker Recognition using MFCC-CNN and Online Triplet Mining". International Journal on Advanced Science, Engineering and Information Technology 14, nr 2 (14.04.2024): 420–27. http://dx.doi.org/10.18517/ijaseit.14.2.19396.

Pełny tekst źródła

Streszczenie:

Various biometric security systems, such as face recognition, fingerprint, voice, hand geometry, and iris, have been developed. Apart from being a communication medium, the human voice is also a form of biometrics that can be used for identification. Voice has unique characteristics that can be used as a differentiator between one person and another. A sound speaker recognition system must be able to pick up the features that characterize a person's voice. This study aims to develop a human speaker recognition system using the Convolutional Neural Network (CNN) method. This research proposes improvements in the fine-tuning layer in CNN architecture to improve the Accuracy. The recognition system combines the CNN method with Mel Frequency Cepstral Coefficients (MFCC) to perform feature extraction on raw audio and K Nearest Neighbor (KNN) to classify the embedding output. In general, this system extracts voice data features using MFCC. The process is continued with feature extraction using CNN with triplet loss to obtain the 128-dimensional embedding output. The classification of the CNN embedding output uses the KNN method. This research was conducted on 50 speakers from the TIMIT dataset, which contained eight utterances for each speaker and 60 speakers from live recording using a smartphone. The accuracy of this speaker recognition system achieves high-performance accuracy. Further research can be developed by combining different biometrics objects, commonly known as multimodal, to improve recognition accuracy further.

Style APA, Harvard, Vancouver, ISO itp.

36

Diac, Madalina Maria, Simona Irina Damian, Bianca Diana Butincu, Anton Knieling i Diana Bulgaru Iliescu. "Ethical Aspects of Biometric Identification". BRAIN. Broad Research in Artificial Intelligence and Neuroscience 14, nr 4 (19.12.2023): 124–39. http://dx.doi.org/10.18662/brain/14.4/496.

Pełny tekst źródła

Streszczenie:

The term biometrics derives from Greek (bio=life and metrics=measure) and implies the measurement of biological signs. Biometrics is the science of recognizing people based on their physical, behavioral, and physiological attributes, such as fingerprint, face scan, iris, retina, and voice. The present paper aims to develop a study on biometric identification. The major objective of the study is to conduct a survey among the Romanian population on the importance and knowledge of biometric identification methods. This objective was achieved by assessing the knowledge held by the general population of Romania regarding biometric indicators and the degree of adaptability and openness of citizens related to the widest possible implementation of biometrics. The study was based on conducting a quantitative analysis using a questionnaire. Due to the high degree of accessibility, the online environment was chosen as a method of application, distribution being made through social networks. A biometric template digitizes the human body, it has been argued that the collection of biometric identifiers not only interferes with the privacy and right to protection of a person's data, but also with the integrity of an individual's body. In conclusion, the creation and storage of a unique biometric template must be seen in relation to the purpose of the operation. The protection of citizens from criminal activities is a primary obligation of the state. However, it must be exercised with due respect for a number of fundamental ethical values and in the light of modern human rights law.

Style APA, Harvard, Vancouver, ISO itp.

37

Czyzewski, Andrzej. "Examining the voice verification system resistance developed for banking to attacks employing the voice cloning". Journal of the Acoustical Society of America 154, nr 4_supplement (1.10.2023): A79. http://dx.doi.org/10.1121/10.0022861.

Pełny tekst źródła

Streszczenie:

The developed system for verifying the speaker identity in banking branches is based on voice biometrics employing DeepSpeaker neural network model. The testing of its resistance to a potential attack using voice cloning also employed neural networks, such as SV2TTS, Tacotron, WaveRNN, and GE2E. Subjective listening tests indicated that people might easily get confused and point out cloned recordings as an original sample. Nearly 50% of respondents pointed to the wrong answer, confusing the synthesized recording with the original one. Subjects in most cases declared that the quality of cloned and original recordings is similar (Good or Fair according to ITU-R BS.1534 recommendation) and, in some cases, even better than the original (graded as Good for synthesized sample, Fair for original one). Meanwhile, nearly all verification attempts with cloned samples failed (98.8% of samples were rejected). It proves that voice biometrics based on deep neural networks can identify cloned samples better than human listeners. Methods and results of testing the resistance of the developed voice biometrics system to voice cloning attacks are discussed in thepaper. This research was funded from the budget of project No.POIR.01.01.01-0092/19 subsidized by the Polish National Centre for Research and Development (NCBR).

Style APA, Harvard, Vancouver, ISO itp.

38

STOICA, Iulia-Teodora. "The Future Risk of Biometric Data Theft in Cybersecurity". International Journal of Information Security and Cybercrime 13, nr 1 (28.06.2024): 49–58. http://dx.doi.org/10.19107/ijisc.2024.01.04.

Pełny tekst źródła

Streszczenie:

The aim of this paper is to analyze the technical and engineering issues surrounding the future risk of biometric data theft in cyber security. Biometric data, such as fingerprints, facial recognition, and voice recognition, are increasingly being used as a means of authentication in various industries. However, the collection, storage, and transmission of biometric data present unique security challenges, as this data is highly personal and cannot be changed if compromised. In this paper, we will examine the vulnerabilities in biometric authentication technologies, the risks associated with the use of biometrics in various industries, and the measures that can be taken to mitigate these risks.

Style APA, Harvard, Vancouver, ISO itp.

39

Moreno, L. C., i P. B. Lopes. "The Voice Biometrics Based on Pitch Replication". International Journal for Innovation Education and Research 6, nr 10 (31.10.2018): 351–58. http://dx.doi.org/10.31686/ijier.vol6.iss10.1201.

Pełny tekst źródła

Streszczenie:

Authentication and security in automated systems have become very much necessary in our days and many techniques have been proposed towards this end. One of these alternatives is biometrics in which human body characteristics are used to authenticate the system user. The objective of this article is to present a method of text independent speaker identification through the replication of pitch characteristics. Pitch is an important speech feature and is used in a variety of applications, including voice biometrics. The proposed method of speaker identification is based on short segments of speech, namely, three seconds for training and three seconds for the speaker determination. From these segments pitch characteristics are extracted and are used in the proposed method of replication for identification of the speaker.

Style APA, Harvard, Vancouver, ISO itp.

40

Vallee, Mickey. "Biometrics, affect, autoaffection and the phenomenological voice". Subjectivity 11, nr 2 (23.04.2018): 161–76. http://dx.doi.org/10.1057/s41286-018-0044-3.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

41

Gold, Steve. "Voice biometrics: real-world issues and solutions". Biometric Technology Today 2010, nr 5 (maj 2010): 6–7. http://dx.doi.org/10.1016/s0969-4765(10)70105-3.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

42

Arunachalamand, MuthuKumar, i Kavipriya Amuthan. "Finger Knuckle Print Recognition using MMDA with Fuzzy Vault". International Arab Journal of Information Technology 17, nr 4 (1.07.2020): 554–61. http://dx.doi.org/10.34028/iajit/17/4/14.

Pełny tekst źródła

Streszczenie:

Currently frequent biometric scientific research such as with biometric applications like face, iris, voice, hand-based biometrics traits like palm print and fingerprint technique are utilized for spotting out the persons. These specific biometrics habits have their own improvement and weakness so that no particular biometrics can adequately opt for all terms like the accuracy and cost of all applications. In recent times, in addition, to distinct with the hand-based biometrics technique, Finger Knuckle Print (FKP) has been appealed to boom the attention among biometric researchers. The image template pattern formation of FKP embraces the report that is suitable for spotting the uniqueness of individuality. This FKP trait observes a person based on the knuckle print and the framework in the outer finger surface. This FKP feature determines the line anatomy and finger structures which are well established and persistent throughout the life of an individual. In this paper, a novel method for personal identification will be introduced, along with that data to be stored in a secure way has also been proposed. The authentication process includes the transformation of features using 2D Log Gabor filter and Eigen value representation of Multi-Manifold Discriminant Analysis (MMDA) of FKP. Finally, these features are grouped using k-means clustering for both identification and verification process. This proposed system is initialized based on the FKP framework without a template based on the fuzzy vault. The key idea of fuzzy vault storing is utilized to safeguard the secret key in the existence of random numbers as chaff pints

Style APA, Harvard, Vancouver, ISO itp.

43

Lutsenko, K., i K. Nikulin. "VOICE SPEAKER IDENTIFICATION AS ONE OF THE CURRENT BIOMETRIC METHODS OF IDENTIFICATION OF A PERSON". Theory and Practice of Forensic Science and Criminalistics 19, nr 1 (2.04.2020): 239–55. http://dx.doi.org/10.32353/khrife.1.2019.18.

Pełny tekst źródła

Streszczenie:

The article deals with the most widespread biometric identification systems of individuals, including voice recognition of the speaker on video and sound recordings. The urgency of the topic of identification of a person is due to the active informatization of modern society and the increase of flows of confidential information. The branches of the use of biometric technologies and their general characteristics are given. Here is an overview of the use of identification groups that characterize the voice. Also in the article the division of voice identification systems into the corresponding classes is given. The main advantages of voice biometrics such as simplicity of system realization are considered; low cost (the lowest among all biometric methods); No need for contact, the voice biometry allows for long-range verification, unlike other biometric technologies. The analysis of existing methods of speech recognition recognition identifying a person by a combination of unique voice characteristics, determining their weak and strong points, on the basis of which the choice of the most appropriate method for solving the problem of text-independent recognition, Namely the model of Gaussian mixtures, was carried out. The prerequisite for the development of speech technologies is a significant increase in computing capabilities, memory capacity with a significant reduction in the size of computer systems. It should also be Noted the development of mathematical methods that make it possible to perform the Necessary processing of an audio signal by isolating informative features from it. It has been established that the development of information technologies, and the set of practical applications, which use voice recognition technologies, make this area relevant for further theoretical and practical research.

Style APA, Harvard, Vancouver, ISO itp.

44

Jawalkar, F. P., A. K. Kamble, M. S. Khanolkar i M. A. Gangarde. "Voice Recognition Based Money Transaction Using Stegnography". International Journal for Research in Applied Science and Engineering Technology 11, nr 5 (31.05.2023): 7115–19. http://dx.doi.org/10.22214/ijraset.2023.53375.

Pełny tekst źródła

Streszczenie:

Abstract: Security has been one of the most crucial challenges in today's environment when insecurity is widespread. Voice biometrics is a developing field in security, particularly for the purpose of authentication. Voice biometric speaker recognition utilizes the distinctive qualities of the human voice, including physiological and behavioural traits. These traits have the ability to identify a person and have distinct and relevant vocal features. This method also makes it possible to verify a user regardless of environment or channel changes. With the use of Machine Learning (ML), software can recognize voice and match it during authentication. Voice recognition is a part of speech recognition. A software system can match a customer's identification to their voice using voice recognition, a feature of AI. In this system, first the user has to register using their voice. After registration the user will log into their account. Then the user will select the person to whom the transaction is to be made and enter the amount to be transferred. Then the transaction will be successful. Here we will secure voice in the database at bank server. In this project, the main objectives are to use voice recognition for login, to use audio steganography for security purposes and to build a web application for the mentioned objectives.

Style APA, Harvard, Vancouver, ISO itp.

45

Contreras , Rodrigo Colnago, Monique Simplicio Viana , Everthon Silva Fonseca , Francisco Lledo dos Santos, Rodrigo Bruno Zanin i Rodrigo Capobianco Guido . "An Experimental Analysis on Multicepstral Projection Representation Strategies for Dysphonia Detection". Sensors 23, nr 11 (30.05.2023): 5196. http://dx.doi.org/10.3390/s23115196.

Pełny tekst źródła

Streszczenie:

Biometrics-based authentication has become the most well-established form of user recognition in systems that demand a certain level of security. For example, the most commonplace social activities stand out, such as access to the work environment or to one’s own bank account. Among all biometrics, voice receives special attention due to factors such as ease of collection, the low cost of reading devices, and the high quantity of literature and software packages available for use. However, these biometrics may have the ability to represent the individual impaired by the phenomenon known as dysphonia, which consists of a change in the sound signal due to some disease that acts on the vocal apparatus. As a consequence, for example, a user with the flu may not be properly authenticated by the recognition system. Therefore, it is important that automatic voice dysphonia detection techniques be developed. In this work, we propose a new framework based on the representation of the voice signal by the multiple projection of cepstral coefficients to promote the detection of dysphonic alterations in the voice through machine learning techniques. Most of the best-known cepstral coefficient extraction techniques in the literature are mapped and analyzed separately and together with measures related to the fundamental frequency of the voice signal, and its representation capacity is evaluated on three classifiers. Finally, the experiments on a subset of the Saarbruecken Voice Database prove the effectiveness of the proposed material in detecting the presence of dysphonia in the voice.

Style APA, Harvard, Vancouver, ISO itp.

46

Sulavko, A. E. "Highly reliable two-factor biometric authentication based on handwritten and voice passwords using flexible neural networks". Computer Optics 44, nr 1 (luty 2020): 82–91. http://dx.doi.org/10.18287/2412-6179-co-567.

Pełny tekst źródła

Streszczenie:

The paper addresses a problem of highly reliable biometric authentication based on converters of secret biometric images into a long key or password, as well as their testing on relatively small samples (thousands of images). Static images are open, therefore with remote authentication they are of a limited trust. A process of calculating the biometric parameters of voice and handwritten passwords is described, a method for automatically generating a flexible hybrid network consisting of various types of neurons is proposed, and an absolutely stable algorithm for network learning using small samples of “Custom” (7-15 examples) is developed. A method of a trained hybrid "biometrics-code" converter based on knowledge extraction is proposed. Low values of FAR (false acceptance rate) are achieved.

Style APA, Harvard, Vancouver, ISO itp.

47

Altuwayjiri, Sarah Mohammed, Ouiem Bchir i Mohamed Maher Ben Ismail. "Generalized Replay Spoofing Countermeasure Based on Combining Local Subclassification Models". Applied Sciences 12, nr 22 (18.11.2022): 11742. http://dx.doi.org/10.3390/app122211742.

Pełny tekst źródła

Streszczenie:

Automatic speaker verification (ASV) systems play a prominent role in the security field due to the usability of voice biometrics compared to alternative biometric authentication modalities. Nevertheless, ASV systems are susceptible to malicious voice spoofing attacks. In response to such threats, countermeasures have been devised to prevent breaches and ensure the safety of user data by categorizing utterances as either genuine or spoofed. In this paper, we propose a new voice spoofing countermeasure that seeks to improve the generalization of supervised learning models. This is accomplished by alleviating the problem of intraclass variance. Specifically, the proposed approach addresses the generalization challenge by splitting the classification problem into a set of local subproblems in order to lessen the supervised learning task. The system outperformed existing state-of-the-art approaches with an EER of 0.097% on the ASVspoof challenge corpora related to replaying spoofing attacks.

Style APA, Harvard, Vancouver, ISO itp.

48

Oseremi Onesi-Ozigagun, Yinka James Ololade, Nsisong Louis Eyo-Udo i Damilola Oluwaseun Ogundipe. "AI-driven biometrics for secure fintech: Pioneering safety and trust". International Journal of Engineering Research Updates 6, nr 2 (30.04.2024): 001–12. http://dx.doi.org/10.53430/ijeru.2024.6.2.0023.

Pełny tekst źródła

Streszczenie:

AI-driven biometrics is revolutionizing the security landscape in the financial technology (FinTech) sector, enhancing safety measures and fostering trust among users. This review explores the role of AI-driven biometrics in securing FinTech operations, highlighting its benefits and implications. AI-driven biometrics refers to the use of artificial intelligence (AI) algorithms to analyze biological data for authentication purposes. This technology has gained significant traction in the FinTech sector due to its ability to provide a higher level of security than traditional authentication methods. By analyzing unique biological traits such as fingerprints, facial features, and voice patterns, AI-driven biometrics can accurately verify the identity of users, making it difficult for unauthorized individuals to gain access to sensitive financial information. One of the key benefits of AI-driven biometrics in FinTech is its ability to enhance security measures. Traditional authentication methods such as passwords and PINs are increasingly vulnerable to hacking and fraud. AI-driven biometrics, on the other hand, offers a higher level of security by using biological traits that are unique to each individual. This makes it significantly more difficult for fraudsters to gain access to sensitive financial information. In addition to enhancing security, AI-driven biometrics also improves the user experience. By replacing traditional authentication methods with biometric authentication, users can access their accounts more quickly and conveniently, without the need to remember complex passwords or PINs. This not only improves the overall user experience but also reduces the risk of user error and account lockouts. Overall, AI-driven biometrics is pioneering safety and trust in the FinTech sector by providing a higher level of security and enhancing the user experience. As this technology continues to evolve, it is likely to play an increasingly important role in securing financial transactions and fostering trust among users.

Style APA, Harvard, Vancouver, ISO itp.

49

Mohammed, Safiia, i Michael Hegarty. "Evaluation of Voice & Ear Biometrics Authentication System". International Journal of Education and Management Engineering 7, nr 4 (8.07.2017): 29–40. http://dx.doi.org/10.5815/ijeme.2017.04.04.

Pełny tekst źródła

Style APA, Harvard, Vancouver, ISO itp.

50

Rajasingh, J. Paul, i D. Sai Yaswanth. "Fingerprint Authentication". International Journal of Engineering and Advanced Technology 10, nr 5 (30.06.2021): 87–89. http://dx.doi.org/10.35940/ijeat.e2651.0610521.

Pełny tekst źródła

Streszczenie:

Biometrics refers to the automatic identification of a living person based on physiological or behavioural characteristics for authentication purpose. Among the existing biometric technologies are the face recognisation, fingerprint recognition, finger-geometry, hand geometry, iris recognition, vein recognition, voice recognition and signature recognition, Biometric method requires the physical presence of the person to be identified. This emphasizes its preference over the traditional method of identifying what you have such as, the use of password, a smartcard etc. Also, it potentially prevents unauthorized admittance to access control systems or fraudulent use of ATMs, Time Attendance Systems, cellular phones, smart cards, desktop PCs, Workstations, vehicles and computer networks. Biometric recognition systems offer greater security and convenience than traditional methods of personal recognition.

Style APA, Harvard, Vancouver, ISO itp.

Artykuły w czasopismach na temat „Voice biometrics”

Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych