Eric Yocam¹, Ahmad Alomari², Amjad Gawanmeh^3,*, Wathiq Mansoor³

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3091-3110, 2023, DOI:10.32604/cmc.2023.032826

Abstract A person’s privacy has become a growing concern, given the nature of an expansive reliance on real-time video activities with video capture, stream, and storage. This paper presents an innovative system design based on a privacy-preserving model. The proposed system design is implemented by employing an enhanced capability that overcomes today’s single parameter-based access control protection mechanism for digital privacy preservation. The enhanced capability combines multiple access control parameters: facial expression, resource, environment, location, and time. The proposed system design demonstrated that a person’s facial expressions combined with a set of access control rules can achieve a person’s privacy-preserving preferences.… More >

Xiaorui Zhang^1,2,3,4,*, Yingying Wang¹, Wei Sun^4,5, Qi Cui⁶, Xindong Wei⁷

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3057-3071, 2023, DOI:10.32604/iasc.2023.033578

Abstract Signature verification, which is a method to distinguish the authenticity of signature images, is a biometric verification technique that can effectively reduce the risk of forged signatures in financial, legal, and other business environments. However, compared with ordinary images, signature images have the following characteristics: First, the strokes are slim, i.e., there is less effective information. Second, the signature changes slightly with the time, place, and mood of the signer, i.e., it has high intraclass differences. These challenges lead to the low accuracy of the existing methods based on convolutional neural networks (CNN). This study proposes an end-to-end multi-path attention… More >

Muhammad Azhar^1,*, Sehat Ullah¹, Khalil Ullah², Habib Shah³, Abdallah Namoun⁴, Khaliq Ur Rahman⁵

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 165-182, 2023, DOI:10.32604/cmc.2023.034605

Abstract Human biometric analysis has gotten much attention due to its widespread use in different research areas, such as security, surveillance, health, human identification, and classification. Human gait is one of the key human traits that can identify and classify humans based on their age, gender, and ethnicity. Different approaches have been proposed for the estimation of human age based on gait so far. However, challenges are there, for which an efficient, low-cost technique or algorithm is needed. In this paper, we propose a three-dimensional real-time gait-based age detection system using a machine learning approach. The proposed system consists of training… More >

Ansam A. Abdulhussien^1,2,*, Mohammad F. Nasrudin¹, Saad M. Darwish³, Zaid A. Alyasseri¹

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 219-242, 2023, DOI:10.32604/cmc.2023.033331

Abstract Signature verification is regarded as the most beneficial behavioral characteristic-based biometric feature in security and fraud protection. It is also a popular biometric authentication technology in forensic and commercial transactions due to its various advantages, including noninvasiveness, user-friendliness, and social and legal acceptability. According to the literature, extensive research has been conducted on signature verification systems in a variety of languages, including English, Hindi, Bangla, and Chinese. However, the Arabic Offline Signature Verification (OSV) system is still a challenging issue that has not been investigated as much by researchers due to the Arabic script being distinguished by changing letter shapes,… More >

Mohammad Yamin¹, Saleh Bajaba², Sarah B. Basahel³, E. Laxmi Lydia^4,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 321-336, 2023, DOI:10.32604/csse.2023.034849

Abstract Deep learning (DL) models have been useful in many computer vision, speech recognition, and natural language processing tasks in recent years. These models seem a natural fit to handle the rising number of biometric recognition problems, from cellphone authentication to airport security systems. DL approaches have recently been utilized to improve the efficiency of various biometric recognition systems. Iris recognition was considered the more reliable and accurate biometric detection method accessible. Iris recognition has been an active research region in the last few decades due to its extensive applications, from security in airports to homeland security border control. This article… More >

Smita Khade¹, Shilpa Gite^1,2,*, Sudeep D. Thepade³, Biswajeet Pradhan^4,5,*, Abdullah Alamri⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 323-345, 2023, DOI:10.32604/cmes.2023.023674

Abstract Contactless verification is possible with iris biometric identification, which helps prevent infections like COVID-19 from spreading. Biometric systems have grown unsteady and dangerous as a result of spoofing assaults employing contact lenses, replayed the video, and print attacks. The work demonstrates an iris liveness detection approach by utilizing fragmental coefficients of Haar transformed Iris images as signatures to prevent spoofing attacks for the very first time in the identification of iris liveness. Seven assorted feature creation ways are studied in the presented solutions, and these created features are explored for the training of eight distinct machine learning classifiers and ensembles.… More > Graphic Abstract

J. Vasavi¹, M. S. Abirami^2,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1349-1363, 2023, DOI:10.32604/iasc.2023.032604

Abstract In recent years, biometric sensors are applicable for identifying important individual information and accessing the control using various identifiers by including the characteristics like a fingerprint, palm print, iris recognition, and so on. However, the precise identification of human features is still physically challenging in humans during their lifetime resulting in a variance in their appearance or features. In response to these challenges, a novel Multimodal Biometric Feature Extraction (MBFE) model is proposed to extract the features from the noisy sensor data using a modified Ranking-based Deep Convolution Neural Network (RDCNN). The proposed MBFE model enables the feature extraction from… More >

S. Aanjanadevi^1,*, S. Aanjankumar², K. R. Ramela³, V. Palanisamy⁴

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2351-2362, 2023, DOI:10.32604/csse.2023.031893

Abstract Due to the enormous usage of the internet for transmission of data over a network, security and authenticity become major risks. Major challenges encountered in biometric system are the misuse of enrolled biometric templates stored in database server. To describe these issues various algorithms are implemented to deliver better protection to biometric traits such as physical (Face, fingerprint, Ear etc.) and behavioural (Gesture, Voice, tying etc.) by means of matching and verification process. In this work, biometric security system with fuzzy extractor and convolutional neural networks using face attribute is proposed which provides different choices for supporting cryptographic processes to… More >

Iman Almomani^1,2, Walid El-Shafai^1,3,*, Aala AlKhayer¹, Albandari Alsumayt⁴, Sumayh S. Aljameel⁵, Khalid Alissa⁶

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3515-3537, 2023, DOI:10.32604/cmc.2023.033765

Abstract Nowadays, there is tremendous growth in biometric authentication and cybersecurity applications. Thus, the efficient way of storing and securing personal biometric patterns is mandatory in most governmental and private sectors. Therefore, designing and implementing robust security algorithms for users’ biometrics is still a hot research area to be investigated. This work presents a powerful biometric security system (BSS) to protect different biometric modalities such as faces, iris, and fingerprints. The proposed BSS model is based on hybridizing auto-encoder (AE) network and a chaos-based ciphering algorithm to cipher the details of the stored biometric patterns and ensures their secrecy. The employed… More >

Lamiaa A. Abou Elazm^1,2, Walid El-Shafai^3,4, Sameh Ibrahim², Mohamed G. Egila¹, H. Shawkey¹, Mohamed K. H. Elsaid², Naglaa F. Soliman⁵, Hussah Nasser AlEisa^6,*, Fathi E. Abd El-Samie³

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 929-955, 2023, DOI:10.32604/iasc.2023.031386

Abstract Biometric security is a growing trend, as it supports the authentication of persons using confidential biometric data. Most of the transmitted data in multimedia systems are susceptible to attacks, which affect the security of these systems. Biometric systems provide sufficient protection and privacy for users. The recently-introduced cancellable biometric recognition systems have not been investigated in the presence of different types of attacks. In addition, they have not been studied on different and large biometric datasets. Another point that deserves consideration is the hardware implementation of cancellable biometric recognition systems. This paper presents a suggested hybrid cancellable biometric recognition system… More >