K. Meenakshi^1,*, G. Maragatham²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 627-643, 2023, DOI:10.32604/iasc.2023.026961

Abstract Deep Learning is one of the most popular computer science techniques, with applications in natural language processing, image processing, pattern identification, and various other fields. Despite the success of these deep learning algorithms in multiple scenarios, such as spam detection, malware detection, object detection and tracking, face recognition, and automatic driving, these algorithms and their associated training data are rather vulnerable to numerous security threats. These threats ultimately result in significant performance degradation. Moreover, the supervised based learning models are affected by manipulated data known as adversarial examples, which are images with a particular level of noise that is invisible… More >

Hosam El- El-Sofany^1,2,*

Computer Systems Science and Engineering, Vol.43, No.2, pp. 573-589, 2022, DOI:10.32604/csse.2022.024302

Abstract Most user authentication mechanisms of cloud systems depend on the credentials approach in which a user submits his/her identity through a username and password. Unfortunately, this approach has many security problems because personal data can be stolen or recognized by hackers. This paper aims to present a cloud-based biometric authentication model (CBioAM) for improving and securing cloud services. The research study presents the verification and identification processes of the proposed cloud-based biometric authentication system (CBioAS), where the biometric samples of users are saved in database servers and the authentication process is implemented without loss of the users’ information. The paper… More >

Abdullah Saad AL-Malaise AL-Ghamdi¹, Mahmoud Ragab^2,3,4,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3131-3144, 2022, DOI:10.32604/cmc.2022.026457

Abstract Education 4.0 is being authorized more and more by the design of artificial intelligence (AI) techniques. Higher education institutions (HEI) have started to utilize Internet technologies to improve the quality of the service and boost knowledge. Due to the unavailability of information technology (IT) infrastructures, HEI is vulnerable to cyberattacks. Biometric authentication can be used to authenticate a person based on biological features such as face, fingerprint, iris, and so on. This study designs a novel search and rescue optimization with deep learning based learning authentication technique for cybersecurity in higher education institutions, named SRODL-LAC technique. The proposed SRODL-LAC technique… More >

Amjad Rehman¹, Majid Harouni^2,*, Maedeh Omidiravesh³, Suliman Mohamed Fati¹, Saeed Ali Bahaj⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3369-3383, 2022, DOI:10.32604/cmc.2022.016410

Abstract Biometric-based authentication systems have attracted more attention than traditional authentication techniques such as passwords in the last two decades. Multiple biometrics such as fingerprint, palm, iris, palm vein and finger vein and other biometrics have been introduced. One of the challenges in biometrics is physical injury. Biometric of finger vein is of the biometrics least exposed to physical damage. Numerous methods have been proposed for authentication with the help of this biometric that suffer from weaknesses such as high computational complexity and low identification rate. This paper presents a novel method of scattering wavelet-based identity identification. Scattering wavelet extracts image… More >

Safaa El-Gazar¹, Walid El-Shafai^2,3,*, Ghada El-Banby⁴, Hesham F. A. Hamed¹, Gerges M. Salama¹, Mohammed Abd-Elnaby⁵, Fathi E. Abd El-Samie^2,6

Computer Systems Science and Engineering, Vol.43, No.1, pp. 87-102, 2022, DOI:10.32604/csse.2022.022722

Abstract Biometric authentication is a rapidly growing trend that is gaining increasing attention in the last decades. It achieves safe access to systems using biometrics instead of the traditional passwords. The utilization of a biometric in its original format makes it usable only once. Therefore, a cancelable biometric template should be used, so that it can be replaced when it is attacked. Cancelable biometrics aims to enhance the security and privacy of biometric authentication. Digital encryption is an efficient technique to be used in order to generate cancelable biometric templates. In this paper, a highly-secure encryption algorithm is proposed to ensure… More >

K. Babu^1,*, C. Kumar², C. Kannaiyaraju³

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 317-329, 2022, DOI:10.32604/iasc.2022.023756

Abstract Facial expression for different emotional feelings makes it interesting for researchers to develop recognition techniques. Facial expression is the outcome of emotions they feel, behavioral acts, and the physiological condition of one’s mind. In the world of computer visions and algorithms, precise facial recognition is tough. In predicting the expression of a face, machine learning/artificial intelligence plays a significant role. The deep learning techniques are widely used in more challenging real-world problems which are highly encouraged in facial emotional analysis. In this article, we use three phases for facial expression recognition techniques. The principal component analysis-based dimensionality reduction techniques are… More >

Shumukh M. Aljuaid^*, Arshiya S. Ansari

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1009-1025, 2022, DOI:10.32604/csse.2022.020785

Abstract This paper presents a novel method of a secured card-less Automated Teller Machine (ATM) authentication based on the three bio-metrics measures. It would help in the identification and authorization of individuals and would provide robust security enhancement. Moreover, it would assist in providing identification in ways that cannot be impersonated. To the best of our knowledge, this method of Biometric_ fusion way is the first ATM security algorithm that utilizes a fusion of three biometric features of an individual such as Fingerprint, Face, and Retina simultaneously for recognition and authentication. These biometric images have been collected as input data for… More >

Najlaa Hindi Alsaedi^*, Emad Sami Jaha

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1283-1311, 2022, DOI:10.32604/cmc.2022.021608

Abstract Biometric recognition refers to the process of recognizing a person’s identity using physiological or behavioral modalities, such as face, voice, fingerprint, gait, etc. Such biometric modalities are mostly used in recognition tasks separately as in unimodal systems, or jointly with two or more as in multimodal systems. However, multimodal systems can usually enhance the recognition performance over unimodal systems by integrating the biometric data of multiple modalities at different fusion levels. Despite this enhancement, in real-life applications some factors degrade multimodal systems’ performance, such as occlusion, face poses, and noise in voice data. In this paper, we propose two algorithms… More >

Najlaa Hindi Alsaedi^*, Emad Sami Jaha

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 407-427, 2022, DOI:10.32604/iasc.2022.019538

Abstract Accurate recognition of person identity is a critical task in civil society for various application and different needs. There are different well-established biometric modalities that can be used for recognition purposes such as face, voice, fingerprint, iris, etc. Recently, face images have been widely used for person recognition, since the human face is the most natural and user-friendly recognition method. However, in real-life applications, some factors may degrade the recognition performance, such as partial face occlusion, poses, illumination conditions, facial expressions, etc. In this paper, we propose two dynamic feature subset selection (DFSS) methods to achieve better recognition for occluded… More >

Amr Hefny¹, Aboul Ella Hassanien², Sameh H. Basha^1,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2367-2386, 2021, DOI:10.32604/cmc.2021.018017

Abstract Identity verification using authenticity evaluation of handwritten signatures is an important issue. There have been several approaches for the verification of signatures using dynamics of the signing process. Most of these approaches extract only global characteristics. With the aim of capturing both dynamic global and local features, this paper introduces a novel model for verifying handwritten dynamic signatures using neutrosophic rule-based verification system (NRVS) and Genetic NRVS (GNRVS) models. The neutrosophic Logic is structured to reflect multiple types of knowledge and relations among all features using three values: truth, indeterminacy, and falsity. These three values are determined by neutrosophic membership… More >