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 - 06 February 2023

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… More >

Zulqar Nain¹, B. Shahana², Shehzad Ashraf Chaudhry³, P. Viswanathan⁴, M.S. Mekala¹, Sung Won Kim^1,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5705-5721, 2023, DOI:10.32604/cmc.2023.033194 - 28 December 2022

Abstract Fog computing brings computational services near the network edge to meet the latency constraints of cyber-physical System (CPS) applications. Edge devices enable limited computational capacity and energy availability that hamper end user performance. We designed a novel performance measurement index to gauge a device’s resource capacity. This examination addresses the offloading mechanism issues, where the end user (EU) offloads a part of its workload to a nearby edge server (ES). Sometimes, the ES further offloads the workload to another ES or cloud server to achieve reliable performance because of limited resources (such as storage and… 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 - 21 December 2022

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… More >

Yonghui Duan¹, Keqing Zhao^1,*, Yibin Guo², Xiang Wang²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2207-2222, 2023, DOI:10.32604/csse.2023.032297 - 03 November 2022

Abstract A number of risks exist in commercial housing, and it is critical for the government, the real estate industry, and consumers to establish an objective early warning indicator system for commercial housing risks and to conduct research regarding its measurement and early warning. In this paper, we examine the commodity housing market and construct a risk index for the commodity housing market at three levels: market level, the real estate industry and the national economy. Using the Bootstrap aggregating-grey wolf optimizer-support vector machine (Bagging-GWO-SVM) model after synthesizing the risk index by applying the CRITIC objective More >

Walid El-Shafai^1,2, Noha A. El-Hag³, Ahmed Sedik⁴, Ghada Elbanby⁵, Fathi E. Abd El-Samie¹, Naglaa F. Soliman⁶, Hussah Nasser AlEisa^7,*, Mohammed E. Abdel Samea⁸

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2905-2925, 2023, DOI:10.32604/cmc.2023.031936 - 31 October 2022

Abstract Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and therapy. Deep learning provides a high performance for several medical image analysis applications. This paper proposes a deep learning model for the medical image fusion process. This model depends on Convolutional Neural Network (CNN). The basic idea of the proposed model is to extract features from both CT and MR images. Then, an additional process is executed on the extracted features. After that, the fused feature map is reconstructed to obtain the resulting fused image. More >

Salwa M. Serag Eldin^1,*, Ahmed Sedik², Sultan S. Alshamrani³, Ahmed M. Ayoup⁴

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 733-749, 2023, DOI:10.32604/cmc.2023.030789 - 22 September 2022

Abstract In this paper, a novel cancellable biometrics technique called Multi-Biometric-Feature-Hashing (MBFH) is proposed. The MBFH strategy is utilized to actualize a single direction (non-invertibility) biometric shape. MBFH is a typical model security conspire that is distinguished in the utilization of this protection insurance framework in numerous sorts of biometric feature strategies (retina, palm print, Hand Dorsum, fingerprint). A more robust and accurate multilingual biological structure in expressing human loneliness requires a different format to record clients with inseparable comparisons from individual biographical sources. This may raise worries about their utilization and security when these spread More >

S. A. Shaban^*, Hosnia M. M. Ahmed, D. L. Elsheweikh

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3295-3315, 2023, DOI:10.32604/iasc.2023.030237 - 17 August 2022

Abstract With the rapid spread of the coronavirus epidemic all over the world, educational and other institutions are heading towards digitization. In the era of digitization, identifying educational e-platform users using ear and iris based multimodal biometric systems constitutes an urgent and interesting research topic to preserve enterprise security, particularly with wearing a face mask as a precaution against the new coronavirus epidemic. This study proposes a multimodal system based on ear and iris biometrics at the feature fusion level to identify students in electronic examinations (E-exams) during the COVID-19 pandemic. The proposed system comprises four… More >

Walid El-Shafai^1,2, Marwa A. Elsayed¹, Mohsen A. Rashwan³, Moawad I. Dessouky¹, Adel S. El-Fishawy¹, Naglaa F. Soliman⁴, Amel A. Alhussan^5,*, Fathi E. Abd El-Samie¹

Computer Systems Science and Engineering, Vol.45, No.1, pp. 563-578, 2023, DOI:10.32604/csse.2023.024375 - 16 August 2022

Abstract Most current security and authentication systems are based on personal biometrics. The security problem is a major issue in the field of biometric systems. This is due to the use in databases of the original biometrics. Then biometrics will forever be lost if these databases are attacked. Protecting privacy is the most important goal of cancelable biometrics. In order to protect privacy, therefore, cancelable biometrics should be non-invertible in such a way that no information can be inverted from the cancelable biometric templates stored in personal identification/verification databases. One methodology to achieve non-invertibility is the More >

Mayada Tarek^1,2,*

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2049-2063, 2023, DOI:10.32604/csse.2023.027139 - 01 August 2022

Abstract Cancellable biometrics is the solution for the trade-off between two concepts: Biometrics for Security and Security for Biometrics. The cancelable template is stored in the authentication system’s database rather than the original biometric data. In case of the database is compromised, it is easy for the template to be canceled and regenerated from the same biometric data. Recoverability of the cancelable template comes from the diversity of the cancelable transformation parameters (cancelable key). Therefore, the cancelable key must be secret to be used in the system authentication process as a second authentication factor in conjunction… More >

K. Meenakshi^1,*, G. Maragatham²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 627-643, 2023, DOI:10.32604/iasc.2023.026961 - 06 June 2022

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… More >