Ali Batouche¹, Souham Meshoul^2,*, Hadil Shaiba³, Mohamed Batouche^2,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1727-1752, 2025, DOI:10.32604/cmc.2025.063227 - 16 April 2025

Abstract The field of biometric identification has seen significant advancements over the years, with research focusing on enhancing the accuracy and security of these systems. One of the key developments is the integration of deep learning techniques in biometric systems. However, despite these advancements, certain challenges persist. One of the most significant challenges is scalability over growing complexity. Traditional methods either require maintaining and securing a growing database, introducing serious security challenges, or relying on retraining the entire model when new data is introduced—a process that can be computationally expensive and complex. This challenge underscores the… 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 >

Naglaa F. Soliman^1,2, Abeer D. Algarni^1,*, Walid El-Shafai³, Fathi E. Abd El-Samie^1,3, Ghada M. El Banby⁴

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1571-1595, 2021, DOI:10.32604/cmc.2021.016980 - 21 July 2021

Abstract Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things (IoT) networks. The objective of using cancelable biometrics is to save the original ones from hacking attempts. A generalized algorithm to generate cancelable templates that is applicable on both single and multiple biometrics is proposed in this paper to be considered for cloud and IoT applications. The original biometric is blurred with two co-prime operators. Hence, it can be recovered as the Greatest Common Divisor (GCD) between its two blurred versions. Minimal changes… More >