Xiaoying Qiu^1,*, Xiaoyu Ma¹, Guangxu Zhao¹, Jinwei Yu², Wenbao Jiang¹, Zhaozhong Guo¹, Maozhi Xu³

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2025-2040, 2025, DOI:10.32604/cmc.2025.061869 - 16 April 2025

Abstract Physical layer authentication (PLA) in the context of the Internet of Things (IoT) has gained significant attention. Compared with traditional encryption and blockchain technologies, PLA provides a more computationally efficient alternative to exploiting the properties of the wireless medium itself. Some existing PLA solutions rely on static mechanisms, which are insufficient to address the authentication challenges in fifth generation (5G) and beyond wireless networks. Additionally, with the massive increase in mobile device access, the communication security of the IoT is vulnerable to spoofing attacks. To overcome the above challenges, this paper proposes a lightweight deep More >

Wei Liu¹, Sen Liu^2,3,*, Yinchao He², Jiaojiao Wang¹, Yu Gu¹

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4863-4880, 2025, DOI:10.32604/cmc.2025.059295 - 06 March 2025

Abstract To address the issues of slow diagnostic speed, low accuracy, and poor generalization performance in traditional rolling bearing fault diagnosis methods, we propose a rolling bearing fault diagnosis method based on Markov Transition Field (MTF) image encoding combined with a lightweight convolutional neural network that integrates a Convolutional Block Attention Module (CBAM-LCNN). Specifically, we first use the Markov Transition Field to convert the original one-dimensional vibration signals of rolling bearings into two-dimensional images. Then, we construct a lightweight convolutional neural network incorporating the convolutional attention module (CBAM-LCNN). Finally, the two-dimensional images obtained from MTF mapping… More >

Jie Chen¹, Chengsheng Yuan^1,2,*, Chen Cui², Zhihua Xia¹, Xingming Sun^1,3, Thangarajah Akilan⁴

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 719-733, 2022, DOI:10.32604/cmc.2022.027984 - 18 May 2022

Abstract Fingerprint identification systems have been widely deployed in many occasions of our daily life. However, together with many advantages, they are still vulnerable to the presentation attack (PA) by some counterfeit fingerprints. To address challenges from PA, fingerprint liveness detection (FLD) technology has been proposed and gradually attracted people's attention. The vast majority of the FLD methods directly employ convolutional neural network (CNN), and rarely pay attention to the problem of over-parameterization and over-fitting of models, resulting in large calculation force of model deployment and poor model generalization. Aiming at filling this gap, this paper… More >

Yang Wang¹, Ying Tian^1,*, Ou Tian²

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2203-2216, 2021, DOI:10.32604/cmc.2021.018709 - 21 July 2021

Abstract As the use of facial attributes continues to expand, research into facial age estimation is also developing. Because face images are easily affected by factors including illumination and occlusion, the age estimation of faces is a challenging process. This paper proposes a face age estimation algorithm based on lightweight convolutional neural network in view of the complexity of the environment and the limitations of device computing ability. Improving face age estimation based on Soft Stagewise Regression Network (SSR-Net) and facial images, this paper employs the Center Symmetric Local Binary Pattern (CSLBP) method to obtain the More >