Faguo Wu^1,2,3,4,*, Bo Zhou², Jie Jiang⁵, Tianyu Lei¹, Jiale Song¹

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 957-973, 2023, DOI:10.32604/cmc.2023.038771

Abstract With the rapid increase in demand for data trustworthiness and data security, distributed data storage technology represented by blockchain has received unprecedented attention. These technologies have been suggested for various uses because of their remarkable ability to offer decentralization, high autonomy, full process traceability, and tamper resistance. Blockchain enables the exchange of information and value in an untrusted environment. There has been a significant increase in attention to the confidentiality and privacy preservation of blockchain technology. Ensuring data privacy is a critical concern in cryptography, and one of the most important protocols used to achieve this is the secret-sharing method.… More >

Junqi Guo^1,2, Qingyun Xiong^1,*, Minghui Yang¹, Ziyun Zhao¹

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 827-848, 2023, DOI:10.32604/cmc.2023.036450

Abstract Nowadays, smart wearable devices are used widely in the Social Internet of Things (IoT), which record human physiological data in real time. To protect the data privacy of smart devices, researchers pay more attention to federated learning. Although the data leakage problem is somewhat solved, a new challenge has emerged. Asynchronous federated learning shortens the convergence time, while it has time delay and data heterogeneity problems. Both of the two problems harm the accuracy. To overcome these issues, we propose an asynchronous federated learning scheme based on double compensation to solve the problem of time delay and data heterogeneity problems.… More >

C. Eira Nunes, B. Mouton, S. Van Petegem

Psycho-Oncologie, Vol.16, No.4, pp. 351-358, 2022, DOI:10.3166/pson-2022-0216

Abstract Cet article, bien que non exhaustif, présente un état actuel des connaissances empiriques et théoriques sur la surprotection parentale dans des familles où l’enfant est atteint d’un cancer. Nous abordons les caractéristiques de cette surprotection ainsi que la question de sa fonction adaptative et ses effets potentiellement délétères sur l’enfant dans ce contexte spécifique. Cette revue identifie également certains facteurs familiaux et sociétaux qui peuvent promouvoir la surprotection chez les mères et les pères, soulignant l’importance du contexte familial et sociétal dans l’étude des pratiques parentales en oncologie pédiatrique. More >

LUOJUN ZHENG, LUAN WENG, DIWEN SHOU^*

BIOCELL, Vol.47, No.6, pp. 1345-1352, 2023, DOI:10.32604/biocell.2023.028866

Abstract Background: Ischemic stroke is characterized by permanent or transient obstruction of blood flow, leading to a growing risk factor and health burden. Tianmagouteng yin (TMG) is commonly used in Chinese medicine to treat cerebral ischemia. The aim of this study was to investigate the neuroprotective effects of TMG against ischemic stroke. Methods: Either permanent middle cerebral artery occlusion (pMCAO) or sham operation was performed on anesthetized Wistar male rats (n = 36). Results: Results demonstrated that TMG administration reduced the infarction volume and mitigated the neurobehavioral deficits. Hematoxylin and eosin (HE) staining and Prussian blue staining revealed that TMG attenuated… More >

Jiansheng Zhang¹, Yang Xin^1,*, Yuyan Wang², Xiaohui Lei², Yixian Yang¹

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6185-6199, 2023, DOI:10.32604/cmc.2023.038029

Abstract The car-hailing platform based on Internet of Vehicles (IoV) technology greatly facilitates passengers’ daily car-hailing, enabling drivers to obtain orders more efficiently and obtain more significant benefits. However, to match the driver closest to the passenger, it is often necessary to process the location information of the passenger and driver, which poses a considerable threat to privacy disclosure to the passenger and driver. Targeting these issues, in this paper, by combining blockchain and Paillier homomorphic encryption algorithm, we design a secure blockchain-enabled IoV scheme with privacy protection for online car-hailing. In this scheme, firstly, we propose an encryption scheme based… More >

You Lu^1,2,#,*, Linqian Cui^1,2,#,*, Yunzhe Wang^1,2, Jiacheng Sun^1,2, Lanhui Liu³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 717-732, 2023, DOI:10.32604/cmes.2023.027032

Abstract Most studies have conducted experiments on predicting energy consumption by integrating data for model training. However, the process of centralizing data can cause problems of data leakage. Meanwhile, many laws and regulations on data security and privacy have been enacted, making it difficult to centralize data, which can lead to a data silo problem. Thus, to train the model while maintaining user privacy, we adopt a federated learning framework. However, in all classical federated learning frameworks secure aggregation, the Federated Averaging (FedAvg) method is used to directly weight the model parameters on average, which may have an adverse effect on… More >

Lemei Da¹, Hai Liang^1,*, Yong Ding^1,2, Yujue Wang¹, Changsong Yang¹, Huiyong Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 879-902, 2023, DOI:10.32604/cmes.2023.026309

Abstract The unmanned aerial vehicle (UAV) self-organizing network is composed of multiple UAVs with autonomous capabilities according to a certain structure and scale, which can quickly and accurately complete complex tasks such as path planning, situational awareness, and information transmission. Due to the openness of the network, the UAV cluster is more vulnerable to passive eavesdropping, active interference, and other attacks, which makes the system face serious security threats. This paper proposes a Blockchain-Based Data Acquisition (BDA) scheme with privacy protection to address the data privacy and identity authentication problems in the UAV-assisted data acquisition scenario. Each UAV cluster has an… More >

Ling Zhang^1,*, Lina Nie¹, Leyan Yu²

Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 69-78, 2022, DOI:10.32604/jihpp.2022.039284

Abstract Deep learning is widely used in artificial intelligence fields such as computer vision, natural language recognition, and intelligent robots. With the development of deep learning, people’s expectations for this technology are increasing daily. Enterprises and individuals usually need a lot of computing power to support the practical work of deep learning technology. Many cloud service providers provide and deploy cloud computing environments. However, there are severe risks of privacy leakage when transferring data to cloud service providers and using data for model training, which makes users unable to use deep learning technology in cloud computing environments confidently. This paper mainly… More >

Minmin Xiao¹, Moxiang Cheng¹, Shuangquan Xie¹, Xiushuang Wang¹, Xingming Hao², Li Zhuang^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.6, pp. 1841-1857, 2023, DOI:10.32604/phyton.2023.027369

Abstract To clarify the characteristics of photoinhibition and the primary defense mechanisms of ephemeral plant leaves against photodestruction under high temperature stress, inhibitors and the technology to determine chlorophyll fluorescence were used to explore the protective effects of D1 protein turnover and the lutein cycle in the high temperature stress of the leaves of three ephemeral plants. The results showed that the maximum light conversion efficiency (Fv/Fm) of the ephemeral plant leaves decreased, and the initial fluorescence (Fo) increased under 35°C ± 1°C heat stress for 1–4 h or on sunny days in the summer. Both Fv/Fm and Fo could be… More >

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 >