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 >

Mingshuai Sheng¹, Jingbing Li^1,2,*, Uzair Aslam Bhatti^1,2,3, Jing Liu⁴, Mengxing Huang^1,5, Yen-Wei Chen⁶

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 293-309, 2023, DOI:10.32604/cmc.2023.036438

Abstract Medical images are used as a diagnostic tool, so protecting their confidentiality has long been a topic of study. From this, we propose a Resnet50-DCT-based zero watermarking algorithm for use with medical images. To begin, we use Resnet50, a pre-training network, to draw out the deep features of medical images. Then the deep features are transformed by DCT transform and the perceptual hash function is used to generate the feature vector. The original watermark is chaotic scrambled to get the encrypted watermark, and the watermark information is embedded into the original medical image by XOR operation, and the logical key… More >

Shujuan Tian^1,2,3, Wenjian Ding^1,2,3, Gang Liu⁴, Yuxia Sun⁵, Saiqin Long⁵, Jiang Zhu^1,2,3,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 373-391, 2023, DOI:10.32604/cmc.2023.034770

Abstract In edge computing, a reasonable edge resource bidding mechanism can enable edge providers and users to obtain benefits in a relatively fair fashion. To maximize such benefits, this paper proposes a dynamic multi-attribute resource bidding mechanism (DMRBM). Most of the previous work mainly relies on a third-party agent to exchange information to gain optimal benefits. It is worth noting that when edge providers and users trade with third-party agents which are not entirely reliable and trustworthy, their sensitive information is prone to be leaked. Moreover, the privacy protection of edge providers and users must be considered in the dynamic pricing/transaction… More >

Mingyu Dong, Diqun Yan^*, Rangding Wang

Computer Systems Science and Engineering, Vol.46, No.1, pp. 1-12, 2023, DOI:10.32604/csse.2023.034568

Abstract Speech is easily leaked imperceptibly. When people use their phones, the personal voice assistant is constantly listening and waiting to be activated. Private content in speech may be maliciously extracted through automatic speech recognition (ASR) technology by some applications on phone devices. To guarantee that the recognized speech content is accurate, speech enhancement technology is used to denoise the input speech. Speech enhancement technology has developed rapidly along with deep neural networks (DNNs), but adversarial examples can cause DNNs to fail. Considering that the vulnerability of DNN can be used to protect the privacy in speech. In this work, we… More >

Ze Xu, Sanxing Cao^*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 861-881, 2023, DOI:10.32604/cmes.2023.025159

Abstract Multi-Source data plays an important role in the evolution of media convergence. Its fusion processing enables the further mining of data and utilization of data value and broadens the path for the sharing and dissemination of media data. However, it also faces serious problems in terms of protecting user and data privacy. Many privacy protection methods have been proposed to solve the problem of privacy leakage during the process of data sharing, but they suffer from two flaws: 1) the lack of algorithmic frameworks for specific scenarios such as dynamic datasets in the media domain; 2) the inability to solve… More > Graphic Abstract

Jin Wang¹, Wei Ou¹, Osama Alfarraj², Amr Tolba², Gwang-Jun Kim^3,*, Yongjun Ren⁴

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1805-1819, 2023, DOI:10.32604/csse.2023.029622

Abstract Since transactions in blockchain are based on public ledger verification, this raises security concerns about privacy protection. And it will cause the accumulation of data on the chain and resulting in the low efficiency of block verification, when the whole transaction on the chain is verified. In order to improve the efficiency and privacy protection of block data verification, this paper proposes an efficient block verification mechanism with privacy protection based on zero-knowledge proof (ZKP), which not only protects the privacy of users but also improves the speed of data block verification. There is no need to put the whole… More >

Jieren Cheng¹, Zhenhao Liu^1,*, Yiming Shi¹, Ping Luo^1,2, Victor S. Sheng³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1923-1939, 2023, DOI:10.32604/cmc.2023.032758

Abstract With the increasing number of smart devices and the development of machine learning technology, the value of users’ personal data is becoming more and more important. Based on the premise of protecting users’ personal privacy data, federated learning (FL) uses data stored on edge devices to realize training tasks by contributing training model parameters without revealing the original data. However, since FL can still leak the user's original data by exchanging gradient information. The existing privacy protection strategy will increase the uplink time due to encryption measures. It is a huge challenge in terms of communication. When there are a… More >

Kaifeng Zhang¹, Zhao Qiu^1,*, Gengquan Xie¹, Jiale Lin¹, Tingting Zhang¹, Yingsheng Lian¹, Tao Chen¹, Yunlong He², Yu Yang²

Journal of Cyber Security, Vol.4, No.2, pp. 95-107, 2022, DOI:10.32604/jcs.2022.029451

Abstract Due to its unique security, blockchain technology is widely used in the financial field. Under the background of the rapid development of information technology and the rapid improvement of medical level, it is also a general trend to integrate blockchain technology into the medical field. According to the characteristics of blockchain and the research contents of many scholars on the application of blockchain in the medical field, this paper analyzes and summarizes the problems existing in the current development of blockchain, puts forward corresponding solutions, and looks forward to the further application of blockchain technology in the medical field. More >

B. Murugeshwari^1,*, D. Selvaraj², K. Sudharson³, S. Radhika⁴

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 839-851, 2023, DOI:10.32604/iasc.2023.028548

Abstract Protecting the privacy of data in the multi-cloud is a crucial task. Data mining is a technique that protects the privacy of individual data while mining those data. The most significant task entails obtaining data from numerous remote databases. Mining algorithms can obtain sensitive information once the data is in the data warehouse. Many traditional algorithms/techniques promise to provide safe data transfer, storing, and retrieving over the cloud platform. These strategies are primarily concerned with protecting the privacy of user data. This study aims to present data mining with privacy protection (DMPP) using precise elliptic curve cryptography (PECC), which builds… More >