Sur Singh Rawat^1,*, Youseef Alotaibi², Nitima Malsa¹, Vimal Gupta¹

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1797-1815, 2023, DOI:10.32604/cmc.2023.039381 - 30 August 2023

Abstract Unmanned aerial vehicles (UAVs), or drones, have revolutionized a wide range of industries, including monitoring, agriculture, surveillance, and supply chain. However, their widespread use also poses significant challenges, such as public safety, privacy, and cybersecurity. Cyberattacks, targeting UAVs have become more frequent, which highlights the need for robust security solutions. Blockchain technology, the foundation of cryptocurrencies has the potential to address these challenges. This study suggests a platform that utilizes blockchain technology to manage drone operations securely and confidentially. By incorporating blockchain technology, the proposed method aims to increase the security and privacy of drone… 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 - 08 June 2023

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… More >

Zaid Abdulsalam Ibrahim^1,*, Muhammad Ilyas²

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 939-956, 2023, DOI:10.32604/cmc.2023.035798 - 08 June 2023

Abstract Most research works nowadays deal with real-time Internet of Things (IoT) data. However, with exponential data volume increases, organizations need help storing such humongous amounts of IoT data in cloud storage systems. Moreover, such systems create security issues while efficiently using IoT and Cloud Computing technologies. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has the potential to make IoT data more secure and reliable in various cloud storage services. Cloud-assisted IoTs suffer from two privacy issues: access policies (public) and super polynomial decryption times (attributed mainly to complex access structures). We have developed a CP-ABE scheme in alignment… 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 - 23 April 2023

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… 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 - 23 April 2023

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.… More >

Ping Zhang¹, Haoran Zhu¹, Wenjun Li², Osama Alfarraj³, Amr Tolba³, Gwang-jun Kim^4,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3589-3605, 2023, DOI:10.32604/cmc.2023.032097 - 31 March 2023

Abstract Many Internet of things application scenarios have the characteristics of limited hardware resources and limited energy supply, which are not suitable for traditional security technology. The security technology based on the physical mechanism has attracted extensive attention. How to improve the key generation rate has always been one of the urgent problems to be solved in the security technology based on the physical mechanism. In this paper, superlattice technology is introduced to the security field of Internet of things, and a high-speed symmetric key generation scheme based on superlattice for Internet of things is proposed. More >

Mao Yuxin, Wang Honglin^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 863-878, 2023, DOI:10.32604/cmc.2023.034879 - 06 February 2023

Abstract In the financial sector, data are highly confidential and sensitive, and ensuring data privacy is critical. Sample fusion is the basis of horizontal federation learning, but it is suitable only for scenarios where customers have the same format but different targets, namely for scenarios with strong feature overlapping and weak user overlapping. To solve this limitation, this paper proposes a federated learning-based model with local data sharing and differential privacy. The indexing mechanism of differential privacy is used to obtain different degrees of privacy budgets, which are applied to the gradient according to the contribution… 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 - 05 January 2023

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;… More > Graphic Abstract

Yinggang Sun¹, Hongguo Zhang¹, Chao Ma^1,*, Hai Huang¹, Dongyang Zhan^2,3, Jiaxing Qu⁴

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4043-4058, 2023, DOI:10.32604/cmc.2023.031684 - 31 October 2022

Abstract The problem of data island hinders the application of big data in artificial intelligence model training, so researchers propose a federated learning framework. It enables model training without having to centralize all data in a central storage point. In the current horizontal federated learning scheme, each participant gets the final jointly trained model. No solution is proposed for scenarios where participants only provide training data in exchange for benefits, but do not care about the final jointly trained model. Therefore, this paper proposes a new boosted tree algorithm, called RPBT (the originator Rights Protected federated… More >

B. Murugeshwari^1,*, S. Rajalakshmi¹, K. Sudharson²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2293-2307, 2023, DOI:10.32604/csse.2023.029074 - 01 August 2022

Abstract Imagine numerous clients, each with personal data; individual inputs are severely corrupt, and a server only concerns the collective, statistically essential facets of this data. In several data mining methods, privacy has become highly critical. As a result, various privacy-preserving data analysis technologies have emerged. Hence, we use the randomization process to reconstruct composite data attributes accurately. Also, we use privacy measures to estimate how much deception is required to guarantee privacy. There are several viable privacy protections; however, determining which one is the best is still a work in progress. This paper discusses the… More >