Article
Computer Science, Theory & Methods
Yuqing Ni, Junfeng Wu, Li Li, Ling Shi
Summary: This paper focuses on dynamic state estimation with a privacy-preserving approach for multiple parties' sensing data. It introduces a paradigm utilizing additively homomorphic encryption to ensure data privacy while collaboratively developing a stable fusion rule. The analysis includes stabilization methods, collaborative gain design, and numerical examples to illustrate the proposed filtering paradigm.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
Article
Physics, Multidisciplinary
Jiang-Shan Liu, Yuan-Cheng Li, Qing-Le Wang, Meng Hu, Zhi-Chao Zhang
Summary: The paper introduces a quantum anonymous voting protocol based on quantum mechanics using high-dimensional single particles, achieving properties of eligibility, privacy, no-reusability, verifiability, and fairness. Analysis shows that the protocol can successfully resist attacks from external eavesdroppers and internal participants, ensuring security under ideal conditions. Designing mature quantum anonymous voting protocols is challenging.
Article
Computer Science, Information Systems
Kranthi Kumar Singamaneni, Ali Nauman, Sapna Juneja, Gaurav Dhiman, Wattana Viriyasitavat, Yasir Hamid, Joseph Henry Anajemba
Summary: Cloud computational service is widely used and provides simple and easy-to-use data management and processing. However, it also presents security challenges. To enhance the security and privacy of users' sensitive data, we propose a novel encryption framework.
Article
Mathematics, Interdisciplinary Applications
Jia Wu, Fangfang Gou, Wangping Xiong, Xian Zhou
Summary: This study proposes a task-sharing strategy that comprehensively considers delay, energy consumption, and terminal reputation value. The simulation results show that this strategy can meet the service requirements of low delay, low power consumption, and high reliability for emerging intelligent applications, effectively optimizing the allocation of computation sharing resources in complex networks.
Article
Computer Science, Information Systems
Ankit Kumar, Turki Aljrees, Sun-Yuan Hsieh, Kamred Udham Singh, Teekam Singh, Linesh Raja, Jitendra Kumar Samriya, Rajesh Kumar Mundotiya
Summary: Cloud storage is a new way for businesses to store data, allowing clients to easily access their data in the cloud. Data security is crucial in cloud computing, and monitoring has become an abstract process to ensure data protection. This paper proposes a secure cloud communication method that addresses data security concerns and enhances trust between data owners and cloud providers.
HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
(2023)
Article
Computer Science, Information Systems
Wenjie Tang, Wenzhong Yang, Xiaodan Tian, Shaoqi Yuan
Summary: With the development of science and technology, the traditional centralized ballot management is no longer capable of meeting the requirements of e-voting transparency and anonymity. Distributed blockchain technology offers a solution with its transparent and tamper-proof features. We propose a blockchain technology-based voting record synchronization model and an anonymous authentication model to achieve user authentication and anonymous voting.
Article
Computer Science, Theory & Methods
Jian Lei, Quanwang Wu, Jin Xu
Summary: This paper investigates the cost and privacy constraints when deploying workflows in a hybrid cloud environment. By designing a three-level data privacy and security model and proposing scheduling heuristics, it is possible to effectively reduce costs and ensure privacy and security.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Software Engineering
Kingsleen Solomon Doss, Somasundaram Kamalakkannan
Summary: This work introduces an optimization-based privacy preservation model by selecting the optimal key matrix. Data sanitization and restoration are carried out in this model. A novel hybrid algorithm called random-based grey dragon algorithm (R-GDA) is used to optimally choose the key matrix. The supremacy of the adopted method is validated over other existing approaches in terms of privacy, utility, and other measures. Privacy preservation in the cloud is achievable in various fields such as education, banking, military, and research community.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Automation & Control Systems
Dongliang Xu, Wei Shi, Wensheng Zhai, Zhihong Tian
Summary: This study proposes a multi-candidate voting model based on blockchain technology, which solves the problems in traditional electronic voting by introducing encryption and anonymity protection algorithms, displaying real-time voting results while satisfying voting security and privacy requirements.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Article
Computer Science, Information Systems
Linwei Sang, Qinran Hu, Yinliang Xu, Zaijun Wu
Summary: This paper proposes a privacy-preserving hybrid cloud framework for TCL-based demand response programs. User private clouds store users' load profiles and elicit temperature flexibility using the proposed stable temperature-related regression model. The aggregation cloud utilizes the slope-priority flexibility aggregation method and the XGBoost-accelerated disaggregation model to analyze the aggregate flexibility and select users in real-time. The hybrid cloud achieves privacy-preserving by separating flexibility eliciting models and aggregation/disaggregation methods into user private clouds and aggregation cloud. Numerical experiments demonstrate the effectiveness of the proposed framework in terms of prediction errors, aggregate flexibility, and solving time reduction.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Chemistry, Multidisciplinary
Vehbi Neziri, Isak Shabani, Ramadan Dervishi, Blerim Rexha
Summary: Anonymity and privacy are crucial for the electoral process, especially in electronic voting systems. This paper proposes a new approach using Blockchain technology to ensure voter anonymity and privacy.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Hardware & Architecture
Wenyan Liu, Junhong Cheng, Xiaoling Wang, Xingjian Lu, Jianwei Yin
Summary: This paper proposes a secure and reliable federated learning algorithm by integrating hybrid differential privacy into federated learning. The algorithm divides users into two categories according to their different privacy needs, and introduces an adaptive gradient clip scheme and an improved composition method to reduce the effects of noise and clip.
JOURNAL OF SYSTEMS ARCHITECTURE
(2022)
Article
Computer Science, Information Systems
Danish Ahamad, Shabi Alam Hameed, Mobin Akhtar
Summary: The rising volume of sensitive and personal data being harvested by data controllers has increased the security essentials in the cloud system. To overcome the challenges in privacy preservation, this paper develops a privacy preservation model in the cloud environment using advancements in artificial intelligent techniques.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Hardware & Architecture
Tehsin Kanwal, Adeel Anjum, Saif U. R. Malik, Abid Khan, Muazzam A. Khan
Summary: This paper investigates the need for a privacy-preserving access control model for healthcare organizations outsourcing EHRs data to a hybrid cloud. The proposed privacy-preserving XACML based access control model effectively invalidates identified security and privacy attacks, verified using High-Level Petri Nets, SMTlib, and Z3 solver. Implementing the model demonstrates its effectiveness in privacy-aware EHRs access and multipurpose usage.
COMPUTER STANDARDS & INTERFACES
(2021)
Article
Quantum Science & Technology
Siwei Huang, Yan Chang, Yusheng Lin, Shibin Zhang
Summary: This paper presents an encryption method for image data that effectively protects the privacy of input data in hybrid quantum-classical convolutional neural networks algorithm. The proposed scheme achieves this by encrypting the user's original image data, calculating the image convolution in the quantum cloud, and obtaining the feature map of the ciphertext image. The decrypted feature map matches the result obtained using the original image as the input, without introducing additional computational complexity.
QUANTUM SCIENCE AND TECHNOLOGY
(2023)
