Hybrid blowfish cryptography with elliptic curve Diffie-Hellman key exchange protocol for enhancing data security and performance by K. Vignesh Saravanan, G. Sakthi Priya

“…The performance depends on factors such as Recall, Ranking Privacy, Precision, Searching Speed. The proposed algorithm efficiently retrieves the required data maintaining the privacy and identifies the relevant data at high accuracy and optimal speed. …”
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A federated LSTM network for load forecasting using multi-source data with homomorphic encryption by Mengdi Wang, Rui Xin, Mingrui Xia, Zhifeng Zuo, Yinyin Ge, Pengfei Zhang, Hongxing Ye

“…These challenges drive the adoption of federated learning (FL) to address issues related to data silos and privacy. In this paper, a novel framework for short-term load forecasting was proposed using historical data from industries such as power, meteorology, and finance. …”
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Analysis of Service Quality in Smart Running Applications Using Big Data Text Mining Techniques by Jongho Kim, Jinwook Chung

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New blockchain consensus algorithm applied on healthcare industry: Proof of Visit- (POV) by Çetin Şahin, Muhammed Ali Aydin, Ahmet Sertbaş

“…Sharing personal EHR without the citizen’s consent can lead to data privacy issues. In systems where patient data is centrally stored, software changes can cause problems such as loss of patient data. …”
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Predictive Model to Analyse Real and Synthetic Data for Learners' Performance Prediction Using Regression Techniques by SHABNAM ARA S.J, Tanuja R, Manjula S.H

“…Real-world data availability is often hampered by privacy concerns, prompting a shift towards synthetic data generation. …”
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A Novel System for Confidential Medical Data Storage Using Chaskey Encryption and Blockchain Technology by Aymen Mudheher Badr, Lamia Chaari Fourati, Samiha Ayed

“… Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. …”
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Secure healthcare data sharing and attack detection framework using radial basis neural network by Abhishek Kumar, Priya Batta, Pramod Singh Rathore, Sachin Ahuja

“…The proposed authenticate access control mechanism (PA2C) safeguards data integrity as well as the security and dependability of EHR data sharing are improved by the use of smart contracts, encryption, and secure key management. …”
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Face-to-Face Interactions Estimated Using Mobile Phone Data to Support Contact Tracing Operations by Silvino Pedro Cumbane, Gyözö Gidófalvi, Osvaldo Fernando Cossa, Afonso Madivadua Júnior, Nuno Sousa, Frederico Branco

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Respiratory Rate Estimation from Thermal Video Data Using Spatio-Temporal Deep Learning by Mohsen Mozafari, Andrew J. Law, Rafik A. Goubran, James R. Green

“…Thermal videos provide a privacy-preserving yet information-rich data source for remote health monitoring, especially for respiration rate (RR) estimation. …”
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How to use relevant data for maximal benefit with minimal risk: digital health data governance to protect vulnerable populations in low-income and middle-income countries by Nicki Tiffin, Asha George, Amnesty Elizabeth LeFevre

“…Globally, the volume of private and personal digital data has massively increased, accompanied by rapid expansion in the generation and use of digital health data. …”
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Data protection impact assessment system in the mode of risk management by Ying CHENG

“…In the era of big data,the risk management approach has been broadly applied in the field of personal information protection.Data protection impact assessment has become an important system to promote data protection.It takes the provisions of the data protection impact assessment of the European General Data Protection Regulation (GDPR) 2016 as the sample.By using the literature research and empirical analysis method,it analyzes in depth the theoretical background,rise and evolution,meaning and scope of data protection impact assessment to establish a standardized and specific impact assessment system as well as promote personal information protection.Assessment content includes not only privacy risk assessment,but also data security,data quality and non-discrimination.Data protection impact assessment should be set as a mandatory obligation for data processing activities that are likely to result in high risks.The evaluation process shall take the advices from stakeholders to reflect their benefits.The external supervision should be strengthened and the assessment report shall be published properly.…”
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Enhanced Fall Detection Using YOLOv7-W6-Pose for Real-Time Elderly Monitoring by Eugenia Tîrziu, Ana-Mihaela Vasilevschi, Adriana Alexandru, Eleonora Tudora

“…Furthermore, the approach ensures data privacy by processing only skeletal points derived from pose estimation, with no personal data stored. …”
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New Images of the Globalized World Crossed by Artificial Intelligence by Vanina Rodríguez

“…Data privacy and security are also major challenges in the use of AI to generate and select content. …”
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Blockchain-Enabled Federated Learning in Healthcare: Survey and State-of-the-Art by Nasim Nezhadsistani, Naghmeh S. Moayedian, Burkhard Stiller

“…Centralization of health data to train ML models does pose privacy, ownership, and regulatory problems. …”
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What if Facebook goes down? Ethical and legal considerations for the demise of big tech by Carl Öhman, Nikita Aggarwal

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Novel Bounds for Incremental Hessian Estimation With Application to Zeroth-Order Federated Learning by Alessio Maritan, Luca Schenato, Subhrakanti Dey

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Federated Learning for Human Activity Recognition: Overview, Advances, and Challenges by Ons Aouedi, Alessio Sacco, Latif U. Khan, Dinh C. Nguyen, Mohsen Guizani

“…Federated Learning (FL) is a promising paradigm for HAR that enables the collaborative training of machine learning models on decentralized devices while preserving data privacy. It improves not only data privacy but also training efficiency as it utilizes the computing power and data of potentially millions of smart devices for parallel training. …”
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PCRFed: personalized federated learning with contrastive representation for non-independently and identically distributed medical image segmentation by Shengyuan Liu, Ruofan Zhang, Mengjie Fang, Hailin Li, Tianwang Xun, Zipei Wang, Wenting Shang, Jie Tian, Di Dong

“…Abstract Federated learning (FL) has shown great potential in addressing data privacy issues in medical image analysis. However, varying data distributions across different sites can create challenges in aggregating client models and achieving good global model performance. …”
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Blockchain-Assisted Hierarchical Attribute-Based Encryption Scheme for Secure Information Sharing in Industrial Internet of Things by A. Sasikumar, Logesh Ravi, Malathi Devarajan, A. Selvalakshmi, Abdulaziz Turki Almaktoom, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…In addition, we developed a blockchain-integrated data-sharing scheme that makes it possible for users to share data via the use of edge and cloud storage. …”
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Multi-authority attribute hidden for electronic medical record sharing scheme based on blockchain by Lin JIN, Youliang TIAN

“…Currently, there is no data exchanging and sharing between different hospitals, and it is easy to form data islands.At the same time, regional medical data contains a large amount of sensitive information of patients.The public acquisition, sharing and circulation of these data will lead to malicious tampering, theft, abuse and loss of ownership, thereby revealing patient privacy.In addition, the size of medical data is enormous and the data is unstructured, then it is more difficult to prevent and hold accountable some highly targeted malicious attacks, such as malicious attacks on medical data theft, tampering, and extortion.In view of the above problems, a blockchain-based on multi-authority attribute hidden electronic medical record sharing scheme was proposed to achieve fine-grained access to shared electronic medical records while ensuring patient privacy.The Multi-Authorization Attribute Encryption (MA-ABE) algorithm was introduced, which used multi-authority organizations to manage decentralized attributes.It also used hash functions to identify different users, in order to effectively resist collusion attacks between users with different authorizations.Besides, the linear secrets sharing scheme (LSSS) was used to realize partial hiding of attributes, and the attributes were divided into two parts:attribute name and attribute value.In addition, combined with the characteristics of blockchain openness, transparency and tamper-proof, the design of access policy can update the algorithm.Based on the access policy update algorithm, the policy block was added.The new access policy was uploaded to the blockchain to form a policy update traceability chain, which can realize distributed and reliable access control management under the condition of hidden policy.It can also support data privacy protection at the same time, and traceability of user behavior.The theoretical proof and experimental analysis have proved that this scheme protect attribute privacy effectively, while reduces computational overhead.…”
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