Convolutional neural network model over encrypted data based on functional encryption by Chen WANG, Jiarun LI, Jian XU

“…Currently, homomorphic encryption, secure multi-party computation, and other encryption schemes are used to protect the privacy of sensitive data in outsourced convolutional neural network (CNN) models.However, the computational and communication overhead caused by the above schemes would reduce system efficiency.Based on the low cost of functional encryption, a new convolutional neural network model over encrypted data was constructed using functional encryption.Firstly, two algorithms based on functional encryption were designed, including inner product functional encryption and basic operation functional encryption algorithms to implement basic operations such as inner product, multiplication, and subtraction over encrypted data, reducing computational and communication costs.Secondly, a secure convolutional computation protocol and a secure loss optimization protocol were designed for each of these basic operations, which achieved ciphertext forward propagation in the convolutional layer and ciphertext backward propagation in the output layer.Finally, a secure training and classification method for the model was provided by the above secure protocols in a module-composable way, which could simultaneously protect the confidentiality of user data as well as data labels.Theoretical analysis and experimental results indicate that the proposed model can achieve CNN training and classification over encrypted data while ensuring accuracy and security.…”
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Approach to keyword search over encrypted data in cloud by Peng ZHANG, Yan LI, Hai-lun LIN, Rong YANG, Qing-yun LIU

“…With the advent of cloud computing,large-scale data are being increasingly outsourced to the cloud.For the protection of data privacy,sensitive data has to be encrypted before outsourcing,which makes effective data utilization a very challenging task.Although traditional searchable encryption approaches allow users to search over encrypted data through keywords,they don’t capture any relevance of data files,so users have to spend much time on post-processing every retrieved file in order to find ones most matching their interest.Moreover,retrieving all files containing the queried keyword further incurs unnecessary network traffic,which is not accord with pay-as-you-use cloud paradigm.An approach to ranked keyword search over encrypted data in cloud is proposed.Ranked search greatly mitigate the user’s effort by returning the matching files in a ranked order,and also protects the data privacy by order-preserving encryption.Extensive experimental results demonstrate the efficiency.…”
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Fused federated learning framework for secure and decentralized patient monitoring in healthcare 5.0 using IoMT by Bassam Almogadwy, Abdulrahman Alqarafi

“…Abstract Federated Learning (FL) enables artificial intelligence frameworks to train on private information without compromising privacy, which is especially useful in the medical and healthcare industries where the knowledge or data at hand is never enough. …”
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How good is your synthetic data? SynthRO, a dashboard to evaluate and benchmark synthetic tabular data by Gabriele Santangelo, Giovanna Nicora, Riccardo Bellazzi, Arianna Dagliati

“…Conclusions Synthetic data mitigate concerns about privacy and data accessibility, yet lacks standardized evaluation metrics. …”
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Multimodal Video Analysis for Crowd Anomaly Detection Using Open Access Tourism Cameras by Alejandro Dionis-Ros, Joan Vila-Francés, Rafael Magdalena-Benedito, Fernando Mateo, Antonio J. Serrano-López

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Collection of location data in criminal proceedings – European (the EU and Strasbourg) standards by Dominika Czerniak

“…This article deals with the problem of collecting, retaining and processing location data for use in criminal proceedings. The collection of location data is an interference with the right to privacy (the Article 8 of the ECHR, the Article 7 of the Charter). …”
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Secure and trusted sharing mechanism of private data for Internet of Things by Mengyuan Li, Shaoyong Guo, Wenjing Li, Ao Xiong, Xiaoming Zhou, Jun Qi, Feng Qi, Dong Wang, Da Li

“…This practice creates the risk of privacy breaches on IoT data sharing platforms, including issues such as data tampering and data breaches. …”
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The tension of usable safety, security and privacy by Kaufhold Marc-André, Mentler Tilo, Nestler Simon, Reuter Christian

“…In this special issue, we investigate the use of computer-based solutions in areas and situations of direct relevance to people’s lives and well-being (Usable Safety), as well as contributions to user-oriented resilience concepts of sociotechnical systems concerning potential attacks (Usable Security) and data protection mechanisms (Usable Privacy).…”
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Survey on privacy protection indoor positioning by Zhiheng WANG, Yanyan XU

“…Smartphones are usually provided with indoor positioning services by third-party positioning service providers, in which the unique privacy leakage risk has become a major factor limiting its development.How to protect the privacy of users and data in the positioning process has become an important issue to be solved.The research progress of indoor positioning privacy protection in recent years was reviewed.The commonly used indoor positioning technologies were introduced, different implementation architectures of indoor positioning systems and their threat models, privacy protection requirements were discussed, security technologies applied to indoor positioning privacy protection were summarized, indoor positioning privacy protection schemes for different architectures were classified and introduced, and the performance of different schemes and their advantages and disadvantages were comprehensively compared and analyzed, and finally future research trends were summarized and looked forward to.…”
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GraphFedAI framework for DDoS attack detection in IoT systems using federated learning and graph based artificial intelligence by Mohd Anjum, Ashit Kumar Dutta, Ali Elrashidi, Sana Shahab, Asma Aldrees, Zaffar Ahmed Shaikh, Abeer Aljohani

“…Federated learning is incorporated to maintain data privacy by training models locally on each device without sharing raw data. …”
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Examining privacy concerns and conversations before, during, and after the onset of the COVID-19 pandemic: an analysis of r/privacy by Erica Shusas, Shruti Sannon, Katie Teitelbaum, Patrick Skeba, Eric P. S. Baumer, Andrea Forte

“…The COVID-19 pandemic brought about new and far-ranging uses of technology that have engendered numerous privacy concerns among the public. …”
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Research on privacy preservation of member inference attacks in online inference process for vertical federated learning linear model by Hongshu YIN, Xuhua ZHOU, Wenjun ZHOU

“…With the development of big data and the introduction of data security regulations, the awareness of privacy protection has gradually increased, and the phenomenon of data isolation has become more and more serious.Federated learning technology as one of the effective methods to solve this problem has become a hot spot of concern.In the online inference process of vertical federated learning, the current mainstream methods do not consider the protection of data identity, which is easy to leak user privacy.A privacy protection method for member inference attacks was proposed in the online inference process of the vertical federated linear model.A filter with a false positive rate was constructed to avoid the accurate positioning of data identity to ensure the security of data.Homomorphic encryption was used to realize the full encrypted state of the online inference process and protect the intermediate calculation results.According to the ciphertext multiplication property of homomorphic encryption, the random number multiplication method was used to mask data, which ensured the security of the final inference result.This scheme further improved the security of user privacy in the online inference process of vertical federated learning and had lower computation overhead and communication costs.…”
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Patient and clinician experiences with the implementation of telemedicine and related adaptations in office-based buprenorphine treatment during the COVID-19 pandemic: a qualitativ... by Melissa Davoust, Angela R. Bazzi, Samantha Blakemore, Juliana Blodgett, Anna Cheng, Sarah Fielman, Kara M. Magane, Jacqueline Theisen, Richard Saitz, Alicia S. Ventura, Zoe M. Weinstein

“…We coded all interview data and used a thematic analysis approach to understand how telemedicine impacted treatment quality and engagement in care, as well as preferences for using telemedicine moving forward. …”
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Integration of metaheuristic based feature selection with ensemble representation learning models for privacy aware cyberattack detection in IoT environments by M. Karthikeyan, R. Brindha, Maria Manuel Vianny, V. Vaitheeshwaran, Mrinal Bachute, Sanket Mishra, Bibhuti Bhusan Dash

“…Abstract The Internet of Things (IoT) connects virtual and physical objects inserted with software, devices, and other technology that interchange data utilizing the Internet. It enables diverse devices and individuals to exchange data, interconnect, and personalize services to ease usage. …”
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Integrating advanced neural network architectures with privacy enhanced encryption for secure and intelligent healthcare analytics by C. Ramesh Babu Durai, S. Dhanasekaran, M. Jamuna Rani, Sindhu Chandra Sekharan

“…Detailed evaluation accepts the performance of structure in maintaining privacy through providing high-demonstration analysis for healthcare data protection. …”
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Self-monitoring of health - user viewpoints on gathering data using consumer health technologies during leisure time by Nora Weinberger, Martina F. Baumann, Maria Maia

“…It focuses on attitudes toward health data collection, data sharing, privacy concerns, and the use of EEG-supported devices.ResultsFindings reveal a complex landscape of trust and concern. …”
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Using big data analytics to improve HIV medical care utilisation in South Carolina: A study protocol by Mohammad Rifat Haider, Bankole Olatosi, Jiajia Zhang, Sharon Weissman, Jianjun Hu, Xiaoming Li

“…The RFA is authorised to collect and merge data from these different sources and to ensure the privacy of all PLWH. …”
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An automated privacy-preserving self-supervised classification of COVID-19 from lung CT scan images minimizing the requirements of large data annotation by Sadia Sultana Chowa, Md Rahad Islam Bhuiyan, Mst. Sazia Tahosin, Asif Karim, Sidratul Montaha, Md. Mehedi Hassan, Mohd Asif Shah, Sami Azam

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USER ACCEPTANCE OF TERMS & CONDITIONS AND PRIVACY POLICY: A LEGAL ANALYSIS OF THE POSITION OF FOOD DELIVERY MOBILE APPS IN THE MALAYSIAN CONTEXT by Mohammed Ibrahim Al Rezan, Md. Mostafa Hosain, Mohammad Ershadul Karim

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Malaysian Public’s Perception Toward Event Data Recorder (EDR) in Vehicles by Fadhlan Hafizhelmi Kamaru Kamaru Zaman, Ismail Danish Rozaimi, Syahrul Afzal Che Abdullah, Lucyantie Mazalan, Husna Zainol Abidin, Amir Radzi Ab. Ghani, Yahaya Ahmad

“…Besides, 40.3% expressed concern about potential privacy breaches and misuse of EDR data. Despite that, nearly 80% of respondents were in favor of installing EDR in their vehicles and allowing the data to be used in court. …”
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