Information Privacy Research Articles

Empowering precision medicine: Insights from a national survey on pharmacogenomics knowledge, attitudes, and perceptions among community pharmacists in the UAE

BackgroundCommunity pharmacists are essential to pharmacogenomics implementation because they can help trainers, clinical advisors, and other medical professionals understand the importance of pharmacogenomics and encourage them to use it in their practice. This study is to evaluate the community pharmacists' understanding, attitudes, and perceptions of pharmacogenomics in the United Arab Emirates (UAE). MethodsProfessionals employed at community pharmacies in Abu Dhabi, Dubai, and the Northern Emirates participated in a cross-sectional study design. From July 2023 to February 2024, five pharmacy students in their last year conducted the survey. The study team employed a structured questionnaire to collect data in addition to conducting in-person interviews. The study questionnaire comprised three distinct sections namely, demographic information, knowledge of pharmacogenomics concepts, and perceptions regarding pharmacogenomics. ResultsA total of 586 pharmacists enrolled in the study. The average knowledge score regarding pharmacogenomics was 75.1 % with a 95 % confidence interval (CI) of [72.4 %, 77.7 %]. The average attitude score toward pharmacogenomics was 67.5 % with a 95 % CI of [66.3 %, 68.7 %]. Better pharmacogenomics knowledge among several groups: independent pharmacies (OR 1.7; 95 % CI 1.2–2.4), Pharmacists in Charge (OR 1.4; 95 % CI 1.3–2.02), pharmacists with 11–15 years of experience (OR 2.1; 95 % CI 1.4–4.2), graduates from international universities (OR 4.6; 95 % CI 1.6–12.9), and those who received training on pharmacogenomics (OR 11.9; 95 % CI 3.3–14.5). Similarly, better attitude scores were observed among independent pharmacies (OR 1.5; 95 % CI 1.1–2.1), Pharmacists in Charge (OR 1.5; 95 % CI 1.07–2.1), pharmacists with 16–20 years of experience (OR 2.1; 95 % CI 1.16–3.7), graduates regional universities (OR 1.47; 95 % CI 1.05–2.1), and those who received training on pharmacogenomics (OR 4.8; 95 % CI 3.2–7.3). ConclusionThe positive attitudes toward pharmacogenomics that we found in our research indicate that community pharmacists in the United Arab Emirates are beginning to realize the potential advantages of pharmacogenomics in terms of improving patient care. Policies ensuring the privacy and confidentiality of genetic information are also necessary in considering concerns about the availability of genetic test results to insurance companies and potential employers.

Speak, search, and stay: determining customers' intentions to use voice-controlled artificial intelligence (AI) for finding suitable hotels and resorts

PurposeThe present study investigates the customers' behavioural intention to use voice-based artificial intelligence (AI) to find the appropriate hotels and resorts in an emerging nation. This study determines the influences of information quality, system quality, privacy, and novelty value on attitude and behavioural intention to use voice-based artificial intelligence to obtain the appropriate information and find the location of the hotels and resorts.Design/methodology/approachThis study used a purposive sampling method for collecting data from the respondents, who are customers of the hotels and resorts in Bangladesh. A self-administered survey questionnaire was used to obtain responses from 378 respondents. After collecting the data, the reliability and validity of the constructs and hypotheses were tested via partial least squares structural equation modelling (PLS-SEM).FindingsThe findings of the study indicate that information quality, system quality, privacy and novelty value have a positive and significant impact on attitude and behavioural intention to use voice-based AI assistant services in an emerging nation. However, system quality does not significantly influence behavioural intention to use voice-based AI assistant but it has an indirect significant influence on behavioural intention through the mediation effect of attitude.Practical implicationsThe study’s findings provide essential guidelines for practitioners to understand the impacts of information quality, system quality, privacy, and novelty value on attitude and behavioural intention to use voice-based artificial intelligence to find the appropriate hotels and resorts to meet customers' needs and expectations.Originality/valueThis study contributes to the existing literature on technology adoption by highlighting the interconnectedness of various factors influencing users' behavioural intentions. The study’s focus on an emerging nation provides a valuable theoretical contribution. It highlights that user perceptions and attitudes towards technology adoption may differ from those in developed nations due to unique contextual factors.

Examining consumers attitude towards E-wallet utilization as a payment method using technology acceptance model: A perspective from young generations in Nueva Ecija, Philippines

This study aims to provide valuable insights into how consumers interact with e-wallets in order to understand their behaviors and preferences. This perspective and behavior can help businesses and institutions better understand consumer behavior and develop strategies to increase e-wallet adoption. This research study is descriptive in nature. The researchers utilized frequency, percentage, weighted mean, and pearson R as statistical treatment. According to the findings, majority of respondents stated that Information Privacy is the most common and most encountered problem related to their use of e-wallets, while few reported the fewest, which were Unauthorized Application Updates. The statement implies that the majority of respondents were concerned about their information's security and safety. According to respondents, fear stems from concerns about others gaining unauthorized access, data breaches, or the misuse of sensitive information. Conduct interviews and surveys in your community to find out why people aren't using e-wallets. The researchers recommended implementing training programs on e-wallet usage to educate the community through focused campaigns, enhancing the usability and accessibility of the application for ongoing enhancement.

Strategic framework and global trends of national smart education policies

Integrating intelligent technology to promote smart education, had become a focus of education policies in many countries. However, there was little literature on strategies and trends of smart education policies at the national level. This study investigated the framework for developing national smart education strategies and trends of national policy making on smart education. Based on the Delphi technique method, a National Smart Education Framework was developed, consisting of four essential leveraging points: (1) forward-thinking governance and policy initiatives, (2) digital learning environments conducive to smart education, (3) transformative teaching and learning enabled through technology, and (4) overarching considerations. Additionally, a textual analysis method was employed to analyze 24 smart education policies from 24 countries or organizations, to uncover the strategies and policy trends of smart education in accordance with the proposed smart education framework. Promoting high-quality, inclusive, and accessible education, increasing Internet connectivity and access to digital tools, enhancing digital skills, ensuring information security and privacy, implementing new digital pedagogies, providing real-time feedback, emphasizing critical thinking, problem-solving, and creativity, etc. were the main trends for smart education policy making. The findings of this study provide valuable insights for policymakers and educators in shaping smart education policies and practices worldwide to promote sustainable development.

A certificateless designated verifier sanitizable signature in e-health intelligent mobile communication system

With the widespread use of mobile communication and smart devices in the medical field, mobile healthcare has gained significant attention due to its ability to overcome geographical limitations and provide more efficient and high-quality medical services. In mobile healthcare, various instruments and wearable device data are collected, encrypted, and uploaded to the cloud, accessible to medical professionals, researchers, and insurance companies, among others. However, ensuring the security and privacy of healthcare data in the context of mobile networks has been a highly challenging issue. Certificateless signature schemes allow patients to conceal their respective privacy information for different sharing needs. Nevertheless, existing mobile healthcare data protection solutions suffer from costly certificate management and the inability to restrict signature verifiers. This paper proposes a certificateless designated verifier sanitizable signature for mobile healthcare scenarios, aiming to enhance the security and privacy of mobile healthcare data. This scheme enables the sanitization of sensitive data without the need for certificate management and allows for the specification of signature verifiers. This ensures the confidentiality of medical data, protects patient privacy, and prevents unauthorized access to healthcare data. Through security analysis and experimental comparisons, it is demonstrated that the proposed scheme is both efficient and effectively ensures data security and user privacy. Therefore, it is well-suited for privacy protection in mobile healthcare data.

Communication issues between caregivers and patients with concealment of advanced-stage cancer: A qualitative study.

Communication is a key element of palliative care. The concealment of advanced-stage diseases is a communication challenge. This study aimed to explore the patterns and difficulties in communication regarding the concealment of advanced-stage cancer between caregivers and patients. Methods: This qualitative study employed an interpretive phenomenological approach and was conducted at a district hospital in Thailand. Semi-structured in-depth interviews were performed to collect data from caregivers (i.e. family members) of patients regarding the concealment of advanced-stage cancer. The data analysis followed an inductive thematic approach. Ten in-depth interviews were conducted among the caregivers of patients aged 57-97 years. Four themes emerged: (i) reasons for concealing the diagnosis and prognosis (personality of patients and concerns about negative effects), (ii) communication patterns between caregivers and patients (communicating symptoms/signs instead of the diagnosis/prognosis and distorting information), (iii) difficulties and challenges in maintaining concealment (feelings of guilt, hesitation in sharing the information and suspicion of patients' awareness of their diagnosis/prognosis) and (iv) communication support from healthcare professionals (avoiding informing patients about their diagnosis/prognosis, supporting decision-making and disclosing the information). The concealment of advanced-stage cancer is perceived as an appropriate communication approach among some caregivers. Communicating information about advanced-stage cancer is dynamic. Some caregivers and families consider disclosing the information in the future. Healthcare professionals can support communication throughout care. Future studies should focus on decision-making and communication processes for better handling of information concealment or the conspiracy of silence in palliative care.

Multimaterial Digital-Light Processing of Metal-Organic Framework (MOF) Composites: A Versatile Tool for the Rapid Microfabrication of MOF-Based Devices.

Patterning Metal-Organic Frameworks (MOFs) is essential for their use in sensing, electronics, photonics, and encryption technologies. However, current lithography methods are limited in their ability to pattern more than two MOFs, hindering the potential for creating advanced multifunctional surfaces. Additionally, balancing design flexibility, simplicity, and cost often results in compromises. This study addresses these challenges by combining Digital-Light Processing (DLP) with a capillary-assisted stop-flow system to enable multimaterial MOF patterning. It demonstrates the desktop fabrication of multiplexed arbitrary micropatterns across cm-scale areas while preserving the MOF's pore accessibility. The ink, consisting of a MOF crystal suspension in a low volatile solvent, a mixture of high molecular weight oligomers, and a photoinitiator, is confined by capillarity in the DLP projection area and quickly exchanged using syringe pumps. The versatility of this method is demonstrated by the direct printing of a ZIF-8-based luminescent oxygen sensor, a 5-component dynamic information concealment method, and a PCN-224-based colorimetric sensor for amines, covering disparate pore and analyte sizes. The multi-MOF capabilities, simplicity, and accessibility of this strategy pave the way for the facile exploration of MOF materials across a wide range of applications, with the potential to significantly accelerate the design-to-application cycle of MOF-based devices.

A Novel Authenticated Quantum Anonymous Secret Sharing for Classical and Quantum Information

AbstractAnonymous secret sharing (ASS) is an essential cryptographic concept that facilitates the sharing and reconstruction of secret information while safeguarding the identity of the involved secret receivers, which has broad applications in key management, data backup, and distributed systems. In this study, a novel authenticated quantum anonymous secret sharing (QASS) protocol that emphasizes information privacy and identity anonymity protection is proposed. Employing ‐level multipartite GHZ states as a quantum resource, one‐sided anonymous entanglement (AE) is innovatively established between the dealer and anonymous receivers, enabling the dealer to distribute a random share of secret information. Additionally, by establishing a one‐sided AE between anonymous receivers and restorer, the restorer can securely collect and reconstruct the secret information using quantum teleportation (QT). Rigorous security analysis demonstrates that protocol can resist attacks from active adversaries and potentially dishonest users. Quantum experiments on IBM Qiskit validate the correctness and feasibility of the proposed QASS protocol. This work contributes to the advancement of quantum anonymous communication, addressing the requirements for information privacy and identity anonymity in practical application environments.

Self-concealment scale (SCS) in middle-aged people: psychometric features and cross-age equivalence test

BackgroundIndividuals’ concealment of negative information and privacy may lead to impaired social interactions and threatened health conditions. This study aimed to investigate the effectiveness of the Self-Concealment Scale (SCS) in the middle-aged Chinese population and to examine the equivalence of the SCS among different age groups.MethodsThe current research adopted the SCS, Distress Disclosure Index (DDI), Revised Cheek and Buss Shyness Scale (RCBS), Social Interaction Anxiety Scale (SIAS), Social Phobia Scale (SPS), UCLA Loneliness Scale (ULS-8), and Kessler Psychological Distress Scale (K10) to survey 1124 middle-aged people. To explore the factor structure of the SCS, the study employed exploratory factor analysis and confirmatory factor analysis. The reliability of the SCS was measured based on Cronbach’s α coefficients, McDonald’s Omega coefficients, and split-half reliability. Correlation analysis was applied to examine the relationship between SCS and RCBS, SIAS, SPS, ULS-8, and K10. Moreover, this study recruited 1458 emerging adults and 1104 older adults to identify the cross-age invariance of the SCS.ResultsExploratory factor analysis of the middle aged adults’ data supported a single factor model. The factor loadings of SCS items ranged from 0.62 to 0.73, the commonality ranged from 0.39 to 0.53, and the single-factor model fitted well. The scale showed a Cronbach’s α coefficient value of 0.895, McDonald’s Omega coefficient of 0.893, and a split-half reliability coefficient value of 0.861. In addition, the SCS demonstrated invariance in emerging adults, middle-aged adults, and older adults. Further analysis showed that the scores of the SCS (F = 3.55, p = 0.029) among emerging adults (M = 26.43, SD = 7.96) were significantly higher than among middle-aged (M = 25.77, SD = 7.79), and older cohort (M = 25.69, SD = 7.91).ConclusionThe SCS revealed favorable psychometric characteristics among the middle-aged Chinese population. The degree of self-concealment among emerging adults was higher than that of middle-aged and older people.

Leveraging the use of a social media app as a collaborative medical information and knowledge sharing tool—insights from experiential use and survey of a CME WhatsApp community

Background and aimContinuing Medical Education (CME) is crucial for physicians to stay current in the rapidly advancing field of medicine. A WhatsApp (WA) based community of physicians was initiated in 2016 ‘WhatsApp CME India Group’ to facilitate learning, knowledge sharing, and discussion among physicians. Due to participant size constraints of the technology, it evolved into seven distinct WA groups, overseen by a central administrator. A survey undertaken in the group’s 7th year aimed to evaluate its effectiveness in achieving its goals, measure participant engagement, and uncover the primary factors driving its usage.MethodsThe survey questionnaire was distributed to 3500 members across the 07 WhatsApp CME groups for voluntary participation. Data collected was analysed using SPSS version 24.0 (SPSS Inc., Chicago, IL, USA) and reported using descriptive statistics.ResultsAmong the 581 survey respondents, the study found 43% of physicians use the WhatsApp academic groups for CME content, with 32% accessing their group over four times daily. The primary motivation for 77% was to discuss challenging cases and to gain knowledge updates from fellow physician (70%). Medical websites (57%), referral books (49%), and Google (43%) were other significant resources. Every participant (100%) found the WhatsApp CME India group the most beneficial resource for daily medical science updates. A significant portion (57%) of the respondents found the group valuable for real-time information exchange. Over 78% stated it kept them current with knowledge and guidelines. Notably, 94% viewed WhatsApp CME as complementary to physical conferences, not a replacement. The post-conference/webinar summaries were appreciated by 81% participants. Case discussions (31%) and update posts from fellow physicians sharing their insights and learnings (24%) were noted as activities of great academic interest.ConclusionThis study underscores the potential of digital platforms like WhatsApp in supplementing CME in India and potentially other comparable settings. The blend of digital and traditional resources suggests a balanced learning approach. While real-time engagement is a strength, challenges like information overload and privacy concerns require careful management. Striking a balance is crucial for ensuring content quality, structured discussions and privacy. As the digital age advances, professionals must critically assess shared information on these platforms to guarantee evidence-based and reliable knowledge dissemination.Trial registrationARK 001.

An efficient model of enhanced optimization and dilated-GRU based secured multi-access edge computing with blockchain for VANET sector

The establishment of Vehicular Ad Hoc Networks (VANETs) has brought significant advantages to humans, yet it also raises crucial safety considerations. Security is one of the major challenges in VANETs and is receiving significant attention. Hostile Onboard Units (OBUs) can use a variety of tactics including blocking, monitoring and tampering to harm neighboring OBUs to make illicit profits. The widespread use of the decentralized architecture built around blockchain technology has enabled the clear, safe, and dispersed storage and transmission of VANET application-related information without the need for an administrative center of authority. Perhaps the most important parts of the blockchain-driven VANET system involve implementing an efficient and adaptable consensus system, which remains an open academic issue. The objective of the suggested solution is to create a deep learning model for blockchain that will guarantee VANET security. This network topology is comprised of three layers: “perception, edge computing, and services”. The initial layer that comprises the blockchain operation is employed to demonstrate the privacy of VANET information. Additionally, cloud-based services as well as edge computing are used by the perception layer. The data is safeguarded by the service layer through the application of the blockchain system and storage in the cloud. The last layer aids in meeting user criteria for throughput and QoS. The main objective of this model is to evaluate the reliability of vehicle nodes maintained on the blockchain. Here, the node authentication is handled by an Adaptive Dilated Gated Recurrent Unit (AD-GRU), where the hyper-parameters of the recommended AD-GRU model are optimally tuned by an Enhanced Osprey Optimization Algorithm (EOOA). Finally, the proposed system is simulated and its extensive results are carried out. In contrast with other approaches, the novel system delivers the superior results of securing the data over the VANET environment.

Study of Patients' Privacy during the COVID-19 Pandemic in Iranian Health Care Settings.

Patient's privacy protection is a challenging ethical issue. The complex situation of the COVID-19 pandemic was a probable predictor of breaching confidentiality. This study aimed to assess the viewpoints of COVID-19-confirmed patients, who were hospitalized, and their healthcare providers about the compliance of different aspects of patient's privacy. This cross-sectional study included 3433 COVID-19-confirmed patients who were hospitalized in Kerman, between 2020 and 2021, and about 1228 related physicians, nurses, and paraclinical staff. Two separate validated researcher-made questionnaires were developed, each including subscales for physical, informational, and spatial privacy, as well as a satisfaction rate of privacy protection. The data were analyzed using SPSS software version 26, with independent samples t test, Mann-Whitney-U, Kruskal Wallis, and Multiple Linear Regression tests at a 95% confidence interval. The mean percentages of the patients' privacy scores in physical, spatial, and informational areas were significantly lower (P<0.001) than the average of the medical staff's scores in all three areas (Difference: 10.27%, 14.83%, and 4.91%, respectively). Physical and spatial privacy scores could be predicted based on the participants' classification, patients or medical staff, and sex. The mean patients' satisfaction score was 9.25% lower than the medical staff's (P<0.001). Moreover, only academic hospitals showed a statistically significant difference between the patient's satisfaction with privacy protection and medical staff's viewpoints (P<0.001). Although this study indicated the benefits of protecting patients' privacy in the healthcare setting, patients' privacy scores and satisfaction were lower than their healthcare providers. The pandemic conditions might have been an obstacle to preserving patients' rights. These findings demonstrated the importance of sensitizing healthcare providers to manage these ethical challenges in a complicated critical state such as the COVID-19 pandemic.

Distributed Cooperative Dispatch Method of Distribution Network with District Heat Network and Battery Energy Storage System Considering Flexible Regulation Capability

Flexible resources, including district heat networks (DHN) and battery energy storage systems (BESS), can provide flexible regulation capability for distribution networks (DN), thereby increasing the absorption capacity for renewable energy. In order to improve the operation economy of DN and ensure the information privacy of different operators, a distributed cooperative dispatch method of DN with DHN and BESS considering flexible regulation capability is proposed. First, a distributed cooperative dispatch framework of DN-DHN-BESS is constructed. Then, an optimal dispatch model of DHN under constant flow-variable temperature control strategy is established in order to utilize the heat storage capacity to provide flexible regulation capability for DN. Next, the optimal dispatch models of BESS and DN are established with the objective of minimizing the operation cost, respectively. Finally, a solution method based on the alternating direction multiplier method of distributed cooperative dispatch for DN-DHN-BESS is proposed. Case studies are performed on a system consisting of a 33-node DN and a 44-node DHN, and simulation results demonstrate that the proposed method differs from the centralized dispatch method by only 0.52% in the total system cost, and the proposed method reduces the total system cost by 34.5% compared to that of the independent dispatch method.

The role of deep learning in ensuring privacy integrity and security: Applications in AI-driven cybersecurity solutions

This article explores the critical role of deep learning in developing AI-driven cybersecurity solutions, with a particular focus on privacy integrity and information security. It investigates how deep neural networks (DNNs) and advanced machine learning techniques are being used to detect and neutralize cyber threats in real time. The article also considers the implications of these technologies for data privacy, discussing the potential risks and benefits of using AI to protect sensitive information. By examining case studies and current research, the piece provides insights into how organizations can deploy deep learning models to enhance both security and privacy integrity in a digital world.

Inclusion of people with disabilities in Chilean health policy: a policy analysis

BackgroundAround 18% of the population in Chile has disabilities. Evidence shows that this population has greater healthcare needs, yet they face barriers to accessing healthcare due to health system failures. This paper aims to assess the inclusion of people with disabilities in health policy documents and to explore the perceptions of key national stakeholders regarding the policy context, policy processes, and actors involved.MethodsA policy content analysis was conducted of 12 health policy documents using the EquiFrame framework, adapted to assess disability inclusion. Documents were reviewed and rated on their quality of commitment against 21 core concepts of human rights in the framework. Key national stakeholders (n = 15) were interviewed, and data were thematically analysed under the Walt and Gilson Policy Analysis Triangle, using NVivo R1.ResultsCore human rights concepts of disability were mentioned at least once in nearly all health policy documents (92%). However, 50% had poor policy commitments for disability. Across policies, Prevention of health conditions was the main human rights concept reflected, while Privacy of information was the least referenced concept. Participants described a fragmented disability movement and health policy, related to a dominant biomedical model of disability. It appeared that disability was not prioritized in the health policy agenda, due to ineffective mainstreaming of disability by the Government and the limited influence and engagement of civil society in policy processes. Moreover, the limited existing policy framework on disability inclusion is not being implemented effectively. This implementation gap was attributed to lack of financing, leadership, and human resources, coupled with low monitoring of disability inclusion.ConclusionsImprovements are needed in both the development and implementation of disability-inclusive health policies in Chile, to support the achievement of the right to healthcare for people with disabilities and ensuring that the health system truly “leaves no one behind”.

Blockchain-based proxy re-encryption access control method for biological risk privacy protection of agricultural products

In today’s globalized agricultural system, information leakage of agricultural biological risk factors can lead to business risks and public panic, jeopardizing corporate reputation. To solve the above problems, this study constructs a blockchain network for agricultural product biological risk traceability based on agricultural product biological risk factor data to achieve traceability of biological risk traceability data of agricultural product supply chain to meet the sustainability challenges. To guarantee the secure and flexible sharing of agricultural product biological risk privacy information and limit the scope of privacy information dissemination, the blockchain-based proxy re-encryption access control method (BBPR-AC) is designed. Aiming at the problems of proxy re-encryption technology, such as the third-party agent being prone to evil, the authorization judgment being cumbersome, and the authorization process not automated, we design the proxy re-encryption access control mechanism based on the traceability of agricultural products’ biological risk factors. Designing an attribute-based access control (ABAC) mechanism based on the traceability blockchain for agricultural products involves defining the attributes of each link in the agricultural supply chain, formulating policies, and evaluating and executing these policies, deployed in the blockchain system in the form of smart contracts. This approach achieves decentralization of authorization and automation of authority judgment. By analyzing the data characteristics within the agricultural product supply chain to avoid the malicious behavior of third-party agents, the decentralized blockchain system acts as a trusted third-party agent, and the proxy re-encryption is combined with symmetric encryption to improve the encryption efficiency. This ensures a efficient encryption process, making the system safe, transparent, and efficient. Finally, a prototype blockchain system for traceability of agricultural biological risk factors is built based on Hyperledger Fabric to verify this research method’s reliability, security, and efficiency. The experimental results show that this research scheme’s initial encryption, re-encryption, and decryption sessions exhibit lower computational overheads than traditional encryption methods. When the number of policies and the number of requests in the access control session is 100, the policy query latency is less than 400 ms, the request-response latency is slightly more than 360ms, and the data uploading throughput is 48.7 tx/s. The data query throughput is 81.8 tx/s, the system performance consumption is low and can meet the biological risk privacy protection needs of the agricultural supply chain. The BBPR-AC method proposed in this study provides ideas for achieving refined traceability management in the agricultural supply chain and promoting digital transformation in the agricultural industry.

The effect of political environment on security and privacy of contact tracing apps evaluation

PurposeContact tracing apps have emerged to collect data and mitigate the spread of infectious diseases. However, privacy and security concerns have caused individuals to hesitate to adopt these solutions. Our objective is to evaluate the role of the political environment, information privacy, security and users’ intentions to use contact tracing apps.Design/methodology/approachWe scraped the digital app store and collected 399 relevant reviews and other data from 21 contact tracing apps in the USA. A semi-supervised machine learning model was developed to extract information on privacy and security aspects from the reviews.FindingsOur findings show a positive connection between security controls and user adoption, as reflected in star ratings. Users residing in states with blue political environments tend to assign higher ratings to apps, especially when robust security controls are in place. These findings confirm the influence of the political environment on the adoption of contact tracing apps. In times of a pandemic, our findings suggest that users prioritize security over privacy concerns, emphasizing the critical role of strong security features in promoting app acceptance.Originality/valueThis paper emphasizes the political environment of the state offering the app intersects with concerns about security and privacy as well as the effectiveness of security and privacy measures, influencing the app’s ratings. Also, it shows the importance of understanding and addressing the role of the political environment when designing and promoting such public health tools, regardless of the specific disease or outbreak.

Joint bidding strategy of multi‐virtual power plant operators

AbstractThe distributed generation of new energy can effectively use the local endemic clean new energy and provide green power. However, due to the small scale and scattered layout of distributed generation resources, it is difficult to participate in the economic dispatch of power systems and even the competition of the power market. Virtual Power Plant (VPP) can act as a carrier of Distributed Energy Resource (DER) to manage its internal energy, to carry out combined bidding in the day‐ahead energy market and the regulation market. When virtual power plants coordinate multiple distributed energy resources to participate in electricity market transactions, the degree of disclosure of their internal privacy information will produce different trading strategies. A Stackelberg game model between multiple virtual power plant aggregators and virtual power plant operators is constructed, and the Kriging model is combined to protect the privacy information in the transactions of virtual power plant operators. Energy management for distributed generation is carried out, and the profit situation of virtual power plant operators under different strategies is analyzed.

Enhancing medical image classification via federated learning and pre-trained model

The precise classification of medical images is crucial in various healthcare applications, especially in fields like disease diagnosis and treatment planning. In recent times, machine-intelligent models are desired to work in remote settings. However, the potential privacy concerns that arise from sharing confidential patient information to train traditional centralized machine learning models cannot be ignored. Federated learning (FL) offers a promising method for collaborative training on distributed data held by various entities, ensuring the privacy of patient information. This study evaluated the efficiency of the pre-trained models in the FL environment for medical image classification. The Convolutional Neural Network (CNN) model with Gray-Level Co-occurrence Matrix (GLCM) and Local Binary Patterns (LBP), along with the EfficientNet model, are being used as the local models. The trainable parameters from the local models are fed as input for building the global model. Pre-trained models trained on extensive datasets, possess valuable characteristics that can be utilized by FL models trained on proprietary datasets. Implementing this method can improve the efficacy and precision of FL models while also ensuring data confidentiality. The proposed model is evaluated using two distinct medical imaging datasets: Magnetic Resonance Image(MRI) and Computed Tomography (CT) scan images. The research highlights the advantages of utilizing pre-trained models in federated learning for medical image classification (MIC). The model’s performance is assessed acrossseveral assessment criteria, demonstrating the model exhibited a satisfactory accuracy rate of 97.4% and 98.8% for MRI and CT scan images, respectively. The model is evaluated concerning to Diagnostic Odds Ratio (DOR), where the proposed global model has exhibited 1164.54 for the MRI images and 6825.17 for CT scan images, and the values have outperformed the pretrained model.

Securing Digital Identities: The Synergy of Information Technology Security, Trust, and Privacy

Securing Digital Identities: The Synergy of Information Technology Security, Trust, and Privacy