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Cureus Nov 2023The integration of 5G technology in the healthcare sector is poised to bring about transformative changes, offering numerous advantages such as enhanced telemedicine... (Review)
Review
The integration of 5G technology in the healthcare sector is poised to bring about transformative changes, offering numerous advantages such as enhanced telemedicine services, expedited data transfer for medical records, improved remote surgery capabilities, real-time monitoring and diagnostics, advancements in wearable medical devices, and the potential for precision medicine. However, this technological shift is not without its concerns, including potential health implications related to 5G radiation exposure, heightened cybersecurity risks for medical devices and data systems, potential system failures due to technology dependence, and privacy issues linked to data breaches in healthcare. We are striking a balance between harnessing these benefits and addressing the associated risks. Achieving this equilibrium requires the establishment of a robust regulatory framework, ongoing research into the health impacts of 5G radiation, the implementation of stringent cybersecurity measures, education and training for healthcare professionals, and the development of ethical standards. The future of 5G in the medical field holds immense promise, but success depends on our ability to navigate this evolving landscape while prioritizing patient safety, privacy, and ethical practice.
PubMed: 38098915
DOI: 10.7759/cureus.48767 -
Heliyon Dec 2023Traditional cloud-centric approaches to medical data sharing pose risks related to real-time performance, security, and stability. Medical and healthcare data encounter...
Traditional cloud-centric approaches to medical data sharing pose risks related to real-time performance, security, and stability. Medical and healthcare data encounter challenges like data silos, privacy breaches, and transmission latency. In response to these challenges, this paper introduces a blockchain-based framework for trustworthy medical data sharing in edge computing environments. Leveraging healthcare consortium edge blockchains, this framework enables fine-grained access control to medical data. Specifically, it addresses the real-time, multi-attribute authorization challenge in CP-ABE through a Distributed Attribute Authorization strategy (DAA) based on blockchain. Furthermore, it tackles the key security issues in CP-ABE through a Distributed Key Generation protocol (DKG) based on blockchain. To address computational resource constraints in CP-ABE, we enhance a Distributed Modular Exponentiation Outsourcing algorithm (DME) and elevate its verifiable probability to "1". Theoretical analysis establishes the IND-CPA security of this framework in the Random Oracle Model. Experimental results demonstrate the effectiveness of our solution for resource-constrained end-user devices in edge computing environments.
PubMed: 38090001
DOI: 10.1016/j.heliyon.2023.e22542 -
AJPM Focus Feb 2024Alcohol use disorders are heritable, with genetic factors predicting approximately 50% of the risk. Returning information about genetic risk could promote avoidance of...
INTRODUCTION
Alcohol use disorders are heritable, with genetic factors predicting approximately 50% of the risk. Returning information about genetic risk could promote avoidance of alcohol, reducing alcohol use disorder risk. This study explored attitudes toward a precision prevention model of alcohol use disorder targeting adolescents.
METHODS
This study conducted interviews with adolescents and adults to explore attitudes about precision prevention of alcohol use disorders. Interviews were recorded, transcribed, and thematically analyzed to identify perceptions about acceptability, salience, potential harms, and benefits.
RESULTS
Among N=13 participants (mean age 28.6 years, 7 female), 5 had undergone genetic testing, and 6 had a personal or family history of substance use disorder. Attitudes were favorable toward precision prevention of alcohol use disorders for adolescents. Perceived benefits included the potential to engage youth, motivate behavior change, protect family by sharing genetic information, and prompt insight into family problems. Perceived harms included the potential for anxiety, false sense of immunity from alcohol use disorders should genetic testing indicate no heightened risk, and experience of stigma from disclosure or breach of privacy.
CONCLUSIONS
This qualitative study identified the potential harms and benefits of a precision prevention approach for addressing alcohol use disorder risk targeting adolescents, along with appreciation for the complexities of the model. Research is needed to elucidate operational, ethical, and communication strategies to advance the model.
PubMed: 38089426
DOI: 10.1016/j.focus.2023.100153 -
PeerJ. Computer Science 2023In modern society, environmental sustainability is a top priority as one of the most promising entities in the new energy sector. Electric vehicles (EVs) are rapidly...
In modern society, environmental sustainability is a top priority as one of the most promising entities in the new energy sector. Electric vehicles (EVs) are rapidly gaining popularity due to their promise of better performance and comfort. Above all, they can help address the problem of urban air pollution. Nonetheless, lithium batteries, one of the most essential and expensive components of EVs, have posed challenges, such as battery aging, personal safety, and recycling. Precisely estimating the remaining useful life (RUL) of lithium battery packs can effectively assist in enhancing the personal safety of EVs and facilitating secondary trading and recycling in other industries without compromising safety and reliability. However, the RUL estimation of batteries involves many variables, and the operating conditions of EV batteries are highly dynamic as they change with the environment and the driving style of the users. Many existing methods exist to estimate the RUL based on batteries' state of health (SOH), but only some are suitable for real-world data. There are several difficulties as follows. Firstly, obtaining data about battery usage in the real world takes work. Secondly, most of these estimation models must be more representative and generalized because they are trained on separate data for each battery. Lastly, collecting data for centralized training may lead to a breach of user privacy. In this article, we propose an RUL estimation method utilizing a deep learning (DL) approach based on long short-term memory (LSTM) and federated learning (FL) to predict the RUL of lithium batteries. We refrain from incorporating unmeasurable variables as inputs and instead develop an estimation model leveraging LSTM, capitalizing on its ability to predict time series data. In addition, we apply the FL framework to train the model to protect users' battery data privacy. We verified the results of the model on experimental data. Meanwhile, we analyzed the model on actual data by comparing its mean absolute and relative errors. The comparison of the training and prediction results of the three sets of experiments shows that the federated training method achieves higher accuracy in predicting battery RUL compared to the centralized training method and another DL method, with solid training stability.
PubMed: 38077580
DOI: 10.7717/peerj-cs.1652 -
Mathematical Biosciences and... Sep 2023In conventional message communication systems, the practice of multi-message multi-receiver signcryption communication encounters several challenges, including the...
In conventional message communication systems, the practice of multi-message multi-receiver signcryption communication encounters several challenges, including the vulnerability to Key Generation Center (KGC) attacks, privacy breaches and excessive communication data volume. The KGC necessitates a secure channel to transmit partial private keys, thereby rendering the security of these partial private keys reliant on the integrity of the interaction channel. This dependence introduces concerns regarding the confidentiality of the private keys. Our proposal advocates for the substitution of the KGC in traditional certificateless schemes with blockchain and smart contract technology. Parameters are publicly disclosed on the blockchain, leveraging its tamper-proof property to ensure security. Furthermore, this scheme introduces conventional encryption techniques to achieve user identity privacy in the absence of a secure channel, effectively resolving the issue of user identity disclosure inherent in blockchain-based schemes and enhancing communication privacy. Moreover, users utilize smart contract algorithms to generate a portion of the encrypted private key, thereby minimizing the possibility of third-party attacks. In this paper, the scheme exhibits resilience against various attacks, including KGC leakage attacks, internal privilege attacks, replay attacks, distributed denial of service attacks and Man-in-the-Middle (MITM) attacks. Additionally, it possesses desirable security attributes such as key escrow security and non-repudiation. The proposed scheme has been theoretically and experimentally analyzed under the random oracle model, based on the computational Diffie-Hellman problem and the discrete logarithm problem. It has been proven to possess confidentiality and unforgeability. Compared with similar schemes, our scheme has lower computational cost and shorter ciphertext length. It has obvious advantages in communication and time overhead.
PubMed: 38052552
DOI: 10.3934/mbe.2023806 -
Scientific Reports Nov 2023Navigating the challenges of data-driven speech processing, one of the primary hurdles is accessing reliable pathological speech data. While public datasets appear to...
Navigating the challenges of data-driven speech processing, one of the primary hurdles is accessing reliable pathological speech data. While public datasets appear to offer solutions, they come with inherent risks of potential unintended exposure of patient health information via re-identification attacks. Using a comprehensive real-world pathological speech corpus, with over n[Formula: see text]3800 test subjects spanning various age groups and speech disorders, we employed a deep-learning-driven automatic speaker verification (ASV) approach. This resulted in a notable mean equal error rate (EER) of [Formula: see text], outstripping traditional benchmarks. Our comprehensive assessments demonstrate that pathological speech overall faces heightened privacy breach risks compared to healthy speech. Specifically, adults with dysphonia are at heightened re-identification risks, whereas conditions like dysarthria yield results comparable to those of healthy speakers. Crucially, speech intelligibility does not influence the ASV system's performance metrics. In pediatric cases, particularly those with cleft lip and palate, the recording environment plays a decisive role in re-identification. Merging data across pathological types led to a marked EER decrease, suggesting the potential benefits of pathological diversity in ASV, accompanied by a logarithmic boost in ASV effectiveness. In essence, this research sheds light on the dynamics between pathological speech and speaker verification, emphasizing its crucial role in safeguarding patient confidentiality in our increasingly digitized healthcare era.
Topics: Adult; Humans; Child; Cleft Lip; Cleft Palate; Speech-Language Pathology; Speech Intelligibility; Speech Production Measurement; Speech
PubMed: 37993490
DOI: 10.1038/s41598-023-47711-7 -
Sexual and Reproductive Health Matters Dec 2023The COVID-19 pandemic highlighted the harm reduction potential of virtual sex work (VSW) such as video or audio calls with clients. VSW limits exposure to COVID-19 and...
The COVID-19 pandemic highlighted the harm reduction potential of virtual sex work (VSW) such as video or audio calls with clients. VSW limits exposure to COVID-19 and STIs. However, sex workers using digital technologies face high risks of technology-facilitated intimate partner violence (IPV), such as non-consensual distribution of intimate images. This study explored perceived risks and benefits of VSW, including the salience of STI harm reduction. Ethnographic interviews and participant observation with self-identified cis women sex workers in Dakar between January 2018 and August 2019 informed a further period of focused data collection in June 2022, in which two key research participants and the author devised a goal of concrete community benefit: a list of contextually relevant digital privacy precautions and resources. Brainstorming this list during workshops with 18 sex workers provided prompts for participant perspectives. While participants generally preferred VSW, citing STI prevention as a key reason, most resumed in-person sex work after COVID-19 curfews lifted; social risks of digital privacy breach and potential outing outweighed physical risks of contracting STIs. Participants proposed privacy features for mobile applications to make VSW viable and benefit from STI prevention. Their reflections call on tech companies to embed values of informed consent and privacy into platform design, shifting the burden of protecting privacy from individuals to companies. This study addresses a gap in technology-facilitated IPV research, which has concentrated on Euro-American contexts. Participant perspectives can inform action in technology policy sectors to advance criminalised communities' rights to sexual health, privacy, and autonomy.
Topics: Humans; Female; Sex Work; Sexual Health; Senegal; Pandemics; Privacy; COVID-19; Sexually Transmitted Diseases
PubMed: 37982806
DOI: 10.1080/26410397.2023.2272741 -
Healthcare Informatics Research Oct 2023Public healthcare data have become crucial to the advancement of medicine, and recent changes in legal structure on privacy protection have expanded access to these data...
OBJECTIVES
Public healthcare data have become crucial to the advancement of medicine, and recent changes in legal structure on privacy protection have expanded access to these data with pseudonymization. Recent debates on public healthcare data use by private insurance companies have shown large discrepancies in perceptions among the general public, healthcare professionals, private companies, and lawmakers. This study examined public attitudes toward the secondary use of public data, focusing on differences between public and private entities.
METHODS
An online survey was conducted from January 11 to 24, 2022, involving a random sample of adults between 19 and 65 of age in 17 provinces, guided by the August 2021 census.
RESULTS
The final survey analysis included 1,370 participants. Most participants were aware of health data collection (72.5%) and recent changes in legal structures (61.4%) but were reluctant to share their pseudonymized raw data (51.8%). Overall, they were favorable toward data use by public agencies but disfavored use by private entities, notably marketing and private insurance companies. Concerns were frequently noted regarding commercial use of data and data breaches. Among the respondents, 50.9% were negative about the use of public healthcare data by private insurance companies, 22.9% favored this use, and 1.9% were "very positive."
CONCLUSIONS
This survey revealed a low understanding among key stakeholders regarding digital health data use, which is hindering the realization of the full potential of public healthcare data. This survey provides a basis for future policy developments and advocacy for the secondary use of health data.
PubMed: 37964459
DOI: 10.4258/hir.2023.29.4.377 -
JMIR Human Factors Nov 2023Increased use of eHealth technology and user data to drive early identification and intervention algorithms in early psychosis (EP) necessitates the implementation of...
Incorporating Community Partner Perspectives on eHealth Technology Data Sharing Practices for the California Early Psychosis Intervention Network: Qualitative Focus Group Study With a User-Centered Design Approach.
BACKGROUND
Increased use of eHealth technology and user data to drive early identification and intervention algorithms in early psychosis (EP) necessitates the implementation of ethical data use practices to increase user acceptability and trust.
OBJECTIVE
First, the study explored EP community partner perspectives on data sharing best practices, including beliefs, attitudes, and preferences for ethical data sharing and how best to present end-user license agreements (EULAs). Second, we present a test case of adopting a user-centered design approach to develop a EULA protocol consistent with community partner perspectives and priorities.
METHODS
We conducted an exploratory, qualitative, and focus group-based study exploring mental health data sharing and privacy preferences among individuals involved in delivering or receiving EP care within the California Early Psychosis Intervention Network. Key themes were identified through a content analysis of focus group transcripts. Additionally, we conducted workshops using a user-centered design approach to develop a EULA that addresses participant priorities.
RESULTS
In total, 24 participants took part in the study (14 EP providers, 6 clients, and 4 family members). Participants reported being receptive to data sharing despite being acutely aware of widespread third-party sharing across digital domains, the risk of breaches, and motives hidden in the legal language of EULAs. Consequently, they reported feeling a loss of control and a lack of protection over their data. Participants indicated these concerns could be mitigated through user-level control for data sharing with third parties and an understandable, transparent EULA, including multiple presentation modalities, text at no more than an eighth-grade reading level, and a clear definition of key terms. These findings were successfully integrated into the development of a EULA and data opt-in process that resulted in 88.1% (421/478) of clients who reviewed the video agreeing to share data.
CONCLUSIONS
Many of the factors considered pertinent to informing data sharing practices in a mental health setting are consistent among clients, family members, and providers delivering or receiving EP care. These community partners' priorities can be successfully incorporated into developing EULA practices that can lead to high voluntary data sharing rates.
Topics: Humans; Focus Groups; User-Centered Design; Psychotic Disorders; California; Geraniaceae; Information Dissemination
PubMed: 37962921
DOI: 10.2196/44194 -
Sensors (Basel, Switzerland) Nov 2023Biomedical Microelectromechanical Systems (BioMEMS) serve as a crucial catalyst in enhancing IoT communication security and safeguarding smart healthcare systems....
Biomedical Microelectromechanical Systems (BioMEMS) serve as a crucial catalyst in enhancing IoT communication security and safeguarding smart healthcare systems. Situated at the nexus of advanced technology and healthcare, BioMEMS are instrumental in pioneering personalized diagnostics, monitoring, and therapeutic applications. Nonetheless, this integration brings forth a complex array of security and privacy challenges intrinsic to IoT communications within smart healthcare ecosystems, demanding comprehensive scrutiny. In this manuscript, we embark on an extensive analysis of the intricate security terrain associated with IoT communications in the realm of BioMEMS, addressing a spectrum of vulnerabilities that spans cyber threats, data manipulation, and interception of communications. The integration of real-world case studies serves to illuminate the direct repercussions of security breaches within smart healthcare systems, highlighting the imperative to safeguard both patient safety and the integrity of medical data. We delve into a suite of security solutions, encompassing rigorous authentication processes, data encryption, designs resistant to attacks, and continuous monitoring mechanisms, all tailored to fortify BioMEMS in the face of ever-evolving threats within smart healthcare environments. Furthermore, the paper underscores the vital role of ethical and regulatory considerations, emphasizing the need to uphold patient autonomy, ensure the confidentiality of data, and maintain equitable access to healthcare in the context of IoT communication security. Looking forward, we explore the impending landscape of BioMEMS security as it intertwines with emerging technologies such as AI-driven diagnostics, quantum computing, and genomic integration, anticipating potential challenges and strategizing for the future. In doing so, this paper highlights the paramount importance of adopting an integrated approach that seamlessly blends technological innovation, ethical foresight, and collaborative ingenuity, thereby steering BioMEMS towards a secure and resilient future within smart healthcare systems, in the ambit of IoT communication security and protection.
Topics: Humans; Privacy; Computing Methodologies; Ecosystem; Micro-Electrical-Mechanical Systems; Quantum Theory; Communication; Delivery of Health Care; Computer Security
PubMed: 37960646
DOI: 10.3390/s23218944