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Risk Management and Healthcare Policy 2024Growing cyberattacks have made it more challenging to maintain healthcare information system (HIS) security in medical institutes, especially for hospitals that provide...
BACKGROUND
Growing cyberattacks have made it more challenging to maintain healthcare information system (HIS) security in medical institutes, especially for hospitals that provide patient portals to access patient information, such as electronic health record (EHR).
OBJECTIVE
This work aims to evaluate the patient portal security risk of Taiwan's EEC (EMR Exchange Center) member hospitals and analyze the association between patient portal security, hospital location, contract category and hospital type.
METHODS
We first collected the basic information of EEC member hospitals, including hospital location, contract category and hospital type. Then, the patient portal security of individual hospitals was evaluated by a well-known vulnerability scanner, UPGUARD, to assess website if vulnerable to high-level attacks such as denial of service attacks or ransomware attacks. Based on their UPSCAN scores, hospitals were classified into four security ratings: absolute low risk, low to medium risk, medium to high risk and high risk. Finally, the associations between security rating, contract category and hospital type were analyzed using chi-square tests.
RESULTS
We surveyed a total of 373 EEC member hospitals. Among them, 20 hospital patient portals were rated as "absolute low risk", 104 hospital patient portals as "low to medium risk", 99 hospital patient portals as "medium to high risk" and 150 hospital patient portals as "high risk". Further investigation revealed that the patient portal security of EEC member hospitals was significantly associated with the contract category and hospital type (<0.001).
CONCLUSION
The analysis results showed that large-scale hospitals generally had higher security levels, implying that the security of low-tier and small-scale hospitals may warrant reinforcement or strengthening. We suggest that hospitals should pay attention to the security risk assessment of their patient portals to preserve patient information privacy.
PubMed: 38910900
DOI: 10.2147/RMHP.S463408 -
Network (Bristol, England) Jun 2024Cloud computing (CC) is a future revolution in the Information technology (IT) and Communication field. Security and internet connectivity are the common major factors...
Cloud computing (CC) is a future revolution in the Information technology (IT) and Communication field. Security and internet connectivity are the common major factors to slow down the proliferation of CC. Recently, a new kind of denial of service (DDoS) attacks, known as Economic Denial of Sustainability (EDoS) attack, has been emerging. Though EDoS attacks are smaller at a moment, it can be expected to develop in nearer prospective in tandem with progression in the cloud usage. Here, EfficientNet-B3-Attn-2 fused Deep Quantum Neural Network (EfficientNet-DQNN) is presented for EDoS detection. Initially, cloud is simulated and thereafter, considered input log file is fed to perform data pre-processing. Z-Score Normalization ;(ZSN) is employed to carry out pre-processing of data. Afterwards, feature fusion (FF) is accomplished based on Deep Neural Network (DNN) with Kulczynski similarity. Then, data augmentation (DA) is executed by oversampling based upon Synthetic Minority Over-sampling Technique (SMOTE). At last, attack detection is conducted utilizing EfficientNet-DQNN. Furthermore, EfficientNet-DQNN is formed by incorporation of EfficientNet-B3-Attn-2 with DQNN. In addition, EfficientNet-DQNN attained 89.8% of F1-score, 90.4% of accuracy, 91.1% of precision and 91.2% of recall using BOT-IOT dataset at K-Fold is 9.
PubMed: 38904211
DOI: 10.1080/0954898X.2024.2361093 -
BMC Public Health Jun 2024Social desirability can negatively affect the validity of self-reported measures, including underreporting of stigmatized behaviors like alcohol consumption. The...
BACKGROUND
Social desirability can negatively affect the validity of self-reported measures, including underreporting of stigmatized behaviors like alcohol consumption. The Marlowe-Crowne Social Desirability Scale (SDS) is widely implemented and comprised of Denial and Attribution Domains (i.e., tendencies to deny undesirable traits or attribute socially desirable traits to oneself, respectively). Yet, limited psychometric research has been conducted in sub-Saharan Africa, where the prevalence of unhealthy alcohol consumption is high as well as religiosity and hierarchical social norms. To address this gap, we (a) conducted an exploratory study assessing certain psychometric properties of the 28-item SDS (Runyankole-translated) among persons with HIV (PWH) in Uganda, and (b) examined the relationship between social desirability and self-reported alcohol use.
METHODS
We pooled baseline data (N = 1153) from three studies of PWH engaged in alcohol use from 2017 to 2021. We assessed the translated scale's construct validity (via confirmatory factor analysis), internal consistency, item performance, differential item functioning by gender, concurrent validity with the DUREL religiosity index domains, and the association between social desirability and self-reported alcohol use.
RESULTS
Participants had a mean age of 40.42 years, 63% were men, and 91% had an undetectable HIV viral load. The 28-item SDS had satisfactory construct validity (Model fit indices: RMSEA = 0.07, CFI = 0.84, TLI = 0.82) and internal consistency (Denial Domain Ω = 0.82, Attribution Domain Ω = 0.69). We excluded Item 14 ("I never hesitate to help someone in trouble") from the Attribution Domain, which mitigated differential measurement error by gender and slightly improved the construct validity (Model fit indices: RMSEA = 0.06, CFI = 0.86, TLI = 0.85) and reliability (Attribution Domain Ω = 0.72) of the 27-item modified SDS. Using the 27-item SDS, we found that social desirability was weakly correlated with religiosity and inversely associated with self-reported alcohol use after adjusting for biomarker-measured alcohol use and other confounders (β = -0.05, 95% confidence interval: -0.09 to -0.01, p-value = 0.03).
CONCLUSIONS
We detected and mitigated measurement error in the 28-item Runyankole-translated SDS, and found that the modified 27-item scale had satisfactory construct validity and internal consistency in our sample. Future studies should continue to evaluate the psychometric properties of the Runyankole-translated SDS, including retranslating Item 14 and reevaluating its performance.
Topics: Humans; Psychometrics; Male; Female; Social Desirability; HIV Infections; Adult; Uganda; Middle Aged; Self Report; Alcohol Drinking; Reproducibility of Results; Surveys and Questionnaires
PubMed: 38898463
DOI: 10.1186/s12889-024-18886-z -
Sensors (Basel, Switzerland) Jun 2024Internet of Things (IoT) technology has become an inevitable part of our daily lives. With the increase in usage of IoT Devices, manufacturers continuously develop IoT... (Review)
Review
Internet of Things (IoT) technology has become an inevitable part of our daily lives. With the increase in usage of IoT Devices, manufacturers continuously develop IoT technology. However, the security of IoT devices is left behind in those developments due to cost, size, and computational power limitations. Since these IoT devices are connected to the Internet and have low security levels, one of the main risks of these devices is being compromised by malicious malware and becoming part of IoT botnets. IoT botnets are used for launching different types of large-scale attacks including Distributed Denial-of-Service (DDoS) attacks. These attacks are continuously evolving, and researchers have conducted numerous analyses and studies in this area to narrow security vulnerabilities. This paper systematically reviews the prominent literature on IoT botnet DDoS attacks and detection techniques. Architecture IoT botnet DDoS attacks, evaluations of those attacks, and systematically categorized detection techniques are discussed in detail. The paper presents current threats and detection techniques, and some open research questions are recommended for future studies in this field.
PubMed: 38894365
DOI: 10.3390/s24113571 -
Sensors (Basel, Switzerland) May 2024The healthcare industry went through reformation by integrating the Internet of Medical Things (IoMT) to enable data harnessing by transmission mediums from different...
The healthcare industry went through reformation by integrating the Internet of Medical Things (IoMT) to enable data harnessing by transmission mediums from different devices, about patients to healthcare staff devices, for further analysis through cloud-based servers for proper diagnosis of patients, yielding efficient and accurate results. However, IoMT technology is accompanied by a set of drawbacks in terms of security risks and vulnerabilities, such as violating and exposing patients' sensitive and confidential data. Further, the network traffic data is prone to interception attacks caused by a wireless type of communication and alteration of data, which could cause unwanted outcomes. The advocated scheme provides insight into a robust Intrusion Detection System (IDS) for IoMT networks. It leverages a honeypot to divert attackers away from critical systems, reducing the attack surface. Additionally, the IDS employs an ensemble method combining Logistic Regression and K-Nearest Neighbor algorithms. This approach harnesses the strengths of both algorithms to improve attack detection accuracy and robustness. This work analyzes the impact, performance, accuracy, and precision outcomes of the used model on two IoMT-related datasets which contain multiple attack types such as Man-In-The-Middle (MITM), Data Injection, and Distributed Denial of Services (DDOS). The yielded results showed that the proposed ensemble method was effective in detecting intrusion attempts and classifying them as attacks or normal network traffic, with a high accuracy of 92.5% for the first dataset and 99.54% for the second dataset and a precision of 96.74% for the first dataset and 99.228% for the second dataset.
Topics: Computer Security; Internet of Things; Humans; Algorithms; Delivery of Health Care; Wireless Technology; Cloud Computing; Confidentiality
PubMed: 38894166
DOI: 10.3390/s24113375 -
Archives of Women's Mental Health Jun 2024This study aims to describe the phenomenon of unperceived pregnancy followed by neonaticide with a focus on the lack of awareness of reproductive potential in an...
PURPOSE
This study aims to describe the phenomenon of unperceived pregnancy followed by neonaticide with a focus on the lack of awareness of reproductive potential in an Austrian sample.
METHODS
An explorative comparative study of neonaticide cases with single and repeat perpetrators was conducted using nationwide register-based data from 1995 to 2017. A total number of 55 cases out of 66 were included in the analysis. A standardized coding sheet was used and calculations were performed.
RESULTS
48 women gave birth to 101 children, of which 55 were killed, 23 children lived out of home care and 23 lived with the perpetrator We found a higher fertility rate in both neonaticide perpetrators in the single (1,9) and the repeat group (4,25) in comparison to the general population (1,4). The use of contraception was only 31% among neonaticide perpetrators, deviating substantially from the general Austrian population age group (16-29yrs) which used contraception in 91%. The neonaticide perpetrators used an effective contraception method (pearl-index < 4) in only 2%, whereas 20% of the general population did so. The number of unperceived pregnancies was high in both groups (50/55) 91%.
CONCLUSION
Future case reports and forensic evaluations should take reproductive behavior into account, as it may offer valuable insights into the events leading up to neonaticide. Our findings suggest that denial of reproductive potential often precedes unperceived pregnancies. In the Austrian cohort, women who experienced unperceived pregnancies resulting in unassisted births and subsequent neonaticide showed a low prevalence of contraceptive use. This is particularly noteworthy given that the primary motive for neonaticide is unwanted pregnancy.
PubMed: 38890196
DOI: 10.1007/s00737-024-01481-x -
Journal of Affective Disorders Jun 2024The COVID-19 pandemic has contributed to significant societal challenges, including increased substance misuse. The COVID stress syndrome is a constellation of...
The COVID-19 pandemic has contributed to significant societal challenges, including increased substance misuse. The COVID stress syndrome is a constellation of interrelated processes that occur in response to pandemics, including danger/contamination fears, fears concerning economic consequences, xenophobia, compulsive checking/reassurance-seeking, and pandemic-related traumatic stress symptoms. In the present study, using a sample of 812 adults collected during the early stages of the COVID-19 pandemic in May 2020, we examined the relations between identified profiles of the COVID Stress Scales (CSS) and behavioral and cognitive aspects of substance misuse. Using profile analysis via multidimensional scaling (PAMS), we identified two core profiles of the CSS, which explained 60 % of the variance in participant responding: 1) High compulsive checking & Low xenophobia and 2) High xenophobia & Low danger/contamination. The first profile is consistent with the COVID stress syndrome, while the second profile aligns with the COVID disregard syndrome, which is a constellation of interrelated processes distinguished by a denial or downplaying of the seriousness of the COVID-19 pandemic and lack of perceived vulnerability to disease. Both profiles demonstrated significant positive correlations with drug and alcohol misuse, respectively. However, only the High xenophobia & Low danger/contamination profile demonstrated relations with cognitive aspects of substance misuse via positive and negative correlations with positive and negative expectancies of alcohol use, respectively. These findings provide further support for the relationship between the COVID stress syndrome and substance misuse and offer insight into how unique profiles of this syndrome may impact pandemic-related mental and public health interventions.
PubMed: 38889859
DOI: 10.1016/j.jad.2024.06.044 -
Open Forum Infectious Diseases Jun 2024A vaccine for coccidioidomycosis is likely to undergo trials in the near future. In this paper, we raise 4 questions that should be answered before its use and offer our...
A vaccine for coccidioidomycosis is likely to undergo trials in the near future. In this paper, we raise 4 questions that should be answered before its use and offer our solutions to these questions. These include defining the goals of vaccination, determining who should be vaccinated, how to measure vaccine immunity and protection, and how to address vaccine hesitancy and denial.
PubMed: 38887487
DOI: 10.1093/ofid/ofae095 -
Scientific Reports Jun 2024In the rapidly evolving landscape of Internet of Things (IoT), Zigbee networks have emerged as a critical component for enabling wireless communication in a variety of...
In the rapidly evolving landscape of Internet of Things (IoT), Zigbee networks have emerged as a critical component for enabling wireless communication in a variety of applications. Despite their widespread adoption, Zigbee networks face significant security challenges, particularly in key management and network resilience against cyber attacks like distributed denial of service (DDoS). Traditional key rotation strategies often fall short in dynamically adapting to the ever-changing network conditions, leading to vulnerabilities in network security and efficiency. To address these challenges, this paper proposes a novel approach by implementing a reinforcement learning (RL) model for adaptive key rotation in Zigbee networks. We developed and tested this model against traditional periodic, anomaly detection-based, heuristic-based, and static key rotation methods in a simulated Zigbee network environment. Our comprehensive evaluation over a 30-day period focused on key performance metrics such as network efficiency, response to DDoS attacks, network resilience under various simulated attacks, latency, and packet loss in fluctuating traffic conditions. The results indicate that the RL model significantly outperforms traditional methods, demonstrating improved network efficiency, higher intrusion detection rates, faster response times, and superior resource management. The study underscores the potential of using artificial intelligence (AI)-driven, adaptive strategies for enhancing network security in IoT environments, paving the way for more robust and intelligent Zigbee network security solutions.
PubMed: 38886241
DOI: 10.1038/s41598-024-64895-8 -
Psychotherapie, Psychosomatik,... Jun 2024In the following casuistry, a denied advanced pregnancy was discovered during the diagnosis of an oncological disease. Faced with a life-threatening condition, the...
In the following casuistry, a denied advanced pregnancy was discovered during the diagnosis of an oncological disease. Faced with a life-threatening condition, the patient urged late termination of the pregnancy and was introduced to psychological counselling in order to find a viable and ethically justifiable solution. Strategies for crisis intervention and supportive approaches in the patient's care as well as interdisciplinary collaboration are presented and discussed.
PubMed: 38885657
DOI: 10.1055/a-2322-8408