Healthcare cybersecurity is increasingly targeted by malicious hackers. This sector has many vulnerabilities and health data is very sensitive and valuable. Consequently, any damage caused by malicious intrusions is particularly alarming. The consequences of these attacks can be enormous and endanger patient care. Amongst the already-implemented cybersecurity measures and the ones that need to be further improved, this paper aims to demonstrate how penetration tests can greatly benefit healthcare cybersecurity. It is already proven that this approach has enforced cybersecurity in other sectors. However, it is not popular in healthcare since many prejudices still surround the hacking practice and there is a lack of education on hackers' categories and their ethics. The present analysis aims to comprehend what hacker ethics is and who ethical hackers are. Currently, hacker ethics has the status of personal ethics; however, to employ penetration testers in healthcare, it is recommended to draft an official code of ethics, comprising principles, standards, expectations, and best practices. Additionally, it is important to distinguish between malicious hackers and ethical hackers. Amongst the latter, penetration testers are only a sub-category. Acknowledging the subtle differences between ethical hackers and penetration testers allows to better understand why and how the latter can offer their services to healthcare facilities.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733027 | PMC |
| http://dx.doi.org/10.1186/s12910-022-00872-y | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Generative artificial intelligence enables the generation of bone scintigraphy images and improves generalization of deep learning models in data-constrained environments.
Eur J Nucl Med Mol Imaging
January 2025
Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.
Purpose: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generative artificial intelligence (AI) approach to create synthetic medical images taking the example of bone scintigraphy scans, to increase the data diversity of small-scale datasets for more effective model training and improved generalization.
Methods: We trained a generative model on Tc-bone scintigraphy scans from 9,170 patients in one center to generate high-quality and fully anonymized annotated scans of patients representing two distinct disease patterns: abnormal uptake indicative of (i) bone metastases and (ii) cardiac uptake indicative of cardiac amyloidosis.
Co-culture of Helicobacter pylori with oral microorganisms in human saliva.
Clin Oral Investig
January 2025
Department of Operative Dentistry and Periodontology, Center for Dental Medicine, Medical Center- University of Freiburg, Faculty of Medicine, University of Freiburg, University of Freiburg, Freiburg, Germany.
Objective: Helicobacter pylori is known for colonizing the gastric mucosa and instigating severe upper gastrointestinal diseases such as gastritis, gastroduodenal ulcers, and gastric cancer. To date, there is no data available on the oral cavity as transmission site, whether H. pylori can survive in the oral cavity or in human saliva.
View Article and Find Full Text PDFQuantitative accuracy of preclinical in ovo PET/MRI: influence of attenuation and quantification methods.
EJNMMI Phys
January 2025
QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
Aim: The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) provides an innovation leap in the use of fertilized chicken eggs (in ovo model) in preclinical imaging as PET/MRI enables the investigation of the chick embryonal organ-specific distribution of PET-tracers. However, hybrid PET/MRI inheres technical challenges in quantitative in ovo PET such as attenuation correction (AC) for the object as well as for additional hardware parts present in the PET field-of-view, which potentially contribute to quantification biases in the PET images if not accounted for. This study aimed to investigate the influence of the different sources of attenuation on in ovo PET/MRI and assess the accuracy of MR-based AC for in ovo experiments.
View Article and Find Full Text PDFPreclinical evaluation of the potential PARP-imaging probe [carbonyl-C]DPQ.
EJNMMI Radiopharm Chem
January 2025
Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
Background: Poly (ADP-ribose) polymerase (PARP) enzymes are crucial for the repair of DNA single-strand breaks and have become key therapeutic targets in homologous recombination-deficient cancers, including prostate cancer. To enable non-invasive monitoring of PARP-1 expression, several PARP-1-targeting positron emission tomography (PET) tracers have been developed. Here, we aimed to preclinically investigate [carbonyl-C]DPQ as an alternative PARP-1 PET tracer as it features a strongly distinct chemotype compared to the frontrunners [F]FluorThanatrace and [F]PARPi.
View Article and Find Full Text PDFWith hackers relentlessly disrupting cyberspace and the day-to-day operations of organizations worldwide, there are also concerns related to Personally Identifiable Information (PII). Due to the data breaches and the data getting dumped on the clear web or the dark web, there are serious concerns about how the different threat actors worldwide can misuse the data. Also, it raises the question of how hackers can create a profile of an individual starting from one data leak and getting more details on individuals with the help of Open Source Intelligence (OSINT).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!