Art or Artifact: Evaluating the Accuracy, Appeal, and Educational Value of AI-Generated Imagery in DALL·E 3 for Illustrating Congenital Heart Diseases.

Artificial Intelligence (AI), particularly AI-Generated Imagery, has the potential to impact medical and patient education. This research explores the use of AI-generated imagery, from text-to-images, in medical education, focusing on congenital heart diseases (CHD). Utilizing ChatGPT's DALL·E 3, the research aims to assess the accuracy and educational value of AI-created images for 20 common CHDs.

VASERP: An Adaptive, Lightweight, Secure, and Efficient RFID-Based Authentication Scheme for IoV.

With the rapid growth in wireless communication and IoT technologies, Radio Frequency Identification (RFID) is applied to the Internet of Vehicles (IoV) to ensure the security of private data and the accuracy of identification and tracking. However, in traffic congestion scenarios, frequent mutual authentication increases the overall computing and communication overhead of the network. For this reason, in this work, we propose a lightweight RFID security fast authentication protocol for traffic congestion scenarios, designing an ownership transfer protocol to transfer access rights to vehicle tags in non-congestion scenarios.

Redefining food safety traceability system through blockchain: findings, challenges and open issues.

In the last few decades, there has been an increase in food safety and traceability issues. To prevent accidents and misconduct, it became essential to establish Food Safety Traceability System (FSTS) to trace the food from producer to consumer. The traceability systems can help track food in supply chains from farms to retail.

Smart sentiment analysis system for pain detection using cutting edge techniques in a smart healthcare framework.

A sentiment analysis system has been proposed in this paper for pain detection using cutting edge techniques in a smart healthcare framework. This proposed system may be eligible for detecting pain sentiments by analyzing facial expressions on the human face. The implementation of the proposed system has been divided into four components.

An Efficient Privacy-Preserving Public Auditing Protocol for Cloud-Based Medical Storage System.

The booming Internet of Things makes smart healthcare a reality, while cloud-based medical storage systems solve the problems of large-scale storage and real-time access of medical data. The integrity of medical data outsourced in cloud-based medical storage systems has become crucial since only complete data can make a correct diagnosis, and public auditing protocol is a key technique to solve this problem. To guarantee the integrity of medical data and reduce the burden of the data owner, we propose an efficient privacy-preserving public auditing protocol for the cloud-based medical storage systems, which supports the functions of batch auditing and dynamic update of data.

Hand-based multibiometric systems: state-of-the-art and future challenges.

The traditional methods used for the identification of individuals such as personal identification numbers (PINs), identification tags, etc., are vulnerable as they are easily compromised by the hackers. In this paper, we aim to focus on the existing multibiometric systems that use hand based modalities for the identification of individuals.

Ransomware: Recent advances, analysis, challenges and future research directions.

The COVID-19 pandemic has witnessed a huge surge in the number of ransomware attacks. Different institutions such as healthcare, financial, and government have been targeted. There can be numerous reasons for such a sudden rise in attacks, but it appears working remotely in home-based environments (which is less secure compared to traditional institutional networks) could be one of the reasons.

Emerging IoT Applications in Sustainable Smart Cities for COVID-19: Network Security and Data Preservation Challenges with Future Directions.

COVID-19 is a global infectious disease that can be easily spread by the contiguity of infected people. To prevent from COVID-19 and reduce its impact in sustainable smart cities, the global research communities are working relentlessly by harnessing the emerging technologies to develop the safest diagnosis, evaluation, and treatment procedures, and Internet of Things (IoT) is one of the pioneers among them. IoT can perform a pivotal role to diminish its immense contagious rate by suitable utilization in emerging healthcare IoT applications in sustainable smart cities.

Applications of blockchain in ensuring the security and privacy of electronic health record systems: A survey.

Due to the popularity of blockchain, there have been many proposed applications of blockchain in the healthcare sector, such as electronic health record (EHR) systems. Therefore, in this paper we perform a systematic literature review of blockchain approaches designed for EHR systems, focusing only on the security and privacy aspects. As part of the review, we introduce relevant background knowledge relating to both EHR systems and blockchain, prior to investigating the (potential) applications of blockchain in EHR systems.

Medical Image Analysis using Convolutional Neural Networks: A Review.

The science of solving clinical problems by analyzing images generated in clinical practice is known as medical image analysis. The aim is to extract information in an affective and efficient manner for improved clinical diagnosis. The recent advances in the field of biomedical engineering have made medical image analysis one of the top research and development area.

Design of Secure and Lightweight Authentication Protocol for Wearable Devices Environment.

Wearable devices are used in various applications to collect information including step information, sleeping cycles, workout statistics, and health-related information. Due to the nature and richness of the data collected by such devices, it is important to ensure the security of the collected data. This paper presents a new lightweight authentication scheme suitable for wearable device deployment.

A Standard Mutual Authentication Protocol for Cloud Computing Based Health Care System.

Telecare Medical Information System (TMIS) supports a standard platform to the patient for getting necessary medical treatment from the doctor(s) via Internet communication. Security protection is important for medical records (data) of the patients because of very sensitive information. Besides, patient anonymity is another most important property, which must be protected.

Correction: Optimizing SIEM Throughput on the Cloud Using Parallelization.

[This corrects the article DOI: 10.1371/journal.pone.

Optimizing SIEM Throughput on the Cloud Using Parallelization.

Processing large amounts of data in real time for identifying security issues pose several performance challenges, especially when hardware infrastructure is limited. Managed Security Service Providers (MSSP), mostly hosting their applications on the Cloud, receive events at a very high rate that varies from a few hundred to a couple of thousand events per second (EPS). It is critical to process this data efficiently, so that attacks could be identified quickly and necessary response could be initiated.

Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks.

A wireless sensor network (WSN) comprises small sensor nodes with limited energy capabilities. The power constraints of WSNs necessitate efficient energy utilization to extend the overall network lifetime of these networks. We propose a distance-based and low-energy adaptive clustering (DISCPLN) protocol to streamline the green issue of efficient energy utilization in WSNs.

A Multiserver Biometric Authentication Scheme for TMIS using Elliptic Curve Cryptography.

Recently several authentication schemes are proposed for telecare medicine information system (TMIS). Many of such schemes are proved to have weaknesses against known attacks. Furthermore, numerous such schemes cannot be used in real time scenarios.

A New Random Walk for Replica Detection in WSNs.

Wireless Sensor Networks (WSNs) are vulnerable to Node Replication attacks or Clone attacks. Among all the existing clone detection protocols in WSNs, RAWL shows the most promising results by employing Simple Random Walk (SRW). More recently, RAND outperforms RAWL by incorporating Network Division with SRW.