Data breaches in healthcare: security mechanisms for attack mitigation
The digitalisation of healthcare has increased the risk of cyberattacks in this sector, targeting
sensitive personal information. In this paper, we conduct a systematic review of existing …
sensitive personal information. In this paper, we conduct a systematic review of existing …
Transformative synergy: SSEHCET—bridging mobile edge computing and AI for enhanced eHealth security and efficiency
Blockchain technologies (BCT) are utilized in healthcare to facilitate a smart and secure
transmission of patient data. BCT solutions, however, are unable to store data produced by …
transmission of patient data. BCT solutions, however, are unable to store data produced by …
Restoring private autism dataset from sanitized database using an optimized key produced from enhanced combined PSO-GWO framework
The timely identification of autism spectrum disorder (ASD) in children is imperative to
prevent potential challenges as they grow. When sharing data related to autism for an …
prevent potential challenges as they grow. When sharing data related to autism for an …
Classification of Paediatric Pneumonia Using Modified DenseNet-121 Deep-Learning Model
There is a substantial worldwide effect, both in terms of disease and death, that is caused by
pediatric pneumonia, which is a disorder that affects children under the age of five. Even …
pediatric pneumonia, which is a disorder that affects children under the age of five. Even …
ConjunctiveNet: an improved deep learning-based conjunctive-eyes segmentation and severity detection model
S Pahwa, A Kaur, P Dhiman… - International Journal of …, 2024 - emerald.com
Purpose The study aims to enhance the detection and classification of conjunctival eye
diseases' severity through the development of ConjunctiveNet, an innovative deep learning …
diseases' severity through the development of ConjunctiveNet, an innovative deep learning …
Communication security of intelligent information service platform combining AES and ECC algorithms
B Fu, T Fang, L Zhang, Y Zhou… - Journal of Cyber Security …, 2024 - Taylor & Francis
The rapid progress of information technology has made the status of information service
platforms increasingly prominent in social operations. However, their communication …
platforms increasingly prominent in social operations. However, their communication …
RETRACTED ARTICLE: E-healthcare application cyber security analysis using quantum machine learning in malicious user detection
Z Liu, X Jia, B Li - Optical and Quantum Electronics, 2024 - Springer
In the medical field, it is crucial to manage visual and auditory data generated by Internet of
Things (IoT) devices. Cloud servers are often used to manage the massive amounts of data …
Things (IoT) devices. Cloud servers are often used to manage the massive amounts of data …
Incorporating Feature Interactions and Contrastive Learning for Credit Prediction
L Zhang, Q Yu, B Zhou, Y Zhang, Z Hu - IEEE Access, 2023 - ieeexplore.ieee.org
The efficacy of credit risk assessment models is pivotal to the risk management capacity of
financial institutions. Traditional credit risk models often suffer from inadequate predictive …
financial institutions. Traditional credit risk models often suffer from inadequate predictive …
Using trust and reputation for detecting groups of colluded agents in social networks
One of the most common types of malicious behavior in social networks is represented by
collusion, which consists of a secret cooperation between two or more agents providing …
collusion, which consists of a secret cooperation between two or more agents providing …
Anomaly based multi-stage attack detection method
W Ma, Y Hou, M **, P Jian - Plos one, 2024 - journals.plos.org
Multi-stage attacks are one of the most critical security threats in the current cyberspace. To
accurately identify multi-stage attacks, this paper proposes an anomaly-based multi-stage …
accurately identify multi-stage attacks, this paper proposes an anomaly-based multi-stage …