[HTML][HTML] Human, all too human? An all-around appraisal of the “artificial intelligence revolution” in medical imaging
F Coppola, L Faggioni, M Gabelloni… - Frontiers in …, 2021 - frontiersin.org
Artificial intelligence (AI) has seen dramatic growth over the past decade, evolving from a
niche super specialty computer application into a powerful tool which has revolutionized …
niche super specialty computer application into a powerful tool which has revolutionized …
Explainable artificial intelligence in cybersecurity: A survey
Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being's daily
life. Despite the AI benefits, its application suffers from the opacity of complex internal …
life. Despite the AI benefits, its application suffers from the opacity of complex internal …
[HTML][HTML] A novel approach for network intrusion detection using multistage deep learning image recognition
The current rise in hacking and computer network attacks throughout the world has
heightened the demand for improved intrusion detection and prevention solutions. The …
heightened the demand for improved intrusion detection and prevention solutions. The …
A survey of recent advances in deep learning models for detecting malware in desktop and mobile platforms
Malware is one of the most common and severe cyber threats today. Malware infects
millions of devices and can perform several malicious activities including compromising …
millions of devices and can perform several malicious activities including compromising …
A novel malware classification and augmentation model based on convolutional neural network
The rapid development and widespread use of the Internet have led to an increase in the
number and variety of malware proliferating via the Internet. Malware is the general …
number and variety of malware proliferating via the Internet. Malware is the general …
Transfer learning-based convolutional neural network for COVID-19 detection with X-ray images
K Sahinbas, FO Catak - Data science for COVID-19, 2021 - Elsevier
Countries the world over have focused on protecting human health and combatting the
COVID-19 outbreak. It has had a destructive effect on human health and daily life. Many …
COVID-19 outbreak. It has had a destructive effect on human health and daily life. Many …
[PDF][PDF] Two-stage hybrid malware detection using deep learning
With the increasing number and variety of Internet of Things (IoT) devices supporting a wide
range of services such as smart homes, smart transportation, and smart factories in smart …
range of services such as smart homes, smart transportation, and smart factories in smart …
A benchmark API call dataset for windows PE malware classification
FO Catak, AF Yazı - arXiv preprint arXiv:1905.01999, 2019 - arxiv.org
The use of operating system API calls is a promising task in the detection of PE-type
malware in the Windows operating system. This task is officially defined as running malware …
malware in the Windows operating system. This task is officially defined as running malware …
[HTML][HTML] IIoT malware detection using edge computing and deep learning for cybersecurity in smart factories
H Kim, K Lee - Applied Sciences, 2022 - mdpi.com
The smart factory environment has been transformed into an Industrial Internet of Things
(IIoT) environment, which is an interconnected and open approach. This has made smart …
(IIoT) environment, which is an interconnected and open approach. This has made smart …
Api2vec: Learning representations of api sequences for malware detection
Analyzing malware based on API call sequence is an effective approach as the sequence
reflects the dynamic execution behavior of malware. Recent advancements in deep learning …
reflects the dynamic execution behavior of malware. Recent advancements in deep learning …