Industrial Internet of Things (IoT) is the most rapidly develo** industry in the current IoT
industry, and the intrusion detection system (IDS) remains one of the key technologies for …

Intrusion detection is an essential task for protecting the cyber environment from attacks.
Many studies have proposed sophisticated models to detect intrusions from a large amount …

In Uganda, the absence of a unified dataset for constructing machine learning models to
predict Foot and Mouth Disease outbreaks hinders preparedness. Although machine …

The class imbalance problem negatively impacts learning algorithms' performance in
minority classes which may constitute more severe attacks than the majority ones. This study …

Machine learning has made significant progress in image recognition, natural language
processing, and autonomous driving. However, the generation of adversarial examples has …

Context: Neural networks have achieved state-of-the-art performance in many fields.
However, they are often reported to produce overconfident predictions, especially for …

Due to the escalating network throughput and security risks, the exploration of intrusion
detection systems (IDSs) has garnered significant attention within the computer science …

Abstract Self-Admitted Technical Debt (SATD) is a workaround for current gains and
subsequent software quality in software comments. Some studies have been conducted …

This study investigates a false data injection detection method in an automatic data
acquisition platform for electric energy measurement with the aim of ensuring the stability …

Background: As preexisting comorbidities are risk factors for Coronavirus Disease 19
(COVID-19), improved tools are needed for screening or diagnosing COVID-19 in clinical …