Abstract Concept drift detection techniques can be used to discover substantial changes of
the patterns encoded in data streams in real-time. If left unaddressed, these changes can …

In the Industry 4.0 era of smart grids, the real-world problem of blackouts and cascading
failures due to cyberattacks is a significant concern and highly challenging because the …

Malware classification involves categorizing mal-ware samples based on their
characteristics. While deep learning techniques applied to malware execution traces, mainly …

In the domain of machine learning and predictive analytics, classifiers hold significant
importance as they are instrumental in extracting valuable patterns and enabling precise …

The dynamism of our digital universe systems presents a key challenge for predictive
analytics. Ensuring the model's ability to generalize beyond the training data is crucial for …

The escalating prevalence of cyber-activities under-scores the compelling need for
advanced protective mechanisms, with Intrusion Detection Systems (IDS) emerging as a …

Smart Grid has been exposed to cyberattacks that penetrate the Supervisory Control and
Data Acquisition systems, causing privacy and access control violations on security …