Many anomaly detection applications naturally pro-duce datasets that can be represented
as bipartite graphs (user-interaction-item graphs). These graph datasets are usually sup …

With the development of the smart grid, the number of recorded energy and power times
series increases noticeably. This increase allows for the automation of smart grid …

The ultimate objective of intrusion detection problem is to identify surprising intrusions that
compromise networks. Determining intrusions through the application of classifiers or …

The rapid development of web applications has created many security problems related to
intrusions not just on computer, network systems, but also on web applications themselves …

Adversarial learning is used to test the robustness of machine learning algorithms under
attack and create attacks that deceive the anomaly detection methods in Industrial Control …

By definition, outliers are rarely observed in reality, making them difficult to detect or analyze.
Artificial outliers approximate such genuine outliers and can, for instance, help with the …

As susceptibility of commercial crops to the changing climates and resulting harsher
conditions increases, interest in the potential of resilient underutilised crops grows …

Abstract Structured Query Language (SQL) injection attacks represent a substantial threat to
the security of web applications, making the development of effective detection techniques …

To address the lack of datasets for agetech, this paper presents an approach for generating
synthetic datasets that include traces of benign and attack datasets for agetech. The …

In complex systems like social media and financial transactions, diverse entities (users,
groups, products) interact through a multitude of relationships (friendships, comments …