Social media platforms are popular for expressing personal views, emotions and beliefs.
Social media platforms are influential for propagating extremist ideologies for group …

Frontline law enforcement, police, and security personnel of various backgrounds have the
challenging task to identify extremists who have a high risk for committing violent acts …

Malicious actors often use phishing attacks to compromise legitimate users' credentials.
Machine learning is a promising approach for phishing detection. While the accuracy of …

Supervised machine learning is often used to detect phishing websites. However, the
scarcity of phishing data for training purposes limits the classifier's performance. Further …

The emergence of the Internet and social media has provided a ground conducive to the
rapid development of violent ideas and online malicious behavior, and even to rising the …

The search in graph databases for individuals or entities undertaking latent or emergent
behaviors has applicability in the areas of homeland security, consumer analytics …

To advance the agenda in counterterrorism, this work demonstrates how analysts can
combine unsupervised machine learning, exploratory data analysis, and statistical tests to …

In the digital era, online radicalization has emerged as a significant concern for
governments, social media platforms, and researchers. Detecting and preventing online …

Among the operational shortfalls that hinder law enforcement from achieving greater
success in preventing terrorist attacks is the difficulty in dynamically assessing individualized …

Extracting connectivity information in massive social networks is important for many
applications. Algorithms developed for undirected networks cannot be used with social …