Researchers usually detect insider threats by analyzing user behavior. The time information
of user behavior is an important concern in internal threat detection. Existing works on …

The objective and universal nature of user behavior data make it the primary data for insider
threat detection. Existing solutions treat user behavior as atomic symbols and do not …

Insider threat detection has attracted a considerable attention from the researchers and
industries. Existing work mainly focused on applying machine-learning techniques to …

Insider threat makes enterprises or organizations suffer from the loss of property and the
negative influence of reputation. User behavior analysis is the mainstream method of insider …

Insider threat is an important cyber security issue for businesses and organizations. Existing
insider threat detection methods can be roughly divided into two categories, statistical …

Currently, more and more malicious insiders are making threats, and the detection of insider
threats is becoming more challenging. The malicious insider often uses legitimate access …

With the continuous advancement of enterprise digitization, insider threats have become
one of the primary cybersecurity concerns for organizations. Therefore, it is of great …

Insider threats on information security can become a burden for organizations. However,
outsider attacks have received more attention compared to insider attacks. Many …

At present, insider threat detection faces many challenges, such as imbalanced data sets,
the complexity of malicious behavior, high data dimension, and difficulty for manual analysis …

In view of the concealment and destructiveness of insider threats, to detect insider threats is
very important for protecting the security of enterprises and organizations. However, it is still …