On the Impact of Entropy-Based Features

Network anomaly detection is increasingly challenging due to the growing diversity and variability of traffic patterns, which are not always well captured by traditional statistical features. In this work, we explore the use of entropy as an additional feature to support supervised network traffi...

HilEnT: Hilbert, Entropy Transformed Image Based Malware Detection

With the increasing threat of malware across various software related domains, malware detection and classification is critical to determine the response actions. Different strategies have been adopted to address the challenge of malware detection. With the advent of deep learning techniques,...

Leveraging Large Language Models for SQL Behavior-Based Database Intrusion Detection

Database systems are extensively used to store critical data across various domains. However, the frequency of abnormal database access behaviors, such as database intrusion by internal and external attacks, continues to rise. Internal masqueraders often have greater organizational knowledge,...

Reverse Engineering the Analyst: Building Machine Learning Models for the SOC

Many cyber incidents can be traced back to an original alert that was either missed or ignored by the Security Operations Center SOC or Incident Response IR team. While most analysts and SOCs are vigilant and responsive, the fact is they are often overwhelmed with alerts. If a SOC is unable to...