Mechanical engineering research team identifies methods to predict future cyberattacks | UTSA Today | UTSA

The current pervasive security threats motivated the UTSA researchers to develop and use cyber defense tools and sensors to monitor the threats and collect data, which can be used for various purposes in developing defense mechanisms.

“The current damages call for studies to understand and characterize cyberattacks from different perspectives and at various levels of intrusion. There are multiple variables that go into predicting the potential damage these attacks may cause as the aggressors get more sophisticated,” said Feng.

Using predictive situational awareness analysis, the team studied the distinctive nature of the attacks to accurately predict the threats that target and potentially harm personal devices, servers and networks.

“Most studies on cyberattacks focus on microscopic levels of abstractions, meaning how to defend against a particular attack,” Feng said. “Cyber attackers can successfully break in by exploiting a single weakness in a computer system.”

The study aims to analyze the macroscopic levels of abstractions.

“Such macroscopic-level studies are important because they would offer insights towards holistic solutions to defending cyberattacks,” he added.

Feng explains, “It’s very hard to single out the cause of each attack, however, we have big data with time series for each IP address (location). In this research, we use ‘causality’ when there are inter-relationships among IP addresses that have similar patterns of temporal features for identifying the threat.”