Cyber Threat Intelligence from Social Media

PhD Project details

Title: Cyber Threat Intelligence in the Age of Social Media and Online Platforms

The ongoing product digitization has revealed an alarming pattern of increasingly frequent, costly, and damaging cybersecurity incidents involving data breaches or, in the worst case, organizations targeted by ransomware campaigns that have halted production and demanded a ransom (e.g., JBS meat production and Colonial pipeline).

To combat the increasing cyber threats and mitigate the risks of potential security incidents, organizations need continuous access to information on software vulnerabilities, exploits, incidents, and available countermeasures. This helps them stay informed about emerging cyber threats that could endanger their products and assets. This information, known as “threat intelligence,” is actively shared in open-source documents and social media platforms. However, the sheer volume and heterogeneous social media data present significant challenges for security analysts to process and analyze manually. There is an urgent need to automate this process with machine learning systems.

This project aims to develop an effective machine learning framework to automate the data processing pipeline for cyber threat intelligence and create solutions that will assist security professionals in uncovering useful insights, patterns, and trends from large databases. These insights will aid in identifying risks associated with cyber threats. The outcome will be highly beneficial for cybersecurity community, enabling them to make better data-backed decisions and transform the current reactive cyber defense into a proactive cyber defense.

Supervisory team:

Prof. Richi Nayak,  Dr Md Abul Bashar, Dr Mahinthan Chandramohan