Understanding Cybersecurity Threat Trends Through Dynamic Topic Modeling

Cybersecurity threats continue to increase and are impacting almost all aspects of modern life. Being aware how vulnerabilities their exploits changing gives helpful insights into combating new threats. Applying dynamic topic modeling a time-stamped cybersecurity document collection shows the significance details concepts found in them evolving. We correlate two different temporal corpora, one with reports about specific other research-oriented papers on represent documents, concepts, data semantic knowledge graph support integration, inference, discovery. A critical insight discovering through is seeding domain guide process. use Wikipedia provide basis for performing concept phrase extraction show using those phrases improves quality models. Researchers can query resulting reveal important relations trends. This work novel because it uses topics as bridge relate documents across corpora over time.