| Title | Generating Real Time Cyber Situational Awareness Information Through Social Media Data Mining |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Rodriguez, Ariel, Okamura, Koji |
| Conference Name | 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC) |
| Keywords | composability, Cyber Attacks, cyber risk, cyber situational awareness, cyber situational awareness information, cyber threat landscape, cyberattack, cybersecurity, cybersecurity tweet dataset, data aggregation, Data analysis, data analytics techniques, data mining, information retrieval, Internet, machine learning, Metrics, pubcrawl, ransomware, resilience, Resiliency, security of data, security relevant information retrieval, sentiment analysis, situational awareness, social media, social media data mining, social networking (online), social networking site Twitter.com, text mining |
| Abstract | With the rise of the internet many new data sources have emerged that can be used to help us gain insights into the cyber threat landscape and can allow us to better prepare for cyber attacks before they happen. With this in mind, we present an end to end real time cyber situational awareness system which aims to efficiently retrieve security relevant information from the social networking site Twitter.com. This system classifies and aggregates the data retrieved and provides real time cyber situational awareness information based on sentiment analysis and data analytics techniques. This research will assist security analysts to evaluate the level of cyber risk in their organization and proactively take actions to plan and prepare for potential attacks before they happen as well as contribute to the field through a cybersecurity tweet dataset. |
| DOI | 10.1109/COMPSAC.2019.10256 |
| Citation Key | rodriguez_generating_2019 |
Generating Real Time Cyber Situational Awareness Information Through Social Media Data Mining