ABSTRACT
As more activities are moving to digital platforms in the age of COVID-19 pandemic, cyber security becomes an increasingly critical issue. Thus, understanding how the recent pandemic has changed the Singapore cyber security landscape gains importance in unearthing potential weaknesses present in the infrastructure, which unfortunately is very challenging. In this paper, we propose, LionKeeper, an automated system for discovering the cyber security dynamics timely in Lion City - Singapore through social media data analytics. In particular, considering that the social media platforms like news websites provide immediate reports on local and global cybercrime incidents, in our system, we first crawl all the news articles from mainstream news sources such as CNA and Strait Times. Then, we analyze these news articles to identify those related to cybercrimes, the date and the location of cybercrime incidents, and employ a scoring system to detect the cyber security attack types and their significance. Additionally, based on the extracted information, we perform various analyses to generate meaningful insights for users to understand the cyber attack landscape dynamics before and during the COVID-19 pandemic automatically and intelligently. To the best of our knowledge, this is the first automated solution to understand the Singapore cyber landscape via social media analytics. © 2021 IEEE.