Detection of Cyber Security Threats through Social Media Platforms

The social media platforms are an important source of information for various situations, such as emergencies, disasters and security threats. This work presents a methodology based on text-mining that uses Twitter as source for the realtime detection of information related to cyber security threats. The methodology is supported by a tool that is lightweight in terms of computational resources, provides various customization options, it is integrated with a flexible notification system, and provides a user friendly interface. Evaluation results show that the efficacy of the tool in terms of the identification of relevant tweets reaches 73%.