© 2018 IEEE. This paper presents a framework for detection and classification of cyber threat indicators in the Twitter stream. Contrary to the bulk of similar proposals that rely on manually-designed heuristics and keywordbased filtering of tweets, our framework provides a data-driven approach for modeling and classification of tweets that are related to cybersecurity events. We present a cascaded Convolutional Neural Network (CNN) architecture, comprised of a binary classifier for detection of cyber-related tweets, and a multi-class model for the classification of cyber-related tweets into multiple types of cyber threats. Furthermore, we present an open-source dataset of 21000 annotated cyber-related tweets to facilitate the validation and further research in this area.
|Original language||American English|
|Number of pages||4501|
|State||Published - 22 Jan 2019|
|Event||Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 - |
Duration: 22 Jan 2019 → …
|Conference||Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018|
|Period||22/01/19 → …|