%0 Conference Proceedings %T Active Defense Against Social Engineering: The Case for Human Language Technology %A Dalton, Adam %A Aghaei, Ehsan %A Al-Shaer, Ehab %A Bhatia, Archna %A Castillo, Esteban %A Cheng, Zhuo %A Dhaduvai, Sreekar %A Duan, Qi %A Hebenstreit, Bryanna %A Islam, Md Mazharul %A Karimi, Younes %A Masoumzadeh, Amir %A Mather, Brodie %A Santhanam, Sashank %A Shaikh, Samira %A Zemel, Alan %A Strzalkowski, Tomek %A Dorr, Bonnie J. %Y Bhatia, Archna %Y Shaikh, Samira %S Proceedings for the First International Workshop on Social Threats in Online Conversations: Understanding and Management %D 2020 %8 May %I European Language Resources Association %C Marseille, France %@ 979-10-95546-39-9 %G English %F dalton-etal-2020-active %X We describe a system that supports natural language processing (NLP) components for active defenses against social engineering attacks. We deploy a pipeline of human language technology, including Ask and Framing Detection, Named Entity Recognition, Dialogue Engineering, and Stylometry. The system processes modern message formats through a plug-in architecture to accommodate innovative approaches for message analysis, knowledge representation and dialogue generation. The novelty of the system is that it uses NLP for cyber defense and engages the attacker using bots to elicit evidence to attribute to the attacker and to waste the attacker’s time and resources. %U https://aclanthology.org/2020.stoc-1.1 %P 1-8