Personalized AutoNomous Agents Countering Social Engineering Attacks (PANACEA)
Abstract
We are reporting on the development of PANACEA, 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. PANACEA 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 PANACEA 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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 31, 2020
- Accession Number
- AD1143840
Entities
People
- Adam Dalton
- Alan Zemel
- Amir Masoumzadeh
- Bonnie J. Door
- Ehab Al-Shaer
- Samira Shaikh
- Tomek Strzalkowski