Strategies for Investigating and Eliciting Information from Nuanced Attackers (SIENNA)
Abstract
This research was funded under the DARPA Active Social Engineering Defense (ASED) program. Our effort involved counter-engaging adversaries by gaining their trust and efficiently eliciting information from them, accomplished through our capability of socially coherent attacker investigations. SIENNA is a partial TA2 solution entailing the construction and deployment of a bot framework driven by conversational technology that members of our team originally devised in the context of videogames. When an attack is recognized, SIENNA will deploy a set of bots to engage and investigate the attackers. Each bot has a role, goals, and speaking style (its persona) selected by SIENNA to exploit what it knows so far about the nature and goals of each attacker. The bots true purpose is to engage, build trust, provide fake information, and most importantly to elicit information from the attacker and waste their time and resources.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 15, 2022
- Accession Number
- AD1197089
Entities
People
- Aaron Reed
- Adam Summerville
- Alexander Christner
- Bill Ferguson
- Brian Krisler
- Dustin Wright
- Ian Cook
- James Ryan
- Jordan Hashemi
- Katelyn Carino
- Matthew Vincent
- Nathan Lenz
- Zech Bertilson