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Found 10 papers, 1 papers with code
Detecting Asks in SE attacks: Impact of Linguistic and Structural Knowledge
Social engineers attempt to manipulate users into undertaking actions such as downloading malware by clicking links or providing access to money or sensitive information.
Adaptation of a Lexical Organization for Social Engineering Detection and Response Generation
We present a paradigm for extensible lexicon development based on Lexical Conceptual Structure to support social engineering detection and response generation.
The Panacea Threat Intelligence and Active Defense Platform
We describe Panacea, a system that supports natural language processing (NLP) components for active defenses against social engineering attacks.
Email Threat Detection Using Distinct Neural Network Approaches
This paper describes different approaches to detect malicious content in email interactions through a combination of machine learning and natural language processing tools.
Active Defense Against Social Engineering: The Case for Human Language Technology
We describe a system that supports natural language processing (NLP) components for active defenses against social engineering attacks.
Learning to Plan and Realize Separately for Open-Ended Dialogue Systems
Achieving true human-like ability to conduct a conversation remains an elusive goal for open-ended dialogue systems.
From Stance to Concern: Adaptation of Propositional Analysis to New Tasks and Domains
We develop a ground truth (GT) based on expert annotators and compare our concern detection output to GT, to yield 231% improvement in recall over baseline, with only a 10% loss in precision.
BeSt: The Belief and Sentiment Corpus
We present the BeSt corpus, which records cognitive state: who believes what (i. e., factuality), and who has what sentiment towards what.
