OpenAlex
metadata only
CC BY 4.0
Digital deception: generative artificial intelligence in social engineering and phishing
Abstract The advancement of Artificial Intelligence (AI) and Machine Learning (ML) has profound implications for both the utility and security of our digital interactions. This paper investigates the transformative role of Generative AI in Social Engineering (SE) attacks. We conduct a systematic rev
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Engineered Persuasion: Evaluating Personalized Pretexts in LLM-Generated Spear Phishing#927701
- Editorial: Artificial Intelligence-Driven Information Security and Privacy Enhancement Technologies#990791
- An Efficient Privacy-Enhancing Cross-Silo Federated Learning and Applications for False Data Injection Attack Detection in Smart Grids#177297
- The breach of trust#65770
- Identity-Aware Vision-Language Model for Explainable Face Forgery Detection#793423
Record · ID 1135317
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive