This research introduces a comprehensive framework for identifying and classifying deceptive patterns in user interfaces that manipulate users into unintended decisions.

• Develops an expanded taxonomy of deceptive patterns specifically from security and privacy perspectives
• Presents DPGuard, a novel tool for automated detection of manipulative UI elements
• Demonstrates practical detection capabilities through real-world case studies
• Provides actionable insights on security implications of deceptive designs

This work matters for security professionals because it offers systematic methods to identify and mitigate user manipulation tactics that can compromise security postures and privacy protections.

50 Shades of Deceptive Patterns: A Unified Taxonomy, Multimodal Detection, and Security Implications