Shape and Substance: Dual-Layer Side-Channel Attacks on Local Vision-Language Models
Shape and Substance: Dual-Layer Side-Channel Attacks on Local Vision-Language Models explores Exploit algorithmic side-channels in on-device Vision-Language Models to infer sensitive user contexts, enabling proactive security measures for Edge AI.. Commercial viability score: 7/10 in Edge AI Security.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Startup Essentials
Estimated $10K - $14K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisRobustness of Vision Language Models Against Split-Image Harmful Input AttacksViability: 5.0
- Builds On ThisVision-Language Models on the Edge for Real-Time Robotic PerceptionViability: 6.0
- Builds On ThisRisk Awareness Injection: Calibrating Vision-Language Models for Safety without Compromising UtilityViability: 6.0
- Builds On ThisJailbreaks on Vision Language Model via Multimodal ReasoningViability: 3.0
- Prior WorkDP^2-VL: Private Photo Dataset Protection by Data Poisoning for Vision-Language Models