Machine Learning on the Edge: Performance and Security Evaluation of CNN Implementations in Embedded Systems

Authors

• Krista Stacey, University of South AlabamaFollow

Files

Description

Embedded systems increasingly integrate Machine Learning (ML) for real-time decision-making across loT, infrastructure, and critical systems. However, ecosystems differ significantly in: Latency, Throughput, Energy use, Accuracy of Models Security exposure. Most research evaluates performance or security, not both together. There is a need for a unified cross-platform performance-security evaluation framework

Publication Date

3-2026

Department

Computer Science

Disciplines

Computer Sciences

Recommended Citation

Stacey, Krista, "Machine Learning on the Edge: Performance and Security Evaluation of CNN Implementations in Embedded Systems" (2026). Shelby Hall Graduate Research Forum Posters. 65.
https://jagworks.southalabama.edu/southalabama-shgrf-posters/65