5 papers
Machine Learning-Based Graph Simplification for Symbolic Accelerators
Tiffany Yu, Rye Stahle-Smith, Darssan Eswaramoorthi +1
Graph-based accelerators have been widely adopted in symbolic data processing applications such as genomics, cybersecurity, and artificial intelligence. However, these systems ofte…
Hardware-Accelerated Line-Rate Bitstream Screening for Secure FPGA Reconfiguration
Rye Stahle-Smith, Carter Antley, Jason D. Bakos +1
As Field-Programmable Gate Arrays (FPGAs) scale in multi-tenant cloud and edge-AI environments, the configuration bitstream has become a critical, yet opaque, security boundary. Ex…
Real-time ML-based Defense Against Malicious Payload in Reconfigurable Embedded Systems
Rye Stahle-Smith, Rasha Karakchi
The growing use of FPGAs in reconfigurable systems introducessecurity risks through malicious bitstreams that could cause denial-of-service (DoS), data leakage, or covert attacks.…
ML-Enhanced AES Anomaly Detection for Real-Time Embedded Security
Nishant Chinnasami, Rye Stahle-Smith, Rasha Karakchi
Advanced Encryption Standard (AES) is a widely adopted cryptographic algorithm, yet its practical implementations remain susceptible to side-channel and fault injection attacks. In…
Toward a Lightweight, Scalable, and Parallel Secure Encryption Engine
Rasha Karakchi, Rye Stahle-Smith, Nishant Chinnasami +1
The exponential growth of Internet of Things (IoT) applications has intensified the demand for efficient, high-throughput, and energy-efficient data processing at the edge. Convent…