Dr. Seema G. Aarella

Secure Data Collaboration for Distributed Edge-AI Systems

Abstract:

Edge-AI deployments increasingly rely on multi-device collaboration, yet shared learning and decision-making introduce new security and trust challenges. This talk outlines a secure collaboration model enabling edge devices to exchange intelligence while preserving data integrity, privacy, and device authenticity. Using a blend of hardware trust anchors, lightweight encryption, and federated trust policies, the approach ensures that sensitive data never leaves the device unprotected.
Attendees will learn how secure aggregation, feature-level data exchange, and tamper-proof device identity enable trusted AI inference across drones, robots, sensors, and smart-city infrastructure. Real-world benchmarks and reference architectures will illustrate how to deploy resilient, cooperative edge-AI networks resistant to poisoning, spoofing, and data manipulation attacks. Participants will leave with practical strategies for building secure, privacy-preserving, and scalable distributed edge-AI systems.

Profile:

Dr. Seema G. Aarella is a researcher and educator specializing in cybersecurity, edge computing, and hardware-assisted security. She serves as a faculty member in the Department of Computer Science at Austin College, Texas, where she leads research on secure, energy-efficient authentication frameworks for distributed and resource-constrained systems. Her work focuses on integrating Physically Unclonable Functions (PUFs) with lightweight cryptographic protocols to safeguard device identity and data integrity in collaborative edge computing environments. Dr. Aarella has published in leading journals and conferences, contributing to advancements in secure authentication, IoT security, and privacy-preserving communication. With a strong commitment to applied research, she combines theoretical rigor with practical implementation, delivering solutions that are scalable, resilient to cyberattacks, and optimized for real-world deployment in smart cities, industrial IoT, and mission-critical systems.