EdgeCrypt Tracker: Object Tracking With Differential Encryption for IoAAV Surveillance
Karthik Thiyagarajan, Issam Hammad, Rongxing Lu · IEEE Internet of Things Journal · 2024
This article proposes EdgeCrypt Tracker, an object-tracking algorithm combined with differential encryption to provide better accuracy and runtime efficiency for battery-operated Internet of Autonomous Aerial Vehicles (IoAAV). Specifically, EdgeCrypt Tracker operates directly on high-efficiency video coding (HEVC) and has three stages: 1) preprocessing; 2) object tracking; and 3) differential encryption. The preprocessing stage separates intra frames and removes artificial camera motion caused by camera movement from inter frames. Next, the object tracking stage utilizes a hybrid neural network, combining a single-shot multibox detector (SSD) network with a MobileNetV3 backbone that processes intra coded blocks and a fast gated recurrent neural network (FastGRNN) network that processes inter coded blocks. Finally, the tracked information is passed to the differential encryption stage, which encrypts all syntax elements within moving objects and alternate syntax elements related to the background. Experimental results demonstrate that EdgeCrypt Tracker achieves an average object tracking accuracy of 92%, real-time inference with a 35% lower encryption overhead compared to state-of-the-art methods. This work demonstrates the potential of integrating object tracking and encryption within video compression for secure, efficient AAV-based surveillance.