Ensuring Bidirectional Privacy on Wireless Split Inference Systems

• Published in: IEEE wireless communications Vol. 31; no. 5; pp. 134 - 141
• Main Authors: Sa, Chia-Che, Cheng, Li-Chen, Chung, Hsing-Huan, Chiu, Te-Chuan, Wang, Chih-Yu, Pang, Ai-Chun, Chen, Shang-Tse
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Cloud computing; Computational modeling; Containers; Data models; Data privacy; Edge computing; Image segmentation; Inference; Machine learning; Network latency; Partitioning; Privacy; Semantic segmentation; Servers; User experience; Wireless communication; Wireless communications

With the advances of machine learning, edge computing, and wireless communications, split inference has tracked more and more attention as a versatile inference paradigm. Split inference is essential to accelerate large-scale deep neural network (DNN) inference on resource-limited edge devices throu...