Mukherjee, ShibnathChen, ZhiyuanGangopadhyay, AryyaRussell, Stephen2025-06-052025-06-05http://hdl.handle.net/11603/38583Face recognition technology has received much attention due to its application in defense and crime prevention. In such applications, there is great need to incorporate face recognition technologies onto mobile devices to allow onthe-spot field usage. However there are four major problems that need to be solved, namely the limited storage and processing power of the mobile device, connection instability, security and privacy concerns, and limited network bandwidth. Existing methods do not solve all the problems. This paper addresses all of the above problems holistically by proposing a novel approach. The core of the approach is a DCT-based compression method. This method has high compression ratio such that the compressed image database can be easily stored at a mobile device. Further, face recognition algorithms can be run directly on the compressed database without decompression, which enables on-the-spot field usage. The overhead of network transfer is also greatly reduced due to compression. The security and privacy issue is addressed by pruning most DCT coefficients of images and by a random permutation protocol. As a result, the reconstructed images are not visually recognizable even if the permutation is known. Additional security can also be provided by encrypting the coefficients for network transfer. The system has been implemented on a commercially available general purpose PDA-phone and experimental results demonstrate the potential of the proposed solution.6 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.UMBC Mobile, Pervasive and Sensor Computing Lab (MPSC Lab)UMBC Cybersecurity InstituteUMBC Accelerated Cognitive Cybersecurity LaboratoryUMBC Center for CybersecurityUMBC Accelerated Cognitive Cybersecurity LaboratoryText