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Articles 1 - 3 of 3
Full-Text Articles in Databases and Information Systems
Deepmag+ : Sniffing Mobile Apps In Magnetic Field Through Deep Learning, Rui Ning, Cong Wang, Chunsheng Xin, Jiang Li, Hongyi Wu
Deepmag+ : Sniffing Mobile Apps In Magnetic Field Through Deep Learning, Rui Ning, Cong Wang, Chunsheng Xin, Jiang Li, Hongyi Wu
Electrical & Computer Engineering Faculty Publications
This paper reports a new side-channel attack to smartphones using the unrestricted magnetic sensor data. We demonstrate that attackers can effectively infer the Apps being used on a smartphone with an accuracy of over 80%, through training a deep Convolutional Neural Networks (CNN). Various signal processing strategies have been studied for feature extractions, including a tempogram based scheme. Moreover, by further exploiting the unrestricted motion sensor to cluster magnetometer data, the sniffing accuracy can increase to as high as 98%. To mitigate such attacks, we propose a noise injection scheme that can effectively reduce the App sniffing accuracy to only …
2d Face Database Diversification Based On 3d Face Modeling, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Manuel Filipe Costa (Ed.)
2d Face Database Diversification Based On 3d Face Modeling, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Manuel Filipe Costa (Ed.)
Electrical & Computer Engineering Faculty Publications
Pose and illumination are identified as major problems in 2D face recognition (FR). It has been theoretically proven that the more diversified instances in the training phase, the more accurate and adaptable the FR system appears to be. Based on this common awareness, researchers have developed a large number of photographic face databases to meet the demand for data training purposes. In this paper, we propose a novel scheme for 2D face database diversification based on 3D face modeling and computer graphics techniques, which supplies augmented variances of pose and illumination. Based on the existing samples from identical individuals of …
Special Issue On Information Dissemination And New Services In P2p Systems, Min Song, Sachin Shetty, Wenbin Jiang, E. K. Park
Special Issue On Information Dissemination And New Services In P2p Systems, Min Song, Sachin Shetty, Wenbin Jiang, E. K. Park
Electrical & Computer Engineering Faculty Publications
Information dissemination is an important P2P application that has received considerable research attention in recent years. P2P information dissemination systems range from simple file sharing applications to more complex systems that allows users to securely and efficiently publish, organize, index, search, update and retrieve data in a distributed storage medium. For complex P2P information dissemination systems, there is a need for features which include security, anonymity, fairness, scalability, resource management, and organization capabilities. For effective information dissemination, following features of P2P systems and infrastructure need to be updated: distributed object location and routing mechanisms, novel approaches to content replication, caching …