Visible to the public Biblio

Filters: Author is Wu, Feng  [Clear All Filters]
2020-09-14
Wang, Lizhi, Xiong, Zhiwei, Huang, Hua, Shi, Guangming, Wu, Feng, Zeng, Wenjun.  2019.  High-Speed Hyperspectral Video Acquisition By Combining Nyquist and Compressive Sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence. 41:857–870.
We propose a novel hybrid imaging system to acquire 4D high-speed hyperspectral (HSHS) videos with high spatial and spectral resolution. The proposed system consists of two branches: one branch performs Nyquist sampling in the temporal dimension while integrating the whole spectrum, resulting in a high-frame-rate panchromatic video; the other branch performs compressive sampling in the spectral dimension with longer exposures, resulting in a low-frame-rate hyperspectral video. Owing to the high light throughput and complementary sampling, these two branches jointly provide reliable measurements for recovering the underlying HSHS video. Moreover, the panchromatic video can be used to learn an over-complete 3D dictionary to represent each band-wise video sparsely, thanks to the inherent structural similarity in the spectral dimension. Based on the joint measurements and the self-adaptive dictionary, we further propose a simultaneous spectral sparse (3S) model to reinforce the structural similarity across different bands and develop an efficient computational reconstruction algorithm to recover the HSHS video. Both simulation and hardware experiments validate the effectiveness of the proposed approach. To the best of our knowledge, this is the first time that hyperspectral videos can be acquired at a frame rate up to 100fps with commodity optical elements and under ordinary indoor illumination.
2020-05-11
Xue, Kaiping, Zhang, Xiang, Xia, Qiudong, Wei, David S.L., Yue, Hao, Wu, Feng.  2018.  SEAF: A Secure, Efficient and Accountable Access Control Framework for Information Centric Networking. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications. :2213–2221.
Information Centric Networking (ICN) has been regarded as an ideal architecture for the next-generation network to handle users' increasing demand for content delivery with in-network cache. While making better use of network resources and providing better delivery service, an effective access control mechanism is needed due to wide dissemination of contents. However, in the existing solutions, making cache-enabled routers or content providers authenticate users' requests causes high computation overhead and unnecessary delay. Also, straightforward utilization of advanced encryption algorithms increases the opportunities for DoS attacks. Besides, privacy protection and service accountability are rarely taken into account in this scenario. In this paper, we propose a secure, efficient, and accountable access control framework, called SEAF, for ICN, in which authentication is performed at the network edge to block unauthorized requests at the very beginning. We adopt group signature to achieve anonymous authentication, and use hash chain technique to greatly reduce the overhead when users make continuous requests for the same file. Furthermore, the content providers can affirm the service amount received from the network and extract feedback information from the signatures and hash chains. By formal security analysis and the comparison with related works, we show that SEAF achieves the expected security goals and possesses more useful features. The experimental results also demonstrate that our design is efficient for routers and content providers, and introduces only slight delay for users' content retrieval.