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Sy-Yen Kuo

Publications and source records attributed to Sy-Yen Kuo.

22 records · Page 2Linked to original sources

Multi-modal Bifurcated Network for Depth Guided Image Relighting

Image relighting aims to recalibrate the illumination setting in an image. In this paper, we propose a deep learning-based method called multi-modal bifurcated network (MBNet) for depth guided image relighting. That is, given an image and the corresponding depth maps, a new image with the given illuminant angle and color temperature is generated by our network. This model extracts the image and the depth features by the bifurcated network in the encoder. To use the two features effectively, we adopt the dynamic dilated pyramid modules in the decoder. Moreover, to increase the variety of training data, we propose a novel data process pipeline to increase the number of the training data. Experiments conducted on the VIDIT dataset show that the proposed solution obtains the \textbf{1}$^{st}$ place in terms of SSIM and PMS in the NTIRE 2021 Depth Guide One-to-one Relighting Challenge.

cs.CV↗

Fault-tolerant Operations for Universal Blind Quantum Computation

Blind quantum computation is an appealing use of quantum information technology because it can conceal both the client's data and the algorithm itself from the server. However, problems need to be solved in the practical use of blind quantum computation and fault-tolerance is a major challenge. On an example circuit, the computational cost measured in T gates executed by the client is 97 times more than performing the original computation directly, without using the server, even before applying error correction. (The client still benefits due to drastically reduced memory requirements.) Broadbent et al. proposed running error correction over blind computation, but our first protocol applies one layer of Steane's [[7,1,3]] code underneath instead. This protocol has better fault tolerance, but still results in a substantial overhead. We propose another protocol to reduce the client's computational load by transferring the qubit preparation to the server. For each logical qubit used in the computation, the client is only required to receive eight logical qubits via teleportation then buffer two logical qubits before returning one. This protocol also protects the client's fault-tolerant preparation of logical qubits from a side-channel attack.

quant-ph↗

Secure Multidimensional Queries in Tiered Sensor Networks

In this paper, aiming at securing range query, top-k query, and skyline query in tiered sensor networks, we propose the Secure Range Query (SRQ), Secure Top-$k$ Query (STQ), and Secure Skyline Query (SSQ) schemes, respectively. In particular, SRQ, by using our proposed \emph{prime aggregation} technique, has the lowest communication overhead among prior works, while STQ and SSQ, to our knowledge, are the first proposals in tiered sensor networks for securing top-$k$ and skyline queries, respectively. Moreover, the relatively unexplored issue of the security impact of sensor node compromises on multidimensional queries is studied; two attacks incurred from the sensor node compromises, \emph{collusion attack} and \emph{false-incrimination attack}, are investigated in this paper. After developing a novel technique called \emph{subtree sampling}, we also explore methods of efficiently mitigating the threat of sensor node compromises. Performance analyses regarding the probability for detecting incomplete query-results and communication cost of the proposed schemes are also studied.

cs.NI↗

Constrained Function Based En-Route Filtering for Sensor Networks

Sensor networks are vulnerable to \emph{false data injection attack} and \emph{path-based DoS} (PDoS) attack. While conventional authentication schemes are insufficient for solving these security conflicts, an \emph{en-route filtering} scheme acts as a defense against these two attacks. To construct an efficient en-route filtering scheme, this paper first presents a Constrained Function based message Authentication (CFA) scheme, which can be thought of as a hash function directly supporting the en-route filtering functionality. Together with the \emph{redundancy property} of sensor networks, which means that an event can be simultaneously observed by multiple sensor nodes, the devised CFA scheme is used to construct a CFA-based en-route filtering (CFAEF) scheme. In contrast to most of the existing methods, which rely on complicated security associations among sensor nodes, our design, which directly exploits an en-route filtering hash function, appears to be novel. We examine the CFA and CFAEF schemes from both the theoretical and numerical aspects to demonstrate their efficiency and effectiveness.

cs.NI↗