Integral Attacks on Some Lightweight Block Ciphers

( Shiqiang Zhu ),( Gaoli Wang ),( Yu He ),( Haifeng Qian ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.11

At EUROCRYPT 2015, Todo proposed a new technique named division property, and it is a powerful technique to find integral distinguishers. The original division property is also named word-based division property. Later, Todo and Morii once again proposed a new technique named the bit-based division property at FSE 2016 and find more rounds integral distinguisher for SIMON-32. There are two basic approaches currently being adopted in researches under the bit-based division property. One is conventional bit-based division property (CBDP), the other is bit-based division property using three-subset (BDPT). Particularly, BDPT is more powerful than CBDP. In this paper, we use Boolean Satisfiability Problem (SAT)-aided cryptanalysis to search integral distinguishers. We conduct experiments on SIMON-32/-48/-64/-96, SIMON (102)-32/-48/-64, SIMECK-32/-48/-64, LBlock, GIFT and Khudra to prove the efficiency of our method. For SIMON (102)-32/-48/-64, we can determine some bits are odd, while these bits can only be determined as constant in the previous result. For GIFT, more balanced (zero-sum) bits can be found. For LBlock, we can find some other new integral distinguishers. For Khudra, we obtain two 9-round integral distinguishers. For other ciphers, we can find the same integral distinguishers as before.

A Heterogeneous IoT Node Authentication Scheme Based on Hybrid Blockchain and Trust Value

( Shiqiang Zhang ),( Yang Cao ),( Zhenhu Ning ),( Fei Xue ),( Dongzhi Cao ),( Yongli Yang ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.9

Node identity authentication is an essential means to ensure the security of the Internet of Things. Existing blockchain-based IoT node authentication schemes have many problems. A heterogeneous IoT node authentication scheme based on an improved hybrid blockchain is proposed. Firstly, the hybrid blockchain model is designed to make the blockchain and IoT environment more compatible. Then the proxy node selection mechanism is intended to establish a bridge between the ordinary IoT node and the blockchain, building by calculating the trust value between nodes. Finally, based on the improved hybrid blockchain, the node authentication scheme of the model and proxy node selection mechanism establishes a secure connection for communication between nodes. Safety and performance analysis shows proper safety and performance.

ZnO/NiO nanofibers prepared by electrostatic spinning for rapid ammonia detection at room temperature

Shiqiang Xu,Junhe Wang,Hongying Lin,Rongchao Li,Yongqiang Cheng,Shengbo Sang,Kai Zhuo 대한금속·재료학회 2022 ELECTRONIC MATERIALS LETTERS Vol.18 No.6

ZnO/NiO heterojunction nanofibers were synthesized by an electrostatic spinning technique in thiswork. The morphologies, crystal structures, and compositional features of the ZnO/NiO nanofiberswere analyzed by SEM, TEM, XRD, and EDS characterization. ZnO/NiO nanofibers with Zn contentsof 37.5 at% showed a 46% response to 300-ppm ammonia gas at room temperature (25 ± 1 ℃;56 ± 3% RH), with fast response and recovery behavior (100 s /25 s). The existence of p-n heterojunctionson the surface of ZnO/NiO nanofibers, as well as surface ionic conduction, improved the responseto ammonia gas in a synergistic manner.

Footbridge Serviceability Analysis: From System Identification to Tuned Mass Damper Implementation

Shiqiang Qin,Yun-Lai Zhou,Juntao Kang 대한토목학회 2019 KSCE Journal of Civil Engineering Vol.23 No.2

Footbridges usually suffer from vibrations induced by the actions of pedestrians, which calls for various control measures to improve the serviceability. This study described the dynamic analysis and Tuned Mass Damper (TMD) implementation for a singlepylon cable-stayed footbridge scaled model, aimed at providing an experimental case study regarding of vibration control design of slender structures. A scaled model for the real footbridge was designed based on similarity principles. Then, the dynamic behavior of the footbridge was assessed by ambient vibration tests. The natural frequencies and mode shapes were identified from operational vibration measurements by covariance-driven stochastic subspace identification algorithm. The frequency of first vertical bending modes is 2.10 Hz, falling into the human walking frequency range [1.6, 2.4] Hz. Therefore, the footbridge needs vibration control to improve its serviceability. Finally, a self-made TMD using lead, spring and oil buffer was implemented on the scaled model of the footbridge. The laboratory forced vibration test was employed to illustrate the effectiveness of the TMD. By installing TMD, the acceleration response at mid-span of the footbridge was remarkably reduced. The study could provide meaningful reference for vibration control design of the full-scale footbridge.

Model Updating in Complex Bridge Structures using Kriging Model Ensemble with Genetic Algorithm

Shiqiang Qin,Yun-Lai Zhou,Hongyou Cao,Magd Abdel Wahab 대한토목학회 2018 KSCE Journal of Civil Engineering Vol.22 No.9

Computational cost reduction and the best solution seeking are frequently encountered during model updating for complex structures. In this study, a hybrid algorithm using kriging model and genetic algorithms (GAs) is proposed for updating the Finite Element (FE) model of complex bridge structures employing both static and dynamic experimental measurements. The kriging model is first established to approximate the implicit relationship between structural parameters and responses, serving as a surrogate model for complex FE model when deriving analytical responses. An objective function is later defined based on the residual between analytical response values and experimental measured ones. GAs are finally employed to find the best solution by searching on the whole design space of updating parameters selected based on a sensitivity analysis. To verify the proposed algorithm, Caiyuanba Yangtze River Bridge, a double decked of roadway and light railway bridge with a main span of 420 m is used. Both frequencies and displacements predicted by the updated model are more close to experimental measured ones. The results show that the kriging surrogate model has good accuracy in predicting response and can be used as a surrogate model to reduce computational cost, and GAs provide a higher chance to obtain global best solution.

Model of Online Food Delivery System Services and Restaurant Performance: A Case Study of China

Shiqiang Yan,Sidah Idris,Syarifah Hanum Ali People & Global Business Association 2024 Global Business and Finance Review Vol.29 No.3

A real-time multiple vehicle tracking method for traffic congestion identification

( Xiaoyu Zhang ),( Shiqiang Hu ),( Huanlong Zhang ),( Xing Hu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.6

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

Optimization of Hot Working Parameters of As-Forged Nitinol 60 Shape Memory Alloy Using Processing Maps

Xiaoyong Shu,Shiqiang Lu,Kelu Wang,Guifa Li 대한금속·재료학회 2015 METALS AND MATERIALS International Vol.21 No.4

The hot deformation behavior of as-forged Nitinol 60 alloy (60 wt% Ni, 40 wt% Ti) was studied over the ranges of temperature, 650-850 °C, and strain rate, 0.01-1 s-1, using isothermal constant strain rate compression tests in a Gleeble-3500 simulator. The processing maps, based on the dynamic materials model, were developed to optimize the hot working parameters. The results show that the deformation parameters have a marked effect on the power dissipation efficiency and the instability parameter. A single unstable region (650-775 °C, 0.037-1 s-1), associated with flow localization and/or adiabatic shear, is detected from the processing map. This should be avoided in hot working process. The optimized hot working conditions correspond to 680-790 °C, 0.01- 0.025 s-1 with peak efficiency of 0.45 at 720 °C, 0.01 s-1, and 820-850 °C, 0.1-1 s-1 with peak efficiency of 0.5 at 850 °C, 1 s-1. Microstructure observations indicate that the main deformation mechanism of optimized domains involves dynamic recrystallization.

Exploiting Chaotic Feature Vector for Dynamic Textures Recognition

( Yong Wang ),( Shiqiang Hu ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.11

This paper investigates the description ability of chaotic feature vector to dynamic textures. First a chaotic feature and other features are calculated from each pixel intensity series. Then these features are combined to a chaotic feature vector. Therefore a video is modeled as a feature vector matrix. Next by the aid of bag of words framework, we explore the representation ability of the proposed chaotic feature vector. Finally we investigate recognition rate between different combinations of chaotic features. Experimental results show the merit of chaotic feature vector for pixel intensity series representation.

Chaotic Features for Traffic Video Classification

( Yong Wang ),( Shiqiang Hu ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.8

This paper proposes a novel framework for traffic video classification based on chaotic features. First, each pixel intensity series in the video is modeled as a time series. Second, the chaos theory is employed to generate chaotic features. Each video is then represented by a feature vector matrix. Third, the mean shift clustering algorithm is used to cluster the feature vectors. Finally, the earth mover`s distance (EMD) is employed to obtain a distance matrix by comparing the similarity based on the segmentation results. The distance matrix is transformed into a matching matrix, which is evaluated in the classification task. Experimental results show good traffic video classification performance, with robustness to environmental conditions, such as occlusions and variable lighting.