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10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014

作者： Fu, Zhangjie Xin, Lin Wang, Jin Sun, Xingming School of Computer and Software and Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 China

ISBN: (纸本)9781479953905

Ciphertext-Policy Attribute-based Encryption (CP-ABE) is one of the most suitable technologies for data access control in cloud storage systems. This paper firstly presents the Attribute-based Encryption (ABE), secure deletion and secret-sharing schemes. Then we construct a CP-ABE model using secret-sharing methods to insure its security. At last, we propose an improved scheme on Data Access Control for Multi-Authority Cloud Storage Systems DAC-MACS to insure the security of the central authority (CA). © 2014 IEEE.

关键词： Access control

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A Dual-Chaining Watermark Scheme for Data Integrity Protection in Internet of Things

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computers, Materials & Continua 2019年第3期58卷 679-695页

作者： Baowei Wang Weiwen Kong Wei Li Neal NXiong Jiangsu Engineering Centre of Network Monitoring Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment TechnologySchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Engineering Research Center of Electronic Information and Control from Fujian Provincial Education Department Fuzhou350108China Department of Mathematics and Computer Science Northeastern State UniversityOklahomaUSA.

Chaining watermark is an effective way to verify the integrity of streaming data in wireless network environment,especially in resource-constrained sensor networks,such as the perception layer of Internet of Things ***,in all existing single chaining watermark schemes,how to ensure the synchronization between the data sender and the receiver is still an unsolved *** the synchronization points are attacked by the adversary,existing data integrity authentication schemes are difficult to work properly,and the false negative rate might be up to 50 *** the additional fixed group delimiters not only increase the data size,but are also easily detected by *** this paper,we propose an effective dual-chaining watermark scheme,called DCW,for data integrity protection in smart campus IoT *** proposed DCW scheme has the following three characteristics:(1)In order to authenticate the integrity of the data,fragile watermarks are generated and embedded into the data in a chaining way using dynamic grouping;(2)Instead of additional fixed group delimiters,chained watermark delimiters are proposed to synchronize the both transmission sides in case of the synchronization points are tampered;(3)To achieve lossless integrity authentication,a reversible watermarking technique is *** experimental results and security analysis can prove that the proposed DCW scheme is able to effectively authenticate the integrity of the data with free distortion at low cost in our smart meteorological Internet of Things system.

关键词： Dual-chaining reversible watermark integrity authentication Internet of things.

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A Method for Improving CNN-Based Image Recognition Using DCGAN

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computers, Materials & Continua 2018年第10期57卷 167-178页

作者： Wei Fang Feihong Zhang Victor S.Sheng Yewen Ding School of Computer&Software Jiangsu Engineering Center of Network MonitoringNanjing University of Information Science&TechnologyNanjing210044China State Key Lab.for Novel Software Technology Nanjing UniversityNanjing210023China Computer Science Department University of Central ArkansasConway AR72035USA

Image recognition has always been a hot research topic in the scientific community and *** emergence of convolutional neural networks(CNN)has made this technology turned into research focus on the field of computer vision,especially in image *** it makes the recognition result largely dependent on the number and quality of training ***,DCGAN has become a frontier method for generating images,sounds,and *** this paper,DCGAN is used to generate sample that is difficult to collect and proposed an efficient design method of generating *** combine DCGAN with CNN for the second *** DCGAN to generate samples and training in image recognition model,which based by *** method can enhance the classification model and effectively improve the accuracy of image *** the experiment,we used the radar profile as dataset for 4 categories and achieved satisfactory classification *** paper applies image recognition technology to the meteorological field.

关键词： DCGAN image recognition CNN samples

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Deep Learning for Object Detection:A Survey

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computer Systems Science & engineering 2021年第8期38卷 165-182页

作者： Jun Wang Tingjuan Zhang Yong Cheng Najla Al-Nabhan Science and Technology Industry Department Nanjing University of Information Science&Technology210044China School of Computer&Software Jiangsu Engineering Center of Network MonitoringNanjing University of Information Science&Technology210044China Department Computer Science King Saud UniversityRiyadhKSA

Object detection is one of the most important and challenging branches of computer vision,which has been widely applied in people s life,such as monitoring security,autonomous driving and so on,with the purpose of locating instances of semantic objects of a certain *** the rapid development of deep learning algorithms for detection tasks,the performance of object detectors has been greatly *** order to understand the main development status of target detection,a comprehensive literature review of target detection and an overall discussion of the works closely related to it are presented in this *** paper various object detection methods,including one-stage and two-stage detectors,are systematically summarized,and the datasets and evaluation criteria used in object detection are *** addition,the development of object detection technology is ***,based on the understanding of the current development of target detection,we discuss the main research directions in the future.

关键词： Object detection convolutional neural network computer vision

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Efficient sampling methods for characterizing POIs on maps based on road networks

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Frontiers of computer Science 2018年第3期12卷 582-592页

作者： Ziting ZHOU Pengpeng ZHAO Victor S. SHENG Jiajie XU Zhixu LI Jian WU Zhiming CUI School of Computer Science and Technology Soochow University Suzhou 215006 China Department of Computer Science University of Central Arkansas Conway AR 72035 USA Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology Nanjing 210044 China

With the rapid development of location-based services, a particularly important aspect of start-up marketing research is to explore and characterize points of interest （PoIs） such as restaurants and hotels on maps. However, due to the lack of direct access to PoI databases, it is necessary to rely on existing APIs to query Pols within a region and calculate PoI statistics. Unfortunately, public APIs generally im- pose a limit on the maximum number of queries. Therefore, we propose effective and efficient sampling methods based on road networks to sample PoIs on maps and provide unbiased estimators for calculating PoI statistics. In general, the more intense the roads, the denser the distribution of PoIs is within a region. Experimental results show that compared with state-of-the-art methods, our sampling methods improve the efficiency of aggregate statistical estimations.

关键词： sampling aggregate statistical estimation roadnetworks

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Analysis and Improvement of Steganography Protocol Based on Bell States in Noise Environment

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computers, Materials & Continua 2019年第5期59卷 607-624页

作者： Zhiguo Qu Shengyao Wu Wenjie Liu Xiaojun Wang Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and TechnologyNanjing210044China School of Computer&Software Nanjing University of Information Science and TechnologyNanjing210044China School of Electronic Engineering Dublin City UniversityDublinIreland

In the field of quantum communication,quantum steganography is an important branch of quantum information *** a realistic quantum communication system,quantum noises are unavoidable and will seriously impact the safety and reliability of the quantum steganographic ***,it is very important to analyze the influence of noise on the quantum steganography protocol and how to reduce the effect of *** paper takes the quantum steganography protocol proposed in 2010 as an example to analyze the effects of noises on information qubits and secret message qubits in the four primary quantum noise *** results show that when the noise factor of one quantum channel noise is known,the size of the noise factor of the other quantum channel can be adjusted accordingly,such as artificially applying noise,so that the influence of noises on the protocol is *** addition,this paper also proposes a method of improving the efficiency of the steganographic protocol in a noisy environment.

关键词： Quantum steganography quantum noise noise channel fidelity efficiency

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An Application Review of Artificial Intelligence in Prevention and Cure of COVID-19 Pandemic

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computers, Materials & Continua 2020年第10期65卷 743-760页

作者： Peipeng Yu Zhihua Xia Jianwei Fei Sunil Kumar Jha Engineering Research Center of Digital Forensics Ministry of EducationSchool of Computer and SoftwareJiangsu Engineering Center of Network MonitoringJiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment TechnologyNanjing University of Information Science&TechnologyNanjing210044China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszow Voivodeship100031Poland

Coronaviruses are a well-known family of viruses that can infect humans or ***,the new coronavirus(COVID-19)has spread *** countries in the world are working hard to control the coronavirus ***,many countries are faced with a lack of medical equipment and an insufficient number of medical personnel because of the limitations of the medical system,which leads to the mass spread of *** a powerful tool,artificial intelligence(AI)has been successfully applied to solve various complex problems ranging from big data analysis to computer *** the process of epidemic control,many algorithms are proposed to solve problems in various fields of medical treatment,which is able to reduce the workload of the medical *** to excellent learning ability,AI has played an important role in drug development,epidemic forecast,and clinical *** research provides a comprehensive overview of relevant research on AI during the outbreak and helps to develop new and more powerful methods to deal with the current pandemic.

关键词： Artificial intelligence COVID-19 medical applications clinical diagnosis

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A New Sequential Image Prediction Method Based on LSTM and DCGAN

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computers, Materials & Continua 2020年第7期64卷 217-231页

作者： Wei Fang Feihong Zhang Yewen Ding Jack Sheng School of Computer&Software Jiangsu Engineering Center of Network MonitoringNanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing210023China Department of Economics FinanceInsurance and Risk Management University of Central ArkansasConway72035USA

Image recognition technology is an important field of artificial *** with the development of machine learning technology in recent years,it has great researches value and commercial *** a matter of fact,a single recognition function can no longer meet people’s needs,and accurate image prediction is the trend that people *** paper is based on Long Short-Term Memory(LSTM)and Deep Convolution Generative Adversarial networks(DCGAN),studies and implements a prediction model by using radar image *** adopt a stack cascading strategy in designing network connection which can control of parameter convergence *** new method enables effective learning of image features and makes predictive models to have greater generalization *** demonstrate that our network model is more robust and efficient in terms of timing prediction than 3DCNN and traditional *** sequential image prediction model architecture proposed in this paper is theoretically applicable to all sequential images.

关键词： Image prediction LSTM DCGAN

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Energy-Efficient Data-Collection with Rendezvous-Based Approaches in Large-Scale WSNs with Multi-UGV 1

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5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Zhang, Jian Tan, Ling Zhuang, Wei College of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu Engineering Center of Network Monitoring Nanjing210044 China

ISBN: (数字)9783030242657

ISBN: (纸本)9783030242640

Prolonging the lifetime of wireless sensor networks (WSNs) is a crucial issue referring to energy conservation or balancing of data collection. In this paper, we propose an optimal algorithm for data collection using UGVs based on clustering by definition of rendezvous nodes (RNs). Due to the considerable large difference of long-distance transmission, the rendezvous-based clustered model for load balancing with multiple UGVs is proposed. Furthermore, considering different delay-tolerant applications, we design a data transmission mode called Two-Orbit Back-Propagation algorithm (TOBPA). In these process, we utilized utility function on energy to realize the optimal energy consumption in the sense of energy transmission model and take energy balancing into account meanwhile. As a result, we analyze the cluster lifetimes in different situations and achieve balance to save significant. © 2019, Springer Nature Switzerland AG.

关键词： Energy efficiency

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Vehicle Re-Identication Model Based on Optimized DenseNet121 with Joint Loss

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computers, Materials & Continua 2021年第6期67卷 3933-3948页

作者： Xiaorui Zhang Xuan Chen Wei Sun Xiaozheng He Jiangsu Engineering Center of Network Monitoring Engineering Research Center of Digital ForensicsMinistry of EducationSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing210044China Department of Civil and Environmental Engineering Rensselaer Polytechnic InstituteTroyNY12180USA

With the increasing application of surveillance cameras,vehicle re-identication(Re-ID)has attracted more attention in the eld of public *** Re-ID meets challenge attributable to the large intra-class differences caused by different views of vehicles in the traveling process and obvious inter-class similarities caused by similar *** existing methods focus on local attributes by marking local ***,these methods require additional annotations,resulting in complex algorithms and insufferable computation *** cope with these challenges,this paper proposes a vehicle Re-ID model based on optimized DenseNet121 with joint *** model applies the SE block to automatically obtain the importance of each channel feature and assign the corresponding weight to it,then features are transferred to the deep layer by adjusting the corresponding weights,which reduces the transmission of redundant information in the process of feature reuse in *** the same time,the proposed model leverages the complementary expression advantages of middle features of the CNN to enhance the feature expression ***,a joint loss with focal loss and triplet loss is proposed in vehicle Re-ID to enhance the model’s ability to discriminate difcult-to-separate samples by enlarging the weight of the difcult-to-separate samples during the training *** results on the VeRi-776 dataset show that mAP and Rank-1 reach 75.5%and 94.8%,***,Rank-1 on small,medium and large sub-datasets of Vehicle ID dataset reach 81.3%,78.9%,and 76.5%,respectively,which surpasses most existing vehicle Re-ID methods.

关键词： Vehicle re-identication densenet joint loss focal loss SE block

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