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Detecting Double Mixed Compressed Images Based on Quaternion Convolutional Neural Network

Chinese Journal of Electronics 2024年第3期33卷 657-671页

作者： Hao WANG Jinwei WANG Xuelong HU Bingtao HU Qilin YIN Xiangyang LUO Bin MA Jinsheng SUN Department of Automation Nanjing University of Science and Technology Engineering Research Center of Digital Forensics Ministry of Education Department of Computer and Software Nanjing University of Information Science and Technology School of Management Nanjing University of Posts and Telecommunications Department of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University State Key Laboratory of Mathematical Engineering and Advanced Computing Qilu University of Technology

Detection of color images that have undergone double compression is a critical aspect of digital image *** the existence of various methods capable of detecting double Joint Photographic Experts Group(JPEG) compression,they are unable to address the issue of mixed double compression resulting from the use of different compression *** particular,the implementation of Joint Photographic Experts Group 2000(JPEG2000)as the secondary compression standard can result in a decline or complete loss of performance in existing *** tackle this challenge of JPEG+JPEG2000 compression,a detection method based on quaternion convolutional neural networks(QCNN) is *** QCNN processes the data as a quaternion,transforming the components of a traditional convolutional neural network(CNN) into a quaternion *** relationships between the color channels of the image are preserved,and the utilization of color information is ***,the method includes a feature conversion module that converts the extracted features into quaternion statistical features,thereby amplifying the evidence of double *** results indicate that the proposed QCNN-based method improves,on average,by 27% compared to existing methods in the detection of JPEG+JPEG2000 compression.

关键词： Color image forensics JPEG JPEG2000 Mixed double compression Quaternion convolutional neural network

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PASS: An adaptive multi-copy routing scheme for intermittently connected mobile Ad Hoc networks

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Journal of Convergence Information Technology 2012年第14期7卷 315-323页

作者： Xu, Jia Wang, Ru Chuan Sun, Li Juan College of Computer Nanjing University of Posts and Telecommunications Nanjing China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Jiangsu Province Nanjing China Key Laboratory for Computer Network and Information Integration Southeast University Ministry of Education Nanjing China State Key Lab. for Novel Software Technology Nanjing University Nanjing China

Intermittently Connected Mobile Ad Hoc Networks (ICMANs) are mobile networks in which complete source-to-destination paths do not exist most of the time. This paper proposed a Predictable Adaptive Seed Spray routing (PASS) for intermittently connected mobile Ad Hoc networks. PASS is a cost-efficient delay-bounded routing protocol without network parameters and provides acceptable and resilient service in the face of challenged environments. Simulations have shown that PASS outperforms existing schemes such as Epidemic, binary spray & wait and AMR with respect to routing cost and adaptability.

关键词： Routing protocols

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Modeling and analysis of collaboration network in large-scale complex software systems

Modeling and analysis of collaboration network in large-scal...

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作者： Sun, Shiwen Xia, Chengyi Wang, Li School of Computer and Communication Engineering Tianjin University of Technology Tianjin 300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin 300384 China

ISBN: (纸本)9789881725592

Large-scale software systems represent an important class of artificial complex systems, which can be investigated from the complex network perspective. Based on the collaboration network model, the collaboration relationships between header files from source code of large-scale computer software systems are explored. It has been found that the generated network displays a high degree of heterogeneity in connectivity. The structural heterogeneity also leads to network's another important feature - Robust yet fragile. That is the network displays an unexpected degree of robustness to random attack or disturbance, but is extremely vulnerable to intentional attack, i.e. to the removal of a few of highly connected nodes. These findings can help people to get a better understanding of the organizational principles and evolving mechanism of complex software systems. © 2011 Chinese Assoc of Automati.

关键词： Complex networks

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Mining important topological properties in large-scale computer software systems base on complex networks

Mining important topological properties in large-scale compu...

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World Congress on software Engineering

作者： Sun, Shiwen Xia, Chengyi Wang, Li Wang, Lanying School of Computer and Communication Engineering Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China Periodical Department Hebei University Baoding China

ISBN: (纸本)9780769543031

Recently, large-scale computer software systems have attached a great deal of attention when they are regarded as complex networks composed of interacting units. In this paper, the collaboration relationships between header files in the source code of Linux kernels are analyzed by constructing a weighted File Collaboration Network(FCN): each node represents a header file, two nodes are connected if corresponding header files are both included in the same source file at least once, also the link weight is assigned to evaluate the intensity of co-inclusion of two header files. Through using appropriate non-weighted and weighted quantities, structural properties of FCNs are characterized and analyzed. The study of large-scale softwares from the viewpoint of complex networks can provide a better description of the organizational principles and evolving mechanism of complex software systems. © 2010 IEEE.

关键词： Complex networks

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Random directional attack for fooling deep neural networks

arXiv

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arXiv 2019年

作者： Luo, Wenjian Wu, Chenwang Zhou, Nan Ni, Li Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China Hefei Anhui230027 China

Deep neural networks (DNNs) have been widely used in many fields such as images processing, speech recognition;however, they are vulnerable to adversarial examples, and this is a security issue worthy of attention. Because the training process of DNNs converge the loss by updating the weights along the gradient descent direction, many gradient-based methods attempt to destroy the DNN model by adding perturbations in the gradient direction. Unfortunately, as the model is nonlinear in most cases, the addition of perturbations in the gradient direction does not necessarily increase loss. Thus, we propose a random directed attack (RDA) for generating adversarial examples in this paper. Rather than limiting the gradient direction to generate an attack, RDA searches the attack direction based on hill climbing and uses multiple strategies to avoid local optima that cause attack failure. Compared with state-of-the-art gradient-based methods, the attack performance of RDA is very competitive. Moreover, RDA can attack without any internal knowledge of the model, and its performance under black-box attack is similar to that of the white-box attack in most cases, which is difficult to achieve using existing gradient-based attack methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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M-DFCPP: A runtime library for multi-machine dataflow computing

M-DFCPP: A runtime library for multi-machine dataflow comput...

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作者： Luo, Qiuming Liu, Senhong Huang, Jinke Li, Jinrong College of Computer Science and Software Engineering Shenzhen University Shenzhen China SKT Group Guangdong Province Key Laboratory of Popular High-Performance Computers Shenzhen China SKT Group Guangdong Province Engineering Center of China-made High Performance Data Computing System Shenzhen China

This article designs and implements a runtime library for general dataflow programming, DFCPP (Luo Q, Huang J, Li J, Du Z. Proceedings of the 52nd International Conference on Parallel Processing Workshops. ACM;2023:145-152.), and builds upon it to design and implement a multi-machine C++ dataflow library, M-DFCPP. In comparison to existing dataflow programming environments, DFCPP features a user-friendly interface and richer expressive capabilities (Luo Q, Huang J, Li J, Du Z. Proceedings of the 52nd International Conference on Parallel Processing Workshops. ACM;2023:145-152.), enabling the representation of various types of dataflow actor tasks (static, dynamic and conditional task). Besides that, DFCPP addresses the memory management and task scheduling for non-uniform memory access architectures, while other dataflow libraries lack attention to these issues. M-DFCPP extends the capability of current dataflow runtime libraries (DFCPP, taskflow, openstream, etc.) and capable of multi-machine computing, while maintains the API compatible with DFCPP. M-DFCPP adopts the concepts of master and follower (Dean J, Ghemawat S. Commun ACM. 2008;51(1):107-113;Ghemawat S, Gobioff H, Leung ST. ACM SIGOPS Operating Systems Review. ACM;2003:29-43.), which form a worksharing framework as many multi-machine system. To shift to the M-DFCPP framework, a filtering layer is inserted to the original DFCPP, transforming it into followers that can cooperate with each other. The master is made of modules for scheduling, data processing, graph partition, state management and so forth. In benchmark tests with workload with directed acyclic graph topology of binary trees and random graphs, DFCPP demonstrated performance improvements of 20% and 8%, respectively, compared to the second fastest library. M-DFCPP consistently exhibits outstanding performance across varying levels of concurrency and task workloads, achieving a maximum speedup of more than 20 over DFCPP, when the task parallelism e

关键词： Libraries

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DOA estimation for beam scanning radar based on sparse signal reconstruction with incomplete pulse

DOA estimation for beam scanning radar based on sparse signa...

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2022 IEEE International Conference on Signal Processing, communications and computing, ICSPCC 2022

作者： Wu, Ran Zhang, Yan Ni, Lihua Zhang, Kehao Liu, Ning Wan, Qun University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Northern Institute of Electronic Equipment Beijing100191 China Agile and Intelligent Computing Key Laboratory of Sichuan Province Chengdu611731 China

ISBN: (数字)9781665469722

ISBN: (纸本)9781665469722

Direction of Arrival (DOA) is one of the commonly used measurement for source localization. However, the receiving equipment of modern electronic reconnaissance can not completely intercept the pulse signal in the complex and dense electromagnetic environment. Thus, it is not easy to accurately estimate its DOA, especially in the case of multiple targets. In order to solve this problem, we propose a sparse super-resolution DOA method to achieve DOA estimation incomplete pulse. Combined with compressed sensing theory, the complex DOA estimation problem is transformed into Basis Pursuit (BP) method based on the minimum 1 norm optimization criterion. The method estimates the DOA by solving the optimal sparse vector that constitutes the signal and can detect multiple targets in the same range-azimuth unit. In addition, compared with the traditional direction-finding method using the BP method, our method can guarantee the performance of direction-finding while reducing the requirement of pulse integrity. The simulation results support the theoretical analysis. © 2022 IEEE.

关键词： Direction of arrival

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An immune based algorithm for Chinese network short text clustering

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Zidonghua Xuebao/ Acta Automatica Sinica 2009年第7期35卷 896-902页

作者： He, Tao Cao, Xian-Bin Tan, Hui School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Laboratory of Software in Computing and Communication Anhui Province Hefei 230027 China School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China

Network short text clustering is a major technology in network content security. Since Chinese network short text is less of keywords and full of anomalous writings, the traditional text clustering method is not directly suitable for network short text clustering. This paper presents an immune network regulation based method to cluster Chinese network short texts. First, Chinese N-gram chunks are extracted and transformed to Chinese pinyin to form the feature representation to each Chinese network short text, so as to relieve these two characteristics' bad influence on the clustering performance. Then, the network short text set is constructed as a dynamic network and an immune network learning mechanism is used to learn the similarity among short texts and therefore to gain a better clustering result. Experiments show our method can get better performance in Chinese network short text clustering, compared with traditional method such as K-means. © 2009 Acta Automatica Sinica. All rights reserved.

关键词： Cluster analysis

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Cost-Optimized Microservice Deployment for IoT Application in Cloud-Edge Collaborative Environment 26

Cost-Optimized Microservice Deployment for IoT Application i...

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26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Zhang, Xiaoyuan Tang, Bing Yang, Qing Xu, Wei Guo, Feiyan Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology School of Computer Science and Engineering Xiangtan411201 China Guangzhou Maritime University School of Information and Communication Engineering Guangzhou510725 China

ISBN: (纸本)9798350331684

With the popularity of cloud native and DevOps, container technology is widely used and combined with microservices. The deployment of container-based microservices in distributed cloud-edge infrastructure requires suitable strategies to ensure the quality of service for users. However, the existing container orchestration tools cannot flexibly select the best deployment location according to the user's cost budget, and are insufficient in personalized deployment solutions. From the perspective of application providers, this paper considers the location distribution of users, application dependencies, and server price differences, and proposes a genetic algorithm-based Internet-of-Things (IoT) application deployment strategy for personalized cost budgets. The application deployment problem is defined as an optimization problem that minimizes user service latency under cost constraints. This problem is an NP-hard problem, and genetic algorithm is introduced to solve the optimization problem effectively and improve the deployment efficiency. The proposed algorithm is compared with four baseline algorithms, Time-Greedy, Cost-Greedy, Random and PSO, using real datasets and some synthetic datasets. The results show that the proposed algorithm outperforms other competing baseline algorithms. © 2023 IEEE.

关键词： Genetic algorithms

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A novel denoising method for infrared image based on bilateral filtering and non-local means

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Optoelectronics Letters 2017年第3期13卷 237-240页

作者：刘凤连孙梦尧蔡文娜 Key Laboratory of Computer Vision and System Ministry of Education of ChinaTianjin Key Laboratory of Intelligence Computing and Novel Software TechnologySchool of Computer and Communication EngineeringTianjin University of TechnologyTianjin 300384China

This paper presents an image denoising method based on bilateral filtering and non-local means. The non-local region texture or structure of the image has the characteristics of repetition, which can be used to effectively preserve the edge and detail of the image. And compared with classical methods, bilateral filtering method has a better performance in denosing for the reason that the weight includes the geometric closeness factor and the intensity similarity factor. We combine the geometric closeness factor with the weight of non-local means, and construct a new weight. Experimental results show that the modified algorithm can achieve better performance. And it can protect the image detail and structure information better.

关键词： bilateral filtering similarity pixel texture combine repetition neighborhood preserve noisy

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