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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaoyuan Guan Zhiyong Gan Ling Deng Wei Shi Jiankang Chen Shenshen Bu Chunliang Zhao Jianfang Hu Yuren Zhou Wei-Shi Zheng Ruixuan Wang School of Computer Science and Engineering Sun Yat-Sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing MOE Guangzhou China Network Business Group China Unicom Guangzhou China Department of Network Intelligence Pengcheng Laboratory Shenzhen China School of Data and Science Qingdao University of Science and Technology Qingdao China School of Software Engineering Sun Yat-Sen University Zhuhai China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Out-of-distribution (OOD) detection is vital for the safe application of intelligent systems in real-world scenarios. This paper proposes an enhancement to OOD detection by leveraging the consistency in cognition between two models, both pretrained on in-distribution (ID) data. Specifically, for a given test sample, we first apply Principal Component Analysis (PCA)-based projection on the feature vectors from each model. These obtained feature vectors (with correlation between dimensions decoupled by PCA projection) are then aligned using a multiple linear mapping, which is fitted using the least squares method on the training data. We hypothesize that the regression error for OOD data will be larger than that for ID data, making it a useful metric for OOD detection. Our experimental results demonstrate the effectiveness of this method. When combined with existing robust baselines, our approach achieves state-of-the-art performance in OOD detection.

关键词： Training Measurement Analytical models Training data Vectors Data models Intelligent systems Facial features Principal component analysis Least mean squares methods

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A Parallel Adaptive DBSCAN Algorithm Based on k-Dimensional Tree Partition 2

A Parallel Adaptive DBSCAN Algorithm Based on k-Dimensional ...

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2nd International Conference on Machine Learning, Big Data and Business Intelligence, MLBDBI 2020

作者： Lu, Xin Wang, Yu Yuan, Jiao Wang, Xun Fu, Kun Yang, Ke University of Electronic Science and Technology of China School of Software Chengdu China China Railway Eryuan Engineering Group Co. Ltd Chengdu China

ISBN: (纸本)9781728196381

The existing parallel DBSCAN (density based spatial clustering of applications with noise) algorithm needs to determine the parameter settings manually, and the datasets will be repeatedly accessed in the process of data partitioning and data merging, which reduces the efficiency of the algorithm excuting. Therefore, this paper proposes a parallel adaptive DBSCAN algorithm based on k-dimensional tree partition. It divides the dataset into several balanced data partitions by using k-dimensional tree, and carries out parallel computing in spark distributed computing framework, thus increasing the concurrent processing ability of the algorithm program and improving the I/O access speed. In addition, the improved adaptive DBSCAN parameter method is applied to each data partition for clustering analysis to obtain local clusters, which solves the random problem of manual setting parameters in the clustering process, and ensures the data quality of clustering mining. At the same time of creating local clusters, this algorithm also puts the mapping relationship between data points and adjacent points into the HashMap data structure of the master node, and uses it to merge local clusters into whole clusters, which can reduce the time cost of data merging. The experimental results show that the proposed algorithm can save about 18% running time compared with RDD-DBSCAN algorithm without reducing the clustering quality. With the increase of the number of cluster nodes, the running efficiency of the algorithm can be further improved, so it is suitable for processing massive data clustering analysis. © 2020 IEEE.

关键词： Clustering algorithms

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Multi-sector Risk Management Framework for Analysis Cybersecurity Challenges and Opportunities 1

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11th International Conference on Multimedia Communications, Services and Security, MCSS 2022

作者： Niemiec, Marcin Pappalardo, Salvatore Marco Bozhilova, Maya Stoianov, Nikolai Dziech, Andrzej Stiller, Burkhard AGH University of Science and Technology Mickiewicza 30 Krakow30-059 Poland CIRM Viale Ortles 22 Milan Italy Software Engineering Italia S.r.l. Piazza Abramo Lincoln 7 Catania Italy Bulgarian Defence Institute Sofia Bulgaria Communication Systems Group CSG Department of Informatics IfI University of Zurich UZH Binzmühlestrasse 14 Zürich8050 Switzerland

ISBN: (数字)9783031202155

ISBN: (纸本)9783031202148

This paper describes an approach to analyse transversal and inter-sectoral cybersecurity challenges and opportunities: dedicated risk assessment and management framework, which can be used to develop cybersecurity technology roadmaps. This multi-sector assessment framework is able to prioritise and evaluate cybersecurity risks in trans-sectoral and inter-sectoral contexts as well as supports proper resource allocations and mitigation actions. To achieve this goal, the analysis of known risk management and risk assessment frameworks was performed, and results are presented in this paper. Also, an overview on transversal, inter-sectoral and multi-sectoral technological challenges and opportunities is provided. The result of this analysis is an architecture of the ECHO Multi-sector Assessment Framework, which was described in detail, including identified and analysed transversal aspects, multi-sector dependencies, and technological challenges and opportunities determine the input data for the framework. This solution is applicable in many sectors, such as energy, healthcare, maritime transportation, or defence, however it can also be extended to others. The architecture of the framework proposed supports the design of cybersecurity technology roadmap and the definition of governance models. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Risk assessment

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Securing optical networks using quantum-secured blockchain: An overview

arXiv

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arXiv 2021年

作者： Sharma, Purva Bhatia, Vimal Prakash, Shashi Signals and Software Group Discipline of Electrical Engineering Indian Institute of Technology Indore453552 India Photonics Laboratory Institute of Engineering and Technology Devi Ahilya University Indore452017 India

Deployment of optical network infrastructure and network services is growing exponentially for beyond 5G networks. Since the uptake of e-commerce and e-services has seen unprecedented serge in recent months due to the global COVID- 19 pandemic era, the security of such transactions in optical communication has gained much importance. Optical fiber communication networks are vulnerable to several types of security threats, such as single point failure, wormhole attacks, and sybil attacks. Therefore, blockchain is a promising solution to protect confidential information against attacks and helps in achieving trusted network architecture by creating a distributed ledger platform. Recently, blockchain has received much attention because of its decentralized and distributed ledger technology. Hence, blockchain has also been employed to protect network against such attacks. However, blockchain technology's security relies on the platform of computational complexity, and because of the evolution of quantum computers, it will become insecure in the near future. Therefore, for enhancing blockchain security, research focus on combining quantum key distribution (QKD) with blockchain. This new technology is known as quantumsecured blockchain. The article describes the attacks in optical networks and provides a solution to protect network against security attacks by employing quantum-secured blockchain in optical networks. It provides a brief overview of blockchain technology with its security loopholes and focuses on QKD, which makes blockchain technology more robust against quantumattacks. Next, the article provides a broad view of quantumsecured blockchain and presents the network architecture for future research and development of secure and trusted optical communication networks using quantum-secured blockchain. Copyright © 2021, The Authors. All rights reserved.

关键词： Blockchain

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Cross-modal and Semantics-Augmented Asymmetric CycleGAN for Data-Imbalanced Anime Style Face Translation 2021

Cross-modal and Semantics-Augmented Asymmetric CycleGAN for ...

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2021 3rd International Conference on Video, Signal and Image Processing

作者： Shiping Deng Kaoru Uchida Zhengwei Yin School of Software Engineering University of Science and Technology of China China and Graduate School of Computer and Information Sciences Hosei University Japan Graduate School of Computer and Information Sciences Hosei University Japan Alibaba Group China

ISBN: (纸本)9781450385886

Human face to anime face translation has attracted the attention of many researchers in recent years, and various works have achieved high-quality style transfer on conventional tasks. However, existing works often have fatal shortcomings when the target domain training data is heavily insufficient, which is named as imbalanced setting. Here the imbalanced (low-resource) task, generally means there is no sufficient data on the training dataset compared with the conventional task, e.g. the training data size is less than 100. To solve this problem, we propose a multi-modal translation model for a specific style. Based on the cyclic adversarial network and class activation map, we import semantic modality to enhance data information and attention modules, which help the model focus more on the discriminative areas between source and target domain. The experimental results show that our method has superiority in low-resource settings compared with similar existing work.

关键词： image translation low-resource Deep neural networks

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Classification System Based on Data Mining Technique for Flat-Colored Textiles

SSRN

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SSRN 2025年

作者： Zhou, Min Lin, Yukai Hu, Wei Dai, Chai Tang, Guangfa He, Fei School of Information and Intelligent Engineering Guangzhou xinhua University Dongguan China School of Intelligent Control Hunan Railway Professional Technology College Zhuzhou China College of Electrical and Electrical Engineering Hunan University Changsha China Dept. of Pingdingshan Branch of China Mobile Communication Group Henan co. LTD Henan Pingdingshan China Dept.of Physics Electrical and Intelligent Manufacturing Huaihua University Changsha China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

Manual visual inspection for defect detection in manufacturing can lead to high false positive rates. This paper compares data mining techniques for the binary classification of defects in flat products in a relatively open scenario. The background provides context on research into data mining-based detection. The methodology is divided into five sections: data collection, selection, preprocessing and transformation, classification, and model evaluation. Each section details the techniques applied, tailored to the application context, with specifying examples. Experiments apply real-world data sets self-collected from production lines. Statistics like prediction accuracy are generated by established data mining evaluation algorithms. Results indicate the efficacy of data mining for automated defect detection over manual approaches. Finally, conclusions summarize findings and discuss the limitations of the current research and planned future work to address the drawbacks. Overall, the formalized methodology and supportive experimental results demonstrate both the viability and potential areas of improvement for data mining in manufacturing quality control. © 2025, The Authors. All rights reserved.

关键词： Data accuracy

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HSNP-Miner: High Utility Self-Adaptive Nonoverlapping Pattern Mining 12

HSNP-Miner: High Utility Self-Adaptive Nonoverlapping Patter...

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12th IEEE International Conference on Big Knowledge, ICBK 2021

作者： Hossain, Md Motaher Wu, Youxi Fournier-Viger, Philippe Li, Zhao Guo, Lei Li, Yan Hebei University of Technology School of Artificial Intelligence Tianjin300401 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Alibaba Group Zhejiang Hangzhou310000 China Hebei University of Technology State Key Laboratory of Reliability and Intelligence of Electrical Equipment Tianjing 300401 China Hebei University of Technology School of Economics and Management Tianjing 300401 China

ISBN: (纸本)9781665438582

Sequential pattern mining (SPM) under the nonoverlapping condition (or nonoverlapping SPM) is a type of data mining used to extract frequent gapped subsequences (known as patterns) from sequences, which is more valuable and versatile than other related methods. In nonoverlapping SPM, two occurrences cannot reuse the same sequence letter in the exact location as the occurrences. This method evaluates the frequency of the patterns in the sequence, and ignores the impact of external utility (item price or profit). Therefore, some low-frequency and essential patterns are overlooked. To address this issue, this paper introduces High Utility Self-adaptive Nonoverlapping Pattern (HSNP) mining and proposes HSNP-Miner, which includes two steps: support calculation and candi-date pattern generation. To calculate the support, we propose the NoSup algorithm, which can effectively calculate support while avoiding the creation of redundant nodes. An advanced upper bound method is employed to generate the candidate patterns more efficiently. Compared to other competitive methods, the experimental results demonstrate the efficiency of the proposed algorithm and the uniqueness of nonoverlapping sequence pat-tarns. © 2021 IEEE.

关键词： Miners

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A cooperative heterogeneous vehicular clustering framework for

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Frontiers of Information technology & Electronic engineering 2021年第9期22卷 1247-1259页

作者： Iftikhar AHMAD Rafidah Md NOOR Zaheed AHMED Umm-e-HABIBA Naveed AKRAM Fausto Pedro GARCIA MARQUEZ Department of Computer Science and Information Technology MirpurUniversity of Science and TechnologyMirpur-10250(AJK)Pakistan Facultyof Computer Science and Information Technology University of MalayaKualaLumpur 50603Malaysia Departmentof Software Engineering University of KotliAJK 11100Pakistan Department of Mechanical Engineering Mirpur University of Science andTechnologyMirpur-10250(AJK)Pakistan Department of MechanicalEngineering Faculty of Mechanical EngineeringUniversity of MalayaKualaLumpur 50603Malaysia Ingenium Research Group University of Castilla-LaManchaSpain

Heterogeneous vehicular clustering integrates multiple types of communication networks to work efficiently for various vehicular *** popular form of heterogeneous network is the integration of long-term evolution(LTE)and dedicated short-range *** heterogeneity of such a network infrastructure and the non-cooperation involved in sharing cost/data are potential problems to solve.A vehicular clustering framework is one solution to these problems,but the framework should be formally verified and validated before being deployed in the real *** solve these issues,first,we present a het-erogeneous framework,named destination and interest-aware clustering,for vehicular clustering that integrates vehicular ad hoc networks with the LTE network for improving road traffic ***,we specify a model system of the proposed *** model is formally verified to evaluate its performance at the functional level using a model checking *** evaluate the performance of the proposed framework at the micro-level,a heterogeneous simulation environment is created by integrating state-of-the-art *** comparison of the simulation results with those of other known approaches shows that our proposed framework performs better.

关键词： Vehicular cluster Heterogeneity Cooperation Formal verification System model

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Verifying Transactional Consistency of MongoDB

arXiv

引用

arXiv 2021年

作者： Ouyang, Hongrong Wei, Hengfeng Huang, Yu Li, Haixiang Pan, Anqun State Key Laboratory for Novel Software Technology Nanjing China Nanjing University China Software Institute Nanjing University China TDSQL Team of Technology and Engineering Group of Tencent Tencent Inc. Shenzhen China

MongoDB is a popular general-purpose, document-oriented, distributed NoSQL database. It supports transactions in three different deployments: single-document transactions utilizing the WiredTiger storage engine in a standalone node, multi-document transactions in a replica set which consists of a primary node and several secondary nodes, and distributed transactions in a sharded cluster which is a group of multiple replica sets, among which data is sharded. A natural and fundamental question about MongoDB transactions is: What transactional consistency guarantee do MongoDB transactions in each deployment provide? However, it lacks both concise pseudocode of MongoDB transactions in each deployment and formal specification of the consistency guarantees which MongoDB claimed to provide. In this work, we formally specify and verify the transactional consistency protocols of MongoDB. Specifically, we provide a concise pseudocode for the transactional consistency protocols in each MongoDB deployment, namely WiredTiger, ReplicaSet, and ShardedCluster, based on the official documents and source code. We then prove that WiredTiger, ReplicaSet, and ShardedCluster satisfy different variants of snapshot isolation, namely StrongSI, RealtimeSI, and SessionSI, respectively. We also propose and evaluate efficient white-box checking algorithms for MongoDB transaction protocols against their consistency guarantees, effectively circumventing the NP-hard obstacle in theory. © 2021, CC BY.

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A Systematic Literature Review of Decentralized Applications in Web3: Identifying Challenges and Opportunities for Blockchain Developers

A Systematic Literature Review of Decentralized Applications...

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IEEE International Conference on Big Data

作者： Md Jobair Hossain Faruk Pratusha Raya Md Kamrul Siam Jerry Q. Cheng Hossain Shahriar Alfredo Cuzzocrea Pablo Garcia Bringas Department of Computer Science New York Institute of Technology USA Department of Software Engineering Kennesaw State University USA Center for Cybersecurity University of West Florida USA D4K Group University of Deusto Bilbao Spain iDEA Lab University of Calabria Rende Italy Department of Computer Science University of Paris City Paris France

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

The Internet has opened the floor to stakeholders by redefining the way of organizing, communicating, and collaborating that was initiated by the Web’s development. The advancement of the World Wide Web is an outright phenomenon and significant and we witnessed the evolution of the Web. As decentralized technologies continue to gain traction, Web3, or the decentralized internet, has emerged as a promising approach to enable a more secure, transparent, and privacy-preserved digital landscape. In this paper, we thoroughly conduct a systematic study to explore the challenges and opportunities encountered by blockchain developers in the context of decentralized applications (dApps) in Web3. We analyze a set of peer-reviewed research articles, whitepapers, and technical reports and present an in-depth understanding of the current state of Web3 development and its implications. Our finding indicates the opportunities that Web3 can facilitate, such as expanded use cases, enhanced security and privacy, decentralized infrastructure, and the potential for enabling inclusive development resources for blockchain developers. Additionally, we highlight various challenges that blockchain developers deal with including scalability, security, privacy, interoperability, and the need for standardized tools and frameworks along with various challenges in the software development lifecycle (SDLC). While there are significant challenges to overcome, the potential benefits of Web3 are substantial and could lead to a more inclusive, secure, and transparent digital ecosystem. Furthermore, we emphasize the importance of continued research, collaboration, and innovation among stakeholders to address the identified challenges and capitalize on Web3’s opportunities.

关键词： Privacy Ecosystems Writing Decentralized applications Blockchains Internet Stakeholders Security Web sites software development management

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