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SSRN 2022年

作者： Hu, Jian Xie, Huan Lei, Yan Yu, Ke School of Big Data and Software Engineering Chongqing University Chongqing China

Context: Fault localization (FL) is essentially a search over the space of program statements to find suspicious entities that might have caused a program failure. However, the real-world programs are high dimensional and imbalanced, which limits the effectiveness and efficiency of existing FL methods. The state-of-the-art FL method (Aeneas) solves the imbalanced and high-dimensional problem but in a complex and time-consuming ***: Due to the limited effectiveness of original FL methods and the low efficiency of the state-of-the-art data augmentation method Aeneas, this paper proposes Lamont , a L ight-weight d a ta aug m entati on me t hod to improve the effectiveness of original FL methods and the efficiency of ***: Lamont uses revised linear discriminant analysis (LDA) to reduce the dimensionality of the original coverage matrix and leverage synthetic minority over-sampling (SMOTE) to generate the synthesized failing tests. The balanced coverage matrix with reduced dimensionality is fed into FL algorithms to obtain the ranked suspicious list of statements. To evaluate the efficiency and effectiveness, we compare Lamont with six representative FL methods and Aeneas on 458 versions of 10 real-life ***: It can be observed that Lamont outperforms in most cases for Top-K metric and reduces the number of statements that need to be checked from 17.45% to 79.81% compared with the original six FL methods. Furthermore, Lamont saves the time over the state-of-the-art data augmentation method Aeneas from 55.33% to 68.39% with comparable ***: This work conducts a large-scale experimental study to investigate the effectiveness and efficiency of Lamont . Two conclusions can be obtained based on the experimental results. First, it shows that Lamont is more effective than the original FL methods. Second, it shows Lamont is more efficient than Aeneas with similar effectiveness in six FL methods. © 2022, The Authors. All ri

关键词： Efficiency

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A Large-Capacity Information Hiding Algorithm Based on the Fractal Carrier

A Large-Capacity Information Hiding Algorithm Based on the F...

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Electronic Technology, Communication and Information (ICETCI), IEEE International Conference on

作者： Xuejiao Tao Yahong Leng Qian Yang Sen Bai School of Software Chongqing Institute of Engineering Chongqing China Office of Teaching Affairs Chongqing Institute of Engineering Chongqing China School of Big Data and Artificial Intelligence Chongqing Institute of Engineering Chongqing China

ISBN: (数字)9798350361643

ISBN: (纸本)9798350361650

Information security is a pressing concern in the era of the Internet. Within the realm of information security, significant research focus has been placed on information hiding technology. Researchers strive to enhance both the information hiding capacity and the anti-attack capability. This paper explores the concept of concealing information within fractal images. Fractal images possess a notable attribute of being affine transformed through simple IFS code parameters, thereby generating unique fractal representations. The simplicity of the transmission parameters facilitates an effortless restoration of the carrier. By employing straightforward affine or iterative parameters, the recipient can successfully extract the originally embedded carrier, subsequently unveiling the concealed information. To further augment the security of the information hiding process, an encryption strategy may be implemented to transmit sensitive data. In this scenario, the secret carrier serves as the public key, while the fractal parameter information functions as the private key, thereby intensifying the complexity of steganography analysis. Consequently, this paper introduces a high-capacity fractal carrier information hiding algorithm, which effectively embeds information within fractal images, amplifies and adapts fractal parameters based on requirements, and enhances the overall capacity of the fractal carrier. Exploiting fractal images for information hiding purposes conveys advantages such as minimized reliance on key information and exceptional concealment abilities, thus bolstering the secrecy of hidden data, expanding the storage capacity, and fortifying the resistance against steganalysis.

关键词： Resistance Steganography Shape Information security Public key Pressing Fractals

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Coordinated Spectral Efficiency Prediction for Real-World 5G CoMP Systems

arXiv

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arXiv 2024年

作者： Chen, Zhixing Fan, Zhaoyu Li, Yang Kang, Yibin Yan, Qi Shi, Qingjiang The School of Software Engineering Tongji University Shanghai China The Shenzhen Research Institute of Big Data Shenzhen China The Networking and User Experience Lab Huawei Technologies Shenzhen China Shenzhen Research Institute of Big Data Shenzhen China

Coordinated multipoint (CoMP) systems incur substantial resource consumption due to the management of backhaul links and the coordination among various base stations (BSs). Accurate prediction of coordinated spectral efficiency (CSE) can guide the optimization of network parameters, resulting in enhanced resource utilization efficiency. However, characterizing the CSE is intractable due to the inherent complexity of the CoMP channel model and the diversity of the 5G dynamic network environment, which poses a great challenge for CSE prediction in real-world 5G CoMP systems. To address this challenge, in this letter, we propose a data-driven model-assisted approach. Initially, we leverage domain knowledge to preprocess the collected raw data, thereby creating a well-informed dataset. Within this dataset, we explicitly define the target variable and the input feature space relevant to channel statistics for CSE prediction. Subsequently, a residual-based network model is built to capture the high-dimensional non-linear mapping function from the channel statistics to the CSE. The effectiveness of the proposed approach is validated by experimental results on real-world data. Copyright © 2024, The Authors. All rights reserved.

关键词： Spectrum efficiency

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Algorithm of Controllable Fractal Image Based on IFS Code

Algorithm of Controllable Fractal Image Based on IFS Code

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2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021

作者： Tao, Xuejiao Bai, Sen Liu, Chun Zhu, Change Chen, Haojun Yan, Yi School of Software Chongqing Institute of Engineering Chongqing China School of Big Data and Artificial Intelligence Chongqing Institute of Engineering Chongqing China

ISBN: (纸本)9781728190037

Simulated generation of fractal images is useful in various fields such as information steganography, art decoration, film and television scenes. However, the generation mechanism of fractal images has not been clarified, the function of generation parameters is not clear, and the generated fractal object is insufficiently controllable, which limit the application. Therefore, it is of great significance to explore the role of various affine transformation parameters in the IFS system to obtain the method of generating free and controllable fractal images. Based on the principle of generating fractal images by iterated function system, this paper analyzed the influence of the generation of each affine transformation of IFS code on the appearance of the fractal image. Fractal images with different transformation characteristics were generated by analyzing the types and variation law of affine transformation. The controllability parameters of the IFS code were adjusted to simulate different forms of fractal trees and fractal mountains, and to construct more natural fractal forest and fractal mountains based on this, so as to provide more controllable fractal images for application fields such as information steganography. © 2021 IEEE.

关键词： Fractals

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Hyperbolic Geometric Latent Diffusion Model for Graph Generation 41

Hyperbolic Geometric Latent Diffusion Model for Graph Genera...

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41st International Conference on Machine Learning, ICML 2024

作者： Fu, Xingcheng Gao, Yisen Wei, Yuecen Sun, Qingyun Peng, Hao Li, Jianxin Li, Xianxian Key Lab of Education Blockchain and Intelligent Technology Ministry of Education Guangxi Normal University Guilin China Institute of Artificial Intelligence Beihang University Beijing China School of Software Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing School of Computer Science and Engineering Beihang University Beijing China

Diffusion models have made significant contributions to computer vision, sparking a growing interest in the community recently regarding the application of them to graph generation. Existing discrete graph diffusion models exhibit heightened computational complexity and diminished training efficiency. A preferable and natural way is to directly diffuse the graph within the latent space. However, due to the non-Euclidean structure of graphs is not isotropic in the latent space, the existing latent diffusion models effectively make it difficult to capture and preserve the topological information of graphs. To address the above challenges, we propose a novel geometrically latent diffusion framework HypDiff. Specifically, we first establish a geometrically latent space with interpretability measures based on hyperbolic geometry, to define anisotropic latent diffusion processes for graphs. Then, we propose a geometrically latent diffusion process that is constrained by both radial and angular geometric properties, thereby ensuring the preservation of the original topological properties in the generative graphs. Extensive experimental results demonstrate the superior effectiveness of HypDiff for graph generation with various topologies. Copyright 2024 by the author(s)

关键词： Graph theory

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What Really Matters for Graph Contrastive Learning-Based Recommendations? A Unified Learning Strategy

What Really Matters for Graph Contrastive Learning-Based Rec...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Hongwei Zhou Min Gao Zongwei Wang Linxin Guo Yinghui Tao Wentao Li School of Big Data and Software Engineering Chongqing University Chongqing China Hong Kong University of Science and Technology China

Graph contrastive learning (GCL) has become increasingly popular in recommendation due to its remarkable ability to reduce reliance on labels. Typically, GCL employs data augmentation methods, e.g., structure perturbation and representation perturbation, and CL loss to enhance performance. Recent studies have shown that structural perturbation plays a minor role in GCL, but there is still a lack of exploration on the representation perturbation. Therefore, we compare the two data perturbations in detail and reveal that both of them have a limited impact on performance. Simply combining recommendation loss and CL loss can produce comparable improvements. Besides, we identify a shared principle between the designs of recommendation loss and CL loss: both aim to optimize representation by increasing similarity between a target node and its positive samples while decreasing similarity with negative samples. Based on these findings, we propose Compact Graph Contrastive Learning (CGCL), a streamlined strategy that eliminates the data augmentation and deeply unifies recommendation loss and CL loss by elegantly incorporating their respective contributions. Leveraging the benefits of the unified strategy, we discover that our model can learn a concentrated mode length distribution of representation, which can enhance the ability to debias and thus improve the performance of the recommendation. This is a novel perspective on representation learning, and we also validate its rationality through rigorous experiments. Our comprehensive study on multiple benchmark datasets demonstrates that CGCL outperforms existing GCL methods.

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Test Case Recommendation for Blockchain Systems Based on Graph Convolutional Networks

Test Case Recommendation for Blockchain Systems Based on Gra...

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IEEE International Conference on big data Security on Cloud (bigdataSecurity), High Performance and Smart Computing (HPSC) and Intelligent data and Security (IDS)

作者： Shuyi Li Pengyu Zhang Xueyang Liu Wenhui Hu School of Software & Microelectronics Peking University Beijing China Big data center State Grid Corporation of China Beijing China National Engineering Research Center for Software Engineering Peking University Beijing China

ISBN: (数字)9798350389524

ISBN: (纸本)9798350389531

In the development and operation of blockchain systems, the evaluation of these systems typically necessitates the formulation and execution of test cases. Current testing practices for blockchain systems often involve the manual specification of relevant test scenarios, with testing being conducted through inquiries or the execution of tasks within the system. However, due to the relatively narrow scope of real-world applications for blockchain systems, there exists a deficiency in appropriate test case sets for the evaluation of such systems. Consequently, this paper presents a Blockchain Test Case Recommendation System based on LightGCN, a simplified Graph Convolutional Neural Network. LightGCN dispenses with traditional graph convolutional network components such as non-linear activation and feature transformations, thereby enhancing the efficiency of model training. Experiments illustrate that this system effectively supplements and enhances the blockchain system’s test case set by aggregating information from domain nodes.

关键词： Training System testing Manuals Knowledge graphs big data Blockchains Security

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A Novel Design of Fatigue Driving Detector with mmWave Sensor AWR1642boost 23

A Novel Design of Fatigue Driving Detector with mmWave Senso...

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2023 International Conference on Intelligent Computing and Its Emerging Applications, ICEA 2023

作者： Tseng, Shih-Pang Hsiao, I-Hui Wang, Jhing-Fa School of Software and Big Data Changzhou College of Information Technology Changzhou China Department of Electrical Engineering National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9798400709050

According to statistics from the Ministry of Transportation, distracted driving is one of the main causes of traffic accidents. In Taiwan, approximately 20% of total accidents each year are attributed to distracted or fatigued driving, ranking it as the second leading cause of accidents. Typically, drivers start to feel fatigued and experience decreased reaction and decision-making abilities after driving continuously for 2-3 hours. Post-meal and midnight driving also tend to induce drowsiness more than other times. Additionally, alcohol consumption, drug use, and the use of hypnotic medication can lead to loss of consciousness. Fatigued driving poses a serious public safety issue, endangering both drivers and other road users. Therefore, developing effective methods for detecting driver fatigue is crucial. Based on existing research, employing facial monitoring systems can reduce accident rates by 10% to 20%. However, these systems are limited by lighting conditions. Thus, this paper proposes the use of millimeter-wave technology to realize a fatigue detection system, effectively addressing the high reliance of facial monitoring systems on lighting conditions. In this study, data collection was performed using the AWR1642boost, a highly integrated millimeter-wave radar development board developed by Texas Instruments. Subsequently, a Multi-experts system was developed to integrate and analyze four features: nodding, yawning, breathing, and heart rate. The system employed a Support Vector Machine (SVM) model to improve the accuracy of fatigue detection in driving scenarios. Experimental results demonstrated that the system achieved an accuracy rate of 90%, effectively discerning whether the driver was experiencing fatigue. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Highway accidents

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Research on Multi-AGVs dynamic scheduling based on deep reinforcement learning 19

Research on Multi-AGVs dynamic scheduling based on deep rein...

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19th IEEE International Conference on e-Business engineering, ICEBE 2023

作者： Qin, Zhuorui Wu, Xiaoqian Zheng, Yimin Wu, Qingyao South China University of Technology School of Software Engineering Guangzhou China Key Laboratory of Big Data and Intelligent Robot Ministry of Education China Shenzhen Bangqi Technology Intelligent Development Co. Ltd Shenzhen China Pazhou Lab Guangzhou China

ISBN: (纸本)9798350325553

Driven by the latest advances in industrial artificial intelligence, automatic guided vehicles (AGVs) have been widely used for material handling in flexible workshops. In the pursuit of agile and flexible production transportation planning, the ability to handle unpredictable and dynamic events is becoming increasingly important. In order to achieve this real-time dynamic control, this study proposes a distributed multi-agent architecture to solve the dynamic Multi-AGVs scheduling problem. Double Deep Q-Network algorithm is used to train the scheduling agent, capture the relationship between production transportation operation information and scheduling goals, and make real-time scheduling decisions for flexible jobs with constant arrival intervals. Specialized state, action, and reward representations are proposed to handle variable specifications of dynamic scheduling problems. The performance of this method under different scene scales was verified through simulation studies. Numerical results show that compared with existing traditional heuristic scheduling strategies, this method not only has superior performance, but also its advantages persist even if the manufacturing system job scale changes. © 2023 IEEE.

关键词： Reinforcement learning

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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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Computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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