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What can we learn from quality assurance badges in open-source software?

science China(Information sciences) 2024年第4期67卷 146-163页

作者： Feng LI Yiling LOU Xin TAN Zhenpeng CHEN Jinhao DONG Yang LI Xuanzhi WANG Dan HAO Lu ZHANG MoE Key Lab of HCST School of Computer SciencePeking University Department of computer science Purdue University school of computer science & Engineering Beihang University(BUAA) Department of computer science University College London(UCL)

In the development of open-source software(OSS), many developers use badges to give an overview of the software and share some key features/metrics conveniently. Among various badges, quality assurance(QA) badges make up a large proportion and are the most prevalent because QA is of vital importance in software development, and ineffective QA may lead to anomalies or defects. In this paper, we focus on QA badges in open-source projects, which present quality assurance information directly and instantly,and aim to produce some interesting findings and provide practical implications. We collect and analyze 100000 projects written in popular programming languages from GitHub and conduct a comprehensive empirical study both inside and outside QA badges. Inside QA badges, we build a category classification for all QA badges based on the properties they focus on, which shows the types of QA badges developers use. Then,we analyze the frequency of the properties that QA badges focus on, and property combinations, too, which present their use status. We find that QA badges focus on various properties while developers give different preferences to different properties. The use status also differs between different programming languages. For example, projects written in C focus on Security to a great extent. Our findings also provide implications for developers and badge providers. Outside QA badges, we conduct a correlation analysis between QA badges and some software metrics that have potential relationships with code quality, contribution quality, and popularity. We find that QA badges have statistically significant correlations with various software metrics.

关键词： quality assurance badge open-source software code quality empirical study

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Meta label associated loss for fine-grained visual recognition

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science China(Information sciences) 2024年第6期67卷 230-247页

作者： Yanchao LI Fu XIAO Hao LI Qun LI Shui YU school of computer science Nanjing University of Posts and Telecommunications school of Network Engineering Zhoukou Normal University school of computer science University of Technology Sydney

Recently, intensive attempts have been made to design robust models for fine-grained visual recognition, most notably are the impressive gains for training with noisy labels by incorporating a reweighting strategy into a meta-learning framework. However, it is limited to up or downweighting the contribution of an instance for label reweighting approaches in the learning process. To solve this issue, a novel noise-tolerant method with auxiliary web data is proposed. Specifically, first, the associations made from embeddings of well-labeled data with those of web data and back at the same class are measured. Next, its association probability is employed as a weighting fusion strategy into angular margin-based loss, which makes the trained model robust to noisy datasets. To reduce the influence of the gap between the well-labeled and noisy web data, a bridge schema is proposed via the corresponding loss that encourages the learned embeddings to be coherent. Lastly, the formulation is encapsulated into the meta-learning framework, which can reduce the overfitting of models and learn the network parameters to be noise-tolerant. Extensive experiments are performed on benchmark datasets, and the results clearly show the superiority of the proposed method over existing state-of-the-art approaches.

关键词： label associated loss weighting noisy samples fine-grained visual recognition noise-tolerant learning meta-learning

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A Task Scheduling Algorithm Based on Clustering Pre-processing in Space-Based Information Network

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Chinese Journal of Electronics 2024年第1期33卷 217-230页

作者： Yufei WANG Jun LIU Shengnan ZHANG Sai XU Jingyi WANG school of computer science and Engineering Northeastern University

With the diversification of space-based information network task requirements and the dramatic increase in demand, the efficient scheduling of various tasks in space-based information network becomes a new challenge. To address the problems of a limited number of resources and resource heterogeneity in the space-based information network, we propose a bilateral pre-processing model for tasks and resources in the scheduling pre-processing stage. We use an improved fuzzy clustering method to cluster tasks and resources and design coding rules and matching methods to match similar categories to improve the clustering effect. We propose a space-based information network task scheduling strategy based on an ant colony simulated annealing algorithm for the problems of high latency of space-based information network communication and high resource dynamics. The strategy can efficiently complete the task and resource matching and improve the task scheduling performance. The experimental results show that our proposed task scheduling strategy has less task execution time and higher resource utilization than other algorithms under the same experimental conditions. It has significantly improved scheduling performance.

关键词： Space-based information network Task scheduling Resource clustering Ant colony optimization Simulated annealing

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CToMP: a cycle-task-oriented memory protection scheme for unmanned systems

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science China(Information sciences) 2024年第6期67卷 399-417页

作者： Chengyan MA Ning XI Di LU Yebo FENG Jianfeng MA school of Cyber Engineering Xidian University school of computer science and Technology Xidian University Department of computer and Information science University of Oregon

Memory corruption attacks(MCAs) refer to malicious behaviors of system intruders that modify the contents of a memory location to disrupt the normal operation of computing systems, causing leakage of sensitive data or perturbations to ongoing processes. Unlike general-purpose systems, unmanned systems cannot deploy complete security protection schemes, due to their limitations in size, cost and performance.MCAs in unmanned systems are particularly difficult to defend against. Furthermore, MCAs have diverse and unpredictable attack interfaces in unmanned systems, severely impacting digital and physical sectors. In this paper, we first generalize, model and taxonomize MCAs found in unmanned systems currently, laying the foundation for designing a portable and general defense approach. According to different attack mechanisms,we found that MCAs are mainly categorized into two types — return2libc and return2shellcode. To tackle return2libc attacks, we model the erratic operation of unmanned systems with cycles and then propose a cycle-task-oriented memory protection(CToMP) approach to protect control flows from tampering. To defend against return2shellcode attacks, we introduce a secure process stack with a randomized memory address by leveraging the memory pool to prevent Shellcode from being executed. Moreover, we discuss the mechanism by which CTo MP resists the return-oriented programming(ROP) attack, a novel variant of return2libc attacks. Finally, we implement CTo MP on CUAV V5+ with Ardupilot and Crazyflie. The evaluation and security analysis results demonstrate that the proposed approach CTo MP is resilient to various MCAs in unmanned systems with low footprints and system overhead.

关键词： unmanned system memory corruption attack memory protection system security randomized memory address

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Formal Verification of Data Modifications in Cloud Block Storage Based on Separation Logic

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Chinese Journal of Electronics 2024年第1期33卷 112-127页

作者： Bowen ZHANG Zhao JIN Hanpin WANG Yongzhi CAO Key Laboratory of High Confidence Software Technologies (MOE) School of Computer Science Peking University school of computer and Artificial Intelligence Zhengzhou University school of computer science and Cyber Engineering Guangzhou University

Cloud storage is now widely used, but its reliability has always been a major concern. Cloud block storage(CBS) is a famous type of cloud storage. It has the closest architecture to the underlying storage and can provide interfaces for other types. Data modifications in CBS have potential risks such as null reference or data loss.Formal verification of these operations can improve the reliability of CBS to some extent. Although separation logic is a mainstream approach to verifying program correctness, the complex architecture of CBS creates some challenges for verifications. This paper develops a proof system based on separation logic for verifying the CBS data modifications. The proof system can represent the CBS architecture, describe the properties of the CBS system state, and specify the behavior of CBS data modifications. Using the interactive verification approach from Coq, the proof system is implemented as a verification tool. With this tool, the paper builds machine-checked proofs for the functional correctness of CBS data modifications. This work can thus analyze the reliability of cloud storage from a formal perspective.

关键词： Formal verification Separation logic Cloud block storage Verification tool Coq

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Fast Cross-Platform Binary Code Similarity Detection Framework Based on CFGs Taking Advantage of NLP and Inductive GNN

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Chinese Journal of Electronics 2024年第1期33卷 128-138页

作者： Jinxue PENG Yong WANG Jingfeng XUE Zhenyan LIU school of computer science and Technology Beijing Institute of Technology

Cross-platform binary code similarity detection aims at detecting whether two or more pieces of binary code are similar or not. Existing approaches that combine control flow graphs(CFGs)-based function representation and graph convolutional network(GCN)-based similarity analysis are the best-performing ones. Due to a large amount of convolutional computation and the loss of structural information, the use of convolution networks will inevitably bring problems such as high overhead and sometimes inaccuracy. To address these issues, we propose a fast cross-platform binary code similarity detection framework that takes advantage of natural language processing(NLP)and inductive graph neural network(GNN) for basic blocks embedding and function representation respectively by simulating extracting structural features and temporal features. GNN’s node-centric and small batch is a suitable training way for large CFGs, it can greatly reduce computational overhead. Various NLP basic block embedding models and GNNs are evaluated. Experimental results show that the scheme with long short term memory(LSTM)for basic blocks embedding and inductive learning-based Graph SAGE(GAE) for function representation outperforms the state-of-the-art works. In our framework, we can take only 45% overhead. Improve efficiency significantly with a small performance trade-off.

关键词： Control flow graph Natural language processing Inductive graph neural network Binary code similarity detection

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Troy: Efficient Service Deployment for Windows Systems

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Chinese Journal of Electronics 2024年第1期33卷 313-322页

作者： Deyu ZHANG Yu XIE Mucong XU En CHENG Xiaoyan KUI Bangwen HE Yunhao LI school of computer science and Engineering Central South University

The modern university computer lab and kindergarden through 12th grade classrooms require a centralized solution to efficiently manage a large number of desktops. The existing solutions either bring virtualization overhead in runtime or requires loading a large image over 30 GB leading to an unacceptable network latency. In this work, we propose Troy which takes advantage of the differencing virtual hard disk techniques in Windows systems.As such, Troy only loads the modifications made on one machine to all other machines. Troy consists of two modules that are responsible to generate an initial image and merge a differencing image with its parent image, respectively. Specifically, we identify the key fields in the virtual hard disk image that links the differencing image and the parent image and find the modified blocks in the differencing images that should be used to replace the blocks in the parent image. We further design a lazy copy solution to reduce the I/O burden in image merging. We have implemented Troy on bare metal machines. The evaluation results show that the performance of Troy is comparable to the native implementation in Windows, without requiring the Windows environment.

关键词： Service deployment Virtual hard disk File system merging Windows system

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APF-GAN:Exploring asymmetric pre-training and fine-tuning strategy for conditional generative adversarial network

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Computational Visual Media 2024年第1期10卷 187-192页

作者： Yuxuan Li Lingfeng Yang Xiang Li College of computer science Nankai UniversityTianjinChina school of computer science and Engineering Nanjing University of Science and TechnologyNanjingChina

The use of generative adversarial network(GAN)-based models for the conditional generation of image semantic segmentation has shown promising results in recent years.However,there are still some limitations,including limited diversity of image style,distortion of detailed texture,unbalanced color tone,and lengthy training time.To address these issues,we propose an asymmetric pre-training and fine-tuning(APF)-GAN model.

关键词： tuning network asymmetric

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Local saliency consistency-based label inference for weakly supervised salient object detection using scribble annotations

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 239-249页

作者： Shuo Zhao Peng Cui Jing Shen Haibo Liu school of computer science and Technology Harbin University of Science and TechnologyHarbinChina school of computer science and Technology Harbin Engineering UniversityHarbinChina

Recently,weak supervision has received growing attention in the field of salient object detection due to the convenience of labelling.However,there is a large performance gap between weakly supervised and fully supervised salient object detectors because the scribble annotation can only provide very limited foreground/background information.Therefore,an intuitive idea is to infer annotations that cover more complete object and background regions for training.To this end,a label inference strategy is proposed based on the assumption that pixels with similar colours and close positions should have consistent labels.Specifically,k-means clustering algorithm was first performed on both colours and coordinates of original annotations,and then assigned the same labels to points having similar colours with colour cluster centres and near coordinate cluster centres.Next,the same annotations for pixels with similar colours within each kernel neighbourhood was set further.Extensive experiments on six benchmarks demonstrate that our method can significantly improve the performance and achieve the state-of-the-art results.

关键词： label inference salient object detection weak supervision

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Malware Evasion Attacks Against IoT and Other Devices: An Empirical Study

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Tsinghua science and Technology 2024年第1期29卷 127-142页

作者： Yan Xu Deqiang Li Qianmu Li Shouhuai Xu school of computer science and Engineering Nanjing University of Science and TechnologyNanjing 210094China school of computer science Nanjing University of Posts and TelecommunicationsNanjing 210023China Department of computer science University of Colorado Colorado SpringsColorado SpringsCO 80918USA

The Internet of Things(loT)has grown rapidly due to artificial intelligence driven edge computing.While enabling many new functions,edge computing devices expand the vulnerability surface and have become the target of malware attacks.Moreover,attackers have used advanced techniques to evade defenses by transforming their malware into functionality-preserving variants.We systematically analyze such evasion attacks and conduct a large-scale empirical study in this paper to evaluate their impact on security.More specifically,we focus on two forms of evasion attacks:obfuscation and adversarial attacks.To the best of our knowledge,this paper is the first to investigate and contrast the two families of evasion attacks systematically.We apply 10 obfuscation attacks and 9 adversarial attacks to 2870 malware examples.The obtained findings are as follows.(1)Commercial Off-The-Shelf(COTS)malware detectors are vulnerable to evasion attacks.(2)Adversarial attacks affect COTS malware detectors slightly more effectively than obfuscated malware examples.(3)Code similarity detection approaches can be affected by obfuscated examples and are barely affected by adversarial attacks.(4)These attacks can preserve the functionality of original malware examples.

关键词： Android malware obfuscation adversarial examples

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