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An Analysis of Malicious Behaviors of Open-Source Packages Using Dynamic Analysis 37th

An Analysis of Malicious Behaviors of Open-Source Packages U...

引用

37th International Conference on computer Applications in Industry and Engineering

作者： Thanh-Cong Nguyen Duc-Ly Vu Debnath, Narayan C. Univ Informat Technol Ho Chi Minh City Vietnam Eastern Int Univ Sch Comp & Informat Technol Binh Duong Vietnam

ISBN: (纸本)9783031762727;9783031762734

There has been an increasing number of malicious open-source packages in recent years. A recent backdoor attack on the Linux xz utility has highlighted the importance of security checks on open-source packages, especially popular ones. While major security scanners focus on identifying vulnerabilities (CVEs) in open-source packages, there are very few studies on malware analysis techniques for them. Similar to traditional malware analysis, there are two types of analysis for open-source packages: static and dynamic analysis. Static analysis techniques mainly focus on analyzing the source code of a package while dynamic analysis techniques execute the code in an isolated environment. Dynamic analysis techniques seem more promising than static analysis techniques, as they can expose packages' behaviors at runtime. However, current dynamic analysis tools (e.g., package-analysis) make minimal effort to provide insight into the behaviors of open-source packages. In this paper, we attempt to analyze the dynamic behaviors of open-source packages on popular package repositories, including npm, PyPI, RubyGems, Packagist, and ***. We also analyze the discrepancies in behaviors between benign and malicious packages at runtime, which is helpful in building rules for malware detection. Our study finds that malicious packages perform a significantly higher number of domain communications and command executions. Malicious packages use simple techniques for malicious operations such as base64 or curl.

关键词： Dynamic malware analysis Open-source malicious packages Open-source software security Software supply chain Security Software supply chain attacks

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An Experiment to Investigate Changes in Physiological Signals During Subtle Wind and Scent Presentation for Designing Subtle Notifications 1

引用

8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Omata, Masaki Shioda, Takumi Univ Yamanashi Kofu Yamanashi Japan

ISBN: (数字)9783031826337

ISBN: (纸本)9783031826320;9783031826337

Notifications for visual and auditory modalities from smart phone have some problems. For the visual modality, the user needs to actively control his or her viewpoint toward the phone. For the auditory modality, the user may not hear the notification sound because it is drowned out by surrounding sound. As a solution to the problems, we have proposed a subtle notification system that uses wind and scent to notify users of less important notifications and identify the user's awareness of the notification based on changes in the user's physiological signals. In this paper, we conducted an experiment to measure and analyze physiological signals when subtle wind and scent stimuli were presented to participants performing a reading task, in order to design the proposed system. The results show that the wind stimulus caused a change in skin conductance and the scent stimulus caused a change in the amplitude of respiratory movement. This suggest that even such weak and invisible stimuli are noticed by a user performing a task and are reflected in the user's physiological responses.

关键词： Notification Physiological signal Wind Scent Subtle

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Improvement and Application of Multi-type Image Enhancement Algorithms 5th

Improvement and Application of Multi-type Image Enhancement ...

引用

5th China Intelligent Robotics Academic Conference

作者： Zang, Jingqi Zhang, Jiqing Dalian Maritime Univ Informat Sci & Technol Coll Dalian Peoples R China

ISBN: (纸本)9789819616138;9789819616145

Low-quality images often significantly impair the effectiveness of most computer vision tasks. Improving image quality is challenging due to the diverse range of image types and degradation properties. In this paper, we examine the limitations of three image enhancement approaches based on traditional algorithms and deep learning and enhance them to achieve a better trade-off between the reconstruction quality and time cost. Specifically, we investigate advancements in the receptive field, lightweight design based on distillation, and residual learning for enhancing image brightness, correcting chromatic aberration or color cast, and deblurring images, respectively. Besides, we further evaluate the effectiveness of our image enhancement results by applying them to the downstream task of image segmentation. Extensive experiments show that the proposed approach achieves comparable image enhancement performance and significantly improves the effectiveness of downstream vision tasks.

关键词： computer vision Deep learning Image enhancement

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Introducing Multidimensional Parallel Decoder to Reduce Cost of Implementation and Latency 37th

Introducing Multidimensional Parallel Decoder to Reduce Cost...

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37th International Conference on computer Applications in Industry and Engineering

作者： Mekhiel, Nagi Toronto Metropolitan Univ Dept Elect Comp & Biomed Engn Toronto ON Canada

ISBN: (纸本)9783031762727;9783031762734

The latency and complexity of decoders are critical to performance of devices such as memory and buffers. The number of locations to be accessed in an address could be in billions. We propose a multidimensional parallel decoder that divides the address space into multiple of smaller dimensions each is decoded separately in parallel. The decoding of a much smaller address is simpler compared to the decoding of the whole address space. A combinational circuit combines the outputs of the smaller numbers of decoded outputs that correspond to the different dimensions to obtain the full decoded address space. We also purpose a time multiplexed decoder that divides the address to multiple dimensions in time and uses the multidimensional parallel decoder to obtain the decoded outputs. The results of the multidimensional parallel decoder show reduction in the cost of implementation and latency by multiple folds compared to the conventional decoder.

关键词： memory systems latency of memory access complexity of implementation performance of storage systems decoder design

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Branch Master: A Binary Search Tree Based Board Game 1

引用

15th Indian Conference on Human-computer Interaction Design and Research

作者： Banahatti, Vijayanand Nim, Deekshaa Karanjavkar, Yash Bokil, Prasad Indian Inst Technol IDC Sch Design Mumbai 400076 Maharashtra India

ISBN: (数字)9783031808326

ISBN: (纸本)9783031808319;9783031808326

Computational thinking helps to break down complex issues leading to solutions, learning this skill is essential to navigate in digital world. Learning through games is one strategy used in the past. This strategy is used in this board game (Branch Master) to explain binary search tree (BST) based searching and insertion operations. A strong connection between content and gameplay is created by employing an endogenous design based on BST operations to promote computational thinking in a social context. The game is built considering players know how to compare two numbers with minimalistic rules. The game has an inherent challenge due to conflict and competition which will make players engage throughout the game play.

关键词： Computational Thinking Binary Search Tree (BST) Board Game

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Could You Hear That? Identifying Marathi Phrases Suitable for Aural Transcription Tasks 15th

Could You Hear That? Identifying Marathi Phrases Suitable fo...

引用

15th Indian Conference on Human-computer Interaction Design and Research

作者： Shetye, Saloni Amar Joshi, Anirudha Indian Inst Technol IDC Sch Design Mumbai Maharashtra India

ISBN: (纸本)9783031808289;9783031808296

Predetermined phrase sets are commonly used to carry out transcription tasks in evaluating text input methods. We examine the aural reliability of a set of 299 Marathi phrases that have been used in transcription studies in the past. We present a study in which 80 native Marathi speakers heard 30 randomly chosen phrases each and transcribed them, leading to 2,392 transcriptions (a repetition factor of eight per phrase). After an initial categorisation of transcription errors, we conducted a workshop with Marathi experts and arrived at an error tagging taxonomy consisting of 17 major error tags and 50 error subtags. After analysis of the transcriptions, we assigned 4,152 error subtags. Though the proportion of errors was higher than those reported in a similar study in English, surprisingly, we had a much smaller proportion of comprehension errors. We recommend 142 phrases that are aurally reliable for transcription studies but report the number and types of error subtags so that researchers can make their own assessments. The 157 phrases that we do not recommend have a value of their own, as they can inform future HCI research in Indian languages. Our contributions have potential applications in improving Marathi aural transcription tasks, spellcheck and auto-correct, synthetic speech, scripting for spoken interfaces and accessibility studies.

关键词： Transcription studies Phrase set Synthetic speech Marathi Error analysis Error tagging taxonomy

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Neural Architecture Tuning: A BO-Powered NAS Tool 7th

Neural Architecture Tuning: A BO-Powered NAS Tool

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7th International Conference on Optimization and Learning

作者： Ouertatani, H. Maxim, C. Niar, S. Talbi, E-G. IRT SystemX & INRIA Lille Palaiseau France IRT SystemX Palaiseau France UPHF & LAMIH UMR CNRS Valenciennes France Univ Lille & INRIA Lille France

ISBN: (纸本)9783031779404;9783031779411

Neural Architecture Search (NAS) consists of applying an optimization technique to find the best performing architecture(s) in a defined search space, with regard to an objective function. The practical implementation of NAS currently carries certain limitations, including prohibitive costs with the need for a large number of evaluations, an inflexibility in defining the search space by often having to select from a limited set of possible design components, and a difficulty of integrating existing architecture code by requiring a specialized design language for search space specification. We propose a simplified search tool, with efficiency in the number of evaluations needed to achieve good results, and flexibility by design, allowing for an easy and open definition of the search space and objective function. Interoperability with existing code or newly released architectures from the literature allows the user to quickly and easily tune architectures to produce well-performing solutions tailor-made for particular use cases. We practically apply this tool to certain vision search spaces, and showcase its effectiveness.

关键词： Neural Architecture Search Bayesian Optimization Custom Search Space Multi-fidelity search

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A Road Defect Detection Algorithm Based on Improved YOLOv8 5th

A Road Defect Detection Algorithm Based on Improved YOLOv8

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5th International Conference on Neural Computing for Advanced Applications (NCAA)

作者： Niu, Yiqing Cao, Jianrong Wang, Yuanchang Shandong Jianzhu Univ Sch Informat & Elect Engn Jinan 250101 Peoples R China

ISBN: (纸本)9789819770069;9789819770076

Road defect detection is considered a prerequisite for maintaining road quality and a necessary measure to ensure driving safety. In addressing the challenges posed by existing methods' inefficiency, inaccuracy, and high cost, an improved road defect detection algorithm grounded in the YOLOv8 framework is proposed, denoted as YOLOv8n-CSW. First, we integrate the CBAM attention mechanism into the backbone network's C2f module, now termed the C2fCBAM module, to enhance feature extraction capabilities and suppress irrelevant information interference. Then the lightweight convolutional method GSConv and cross-level partial network module, VoV-GSCSP, can be flexibly integrated as a sleek and efficient slim-neck to seamlessly displace the initial neck network, thus optimizing the overall architecture and performance, ensuring accuracy while reducing computational complexity. Moreover, substituting the loss function with Wise-IoU enables focusing on the anchor frame of common quality and improving overall detector performance. The experimental results conclusively present that on the RDD2022 dataset, the mAP50 of the enhanced algorithm achieves 56.9%, surpassing the original algorithm accuracy by 1.7%. The computational volume is reduced to 7.3G, representing a 9.8% decrease. Additionally, the algorithm achieves an impressive frame detection rate of 83 frames per second (FPS) enabling accurate detection of road defects in real-time.

关键词： Road defect detection YOLOv8 attention mechanism slim-neck WIoU

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Advanced Process Monitoring and OEE Metrics: Leveraging AASs for Efficiency 5th

Advanced Process Monitoring and OEE Metrics: Leveraging AASs...

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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Zielstorff, Aaron Schoettke, Dirk Buettner, Fiona Helena Kaempfe, Thomas Schaefer, Stephan Fraunhofer Inst Expt Software Engn IESE Fraunhofer Pl 1 D-67663 Kaiserslautern Germany Hsch Tech & Wirtschaft HTW Berlin Wilhelminenhofstr 75A D-12459 Berlin Germany

ISBN: (纸本)9783031807596;9783031807602

The article shows a way of collecting data to prepare the Overall Equipment Effectiveness (OEE) using the asset administration shell (AAS) in a case study. A systematic approach and the use of established methods are essential for this. The established KPI metric for evaluating equipment effectiveness has proven itself and is used across all industries for quantitative productivity measurement. The digitalization of systems generates a large amount of data from the production environment, which forms the basis for modern analysis methods. These enable, among other things, the detection of anomalies in the plant environment and an increase in machine effectiveness. With the increasing establishment of the AAS, there is a need for pragmatic integration of data that supports the process of asset evaluation and optimization. In this context, the use of the "Time Series Data" submodel offers an effective solution. It defines a uniform standard for the integration and semantic description of time series data. The effective integration of time series data into the AAS environment, which enables the comprehensive use of generated process data, is explained using an example.

关键词： Asset administration shell Time series data Historic data OEE Digital value creation

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Enhancing Crowdsourcing Data Accuracy for Robot Training via Confidence Learning and GNN 5th

Enhancing Crowdsourcing Data Accuracy for Robot Training via...

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5th China Intelligent Robotics Academic Conference

作者： Tang, Wenjun Chen, Rong Zhang, Zhikang Guo, Shikai Dalian Maritime Univ Dalian Liaoning Peoples R China

ISBN: (纸本)9789819616138;9789819616145

Robotic systems that utilize machine learning typically demand a large amount of highly accurate data for model training and performance improvement. Crowdsourcing provides researchers with a low-cost opportunity to gather diverse data from around the world. These data can significantly enhance robots' capabilities in terms of perception, decision-making, and interaction while also accelerating the optimization of machine learning models. However, owing to variations in the skills, experience, and personal biases of crowdsourcing participants, noise and redundancy are often introduced during data collection, compromising data quality and weakening the effectiveness of crowdsourcing data in improving robotic systems. To address this issue, confidence learning (CL) technology was first introduced to filter out erroneous or unreliable crowdsourced data. By analyzing the explicit or implicit relationships between workers and tasks, graph neural networks (GNNs) can be used to leverage node embeddings to infer the true labels of annotated data, improving accuracy and reliability. The experiments were conducted on real crowdsourced annotation datasets, covering 13 real-world application scenarios. The results demonstrate that after applying these processing steps, the accuracy of the data labels is significantly improved, providing a more robust data foundation for training robotic systems.

关键词： Crowdsourcing Confidence learning Data denoising Graph neural network Robotic system Training of robotic systems

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