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Accelerating high-Precision Vulnerability Detection in C programs with Parallel Graph Summarization 6

Accelerating High-Precision Vulnerability Detection in C Pro...

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6th International conference on Software Engineering and computer Science, CSECS 2023

作者： Xu, Rulin Mao, Xiaoguang Xiao, Wei School of Computer NUDT Changsha China

ISBN: (纸本)9798350306378

C language programs are often subject to memory vulnerabilities, posing substantial security risks to software systems. Conventional detection techniques, rooted in static value-flow analysis, necessitate exhaustive searches across the entirety of value-flow graphs. This approach results in inefficient analyses of large-scale codes and presents difficulties in parallelization due to interdependent steps. In this study, we propose an innovative approach based on parallel graph summarization. This technique effectively transforms the computational bottleneck into a task that can be expedited in a parallel manner, leveraging multicore computation to significantly enhance the performance and scalability of vulnerability detection within $C$ programs. We segment the value-flow graph of the program into multiple subgraphs, extracting summaries of three pivotal types of information from each subgraph: path summaries, guard summaries, and behaviour summaries. These summaries significantly stream-line subsequent vulnerability detection analyses. Moreover, we implement a task-level parallel technique to accelerate the graph summary process in a multicore environment. Notably, empirical results reveal that our method, while ensuring accuracy, achieves 2.7X-6.1X speedup compared to serial algorithms. When assessed against prevalent open-source detection tools, our approach demonstrates superior trade-offs between accuracy and efficiency. In conclusion, this research presents an efficient and effective strategy for vulnerability detection in larze-scale C programs. © 2023 IEEE.

关键词： Static analysis

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A Survey on Vehicular Edge Computing Architectures 13

A Survey on Vehicular Edge Computing Architectures

引用

13th International conference on Information and Communication Technology Convergence, ICTC 2022

作者： Lee, Jaehwan Na, Woongsoo Kongju National University Department of Computer Science and Engineering Korea Republic of Kongju National University Department of Software Korea Republic of

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

With the recent development of intelligent transportation system (ITS), vehicular applications are being actively studied including autonomous driving, vehicle platooning, that require real-time and high-performance processing resources. Accordingly, various system architectures are being studied to satisfy the high-performance computing requirements. Although the mobile cloud computing architecture provides large-scale computing resources, it is not suitable for vehicular environment that requires real-time processing due to the structure in which the edge node and the computing resources are geographically distant. The mobile edge computing (MEC) architecture places computing resources around edge devices. However, it does not consider edge devices moving at a high speed in a limited service area. Vehicular edge computing (VEC) and vehicular fog computing paradigm have emerged to address the latency requirement with the development of vehicular communications. In this paper, such a computation offloading architecture is presented and analyzed. © 2022 IEEE.

关键词： computer architecture

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Safety Verification for Neural Networks Based on Set-Boundary Analysis 1

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17th International conference on Theoretical Aspects of Software Engineering (TASE)

作者： Liang, Zhen Ren, Dejin Liu, Wanwei Wang, Ji Yang, Wenjing Xue, Bai Natl Univ Def Technol Inst Quantum Informat Changsha Peoples R China Natl Univ Def Technol State Key Lab High Performance Comp Changsha Peoples R China Chinese Acad Sci Inst Software State Key Lab Comp Sci Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Natl Univ Def Technol Coll Comp Sci & Technol Changsha Peoples R China

ISBN: (数字)9783031352577

ISBN: (纸本)9783031352560;9783031352577

Neural networks (NNs) are increasingly applied in safety-critical systems such as autonomous vehicles. However, they are fragile and are often ill-behaved. Consequently, their behaviors should undergo rigorous guarantees before deployment in practice. In this paper, we propose a set-boundary reachability method to investigate the safety verification problem of NNs from a topological perspective. Given an NN with an input set and a safe set, the safety verification problem is to determine whether all outputs of the NN resulting from the input set fall within the safe set. In our method, the homeomorphism property of NNs is mainly exploited, which establishes a relationship mapping boundaries to boundaries. The exploitation of this property facilitates reachability computations via extracting subsets of the input set rather than the entire input set, thus controlling the wrapping effect in reachability analysis and facilitating the reduction of computation burdens for safety verification. The homeomorphism property exists in some widely used NNs such as invertible NNs. Notable representations are invertible residual networks (i-ResNets) and Neural ordinary differential equations (Neural ODEs). For these NNs, our set-boundary reachability method only needs to perform reachability analysis on the boundary of the input set. For NNs that do not feature this property with respect to the input set, we explore subsets of the input set for establishing the local homeomorphism property and then abandon these subsets for reachability computations. Finally, some examples demonstrate the performance of the proposed method.

关键词： Safety verification Neural networks Boundary analysis Homeomorphism

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Polar-Net: A Clinical-Friendly Model for Alzheimer's Disease Detection in OCTA Images 26th

Polar-Net: A Clinical-Friendly Model for Alzheimer's Disease...

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26th International conference on Medical Image Computing and computer-Assisted Intervention (MICCAI)

作者： Liu, Shouyue Hao, Jinkui Xu, Yanwu Fu, Huazhu Guo, Xinyu Liu, Jiang Zheng, Yalin Liu, Yonghuai Zhang, Jiong Zhao, Yitian Chinese Acad Sci Ningbo Inst Mat Technol & Engn Cixi Inst Biomed Engn Ningbo Peoples R China Wenzhou Med Univ Cixi Biomed Res Inst Ningbo Peoples R China South China Univ Technol Sch Future Technol Guangzhou Peoples R China Pazhou Lab Guangzhou Peoples R China ASTAR Inst High Performance Comp Singapore Singapore Southern Univ Sci & Technol Dept Comp Sci Shenzhen Peoples R China Univ Liverpool Dept Eye & Vis Sci Liverpool Merseyside England Edge Hill Univ Dept Comp Sci Ormskirk England

ISBN: (纸本)9783031439896;9783031439902

Optical Coherence Tomography Angiography (OCTA) is a promising tool for detecting Alzheimer's disease (AD) by imaging the retinal microvasculature. Ophthalmologists commonly use region-based analysis, such as the ETDRS grid, to study OCTA image biomarkers and understand the correlation with AD. In this work, we propose a novel deep-learning framework called Polar-Net. Our approach involves mapping OCTA images from Cartesian coordinates to polar coordinates, which allows for the use of approximate sector convolution and enables the implementation of the ETDRS grid-based regional analysis method commonly used in clinical practice. Furthermore, Polar-Net incorporates clinical prior information of each sector region into the training process, which further enhances its performance. Additionally, our framework adapts to acquire the importance of the corresponding retinal region, which helps researchers and clinicians understand the model's decision-making process in detecting AD and assess its conformity to clinical observations. Through evaluations on private and public datasets, we have demonstrated that Polar-Net outperforms existing state-of-the-art methods and provides more valuable pathological evidence for the association between retinal vascular changes and AD. In addition, we also show that the two innovative modules introduced in our framework have a significant impact on improving overall performance.

关键词： OCTA Alzheimer's Disease Polar Transformation

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Not All Frequencies Are Created Equal: Towards a Dynamic Fusion of Frequencies in Time-Series Forecasting 24

Not All Frequencies Are Created Equal: Towards a Dynamic Fus...

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32nd ACM International conference on Multimedia, MM 2024

作者： Zhang, Xingyu Zhao, Siyu Song, Zeen Guo, Huijie Zhang, Jianqi Zheng, Changwen Qiang, Wenwen Institute of Software Chinese Academy of Sciences University of Chinese Academy of Sciences BeiJing China School of Mathematical Sciences University of Chinese Academy of Sciences BeiJing China School of Computer Science and Engineering Beihang University BeiJing China

ISBN: (纸本)9798400706868

Long-term time series forecasting is a long-standing challenge in various applications. A central issue in time series forecasting is that methods should expressively capture long-term dependency. Furthermore, time series forecasting methods should be flexible when applied to different scenarios. Although Fourier analysis offers an alternative to effectively capture reusable and periodic patterns to achieve long-term forecasting in different scenarios, existing methods often assume high-frequency components represent noise and should be discarded in time series forecasting. However, we conduct a series of motivation experiments and discover that the role of certain frequencies varies depending on the scenarios. In some scenarios, removing high-frequency components from the original time series can improve the forecasting performance, while in others scenarios, removing them is harmful to forecasting performance. Therefore, it is necessary to treat the frequencies differently according to specific scenarios. To achieve this, we first reformulate the time series forecasting problem as learning a transfer function of each frequency in the Fourier domain. Further, we design Frequency Dynamic Fusion (FreDF), which individually predicts each Fourier component, and dynamically fuses the output of different frequencies. Moreover, we provide a novel insight into the generalization ability of time series forecasting and propose the generalization bound of time series forecasting. Then we prove FreDF has a lower bound, indicating that FreDF has better generalization ability. Extensive experiments conducted on multiple benchmark datasets and ablation studies demonstrate the effectiveness of FreDF. © 2024 Owner/Author.

关键词： Fourier analysis

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Active Sensing for Transformer Model in Sparse Mobile CrowdSensing 20

Active Sensing for Transformer Model in Sparse Mobile CrowdS...

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20th IEEE International conference on Mobile Ad Hoc and Smart Systems, MASS 2023

作者： Hao, Deran Wang, En Liu, Wenbin Liu, Weiting Yuan, Jiang Yang, Yongjian Wu, Jie Jilin University College of Computer Science and Technology Changchun China Temple University Department of Computer and Information Sciences Philadelphia United States

ISBN: (纸本)9798350324334

With the popularization of mobile devices and the development of 5G networks, Mobile Crowd-Sensing (MCS) has emerged as a new paradigm for data collection. As its variant, Sparse MCS is favored by researchers because of its practicality and low costs, which only needs to select a few sub-areas and then infer the entire map. To achieve good performance on the complex sensing tasks, Sparse MCS has to utilize the powerful deep learning methods, e.g., Transformer, which actually has high requirements for training data sets. However, most existing works randomly select spatiotemporal positions to sense training data, which not only ignores the importance of the spatiotemporal positions but also may lead to unbalance sensing data distribution and affect the training of the model. Consequently, in this paper, we propose an active sensing method in Sparse MCS for the Transformer-like models. First, we consider the data correlation at different spatiotemporal positions and use it to evaluate the representativeness of each spatiotemporal position. Secondly, we assess the informativeness of each spatiotemporal position by using the newly proposed spatiotemporal attention mechanism. Then we use these two aspects to evaluate the importance of each spatiotemporal position. Finally, we evaluate the performance of our proposed method through two typical urban sensing tasks with three real-world datasets. © 2023 IEEE.

关键词： 5G mobile communication systems

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EdgeFormer: Edge-Assisted Transformer for Thermal Images Semantic Segmentation 2

EdgeFormer: Edge-Assisted Transformer for Thermal Images Sem...

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2nd International conference on Electronic Information Engineering, Big Data, and computer Technology, EIBDCT 2023

作者： Wang, Futian Ding, Zhongfeng Shi, Tao Tang, Jin Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China

ISBN: (纸本)9781510664968

Most problems in the power system are related to the temperature of electrical equipment. The abnormal high temperature of electrical equipment will not only cause damage to equipment itself, but also threaten the safety of people's life and property. Therefore, patrol inspectors of power system will carry out routine inspection on electric equipment to ensure safety. Semantic segmentation for electrical equipment carries a big weight in the inspection. With the result of semantic segmentation of power equipment, patrol inspectors can quickly judge whether the temperature of power equipment is normal, and then take the corresponding action. For this reason, we propose the EdgeFormer, which is a typical end-to-end network using thermal image to segment electrical equipment. In our method, we employ an edge information extraction network to attain rich edge features to promote the segmentation performance in electrical equipment's edges and interiors, and we also design the global enhancing module (GEM) to get rich semantic information. Besides, we also propose a feature inserting module (FIM) to fuse the feature maps from different stages together. Lots of experiments have been conducted on the LS-ETS dataset and the results show that our EdgeFormer has achieved the best performance. © 2023 SPIE.

关键词： Semantic Segmentation

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Target-aware Guided equivariant Diffusion model for 3D molecule Generation

Target-aware Guided equivariant Diffusion model for 3D molec...

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2024 IEEE International conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Wang, Qian Wei, Zhiqiang Hu, Xiaotong Wang, Zhuoya Lu, Hao Liu, Hao Ocean University of China College of Computer Science and Technology Qingdao China Qingdao Marine Science and Technology Center Qingdao China

ISBN: (纸本)9798350386226

In the process of targeted drug molecule design, models that incorporate three-dimensional structures show better performance than target-free models. This is because the interactions between atoms can be explicitly modeled in three-dimensional space, thereby improving the accuracy and effectiveness of drug design. In previous studies, researchers usually used static or semi-flexible crystal structures to simplify the dynamic interactions between active sites and small molecules, only calculating limited system dynamics information. However, this simplification leads to an inadequate understanding of the dynamic characteristics of active sites, neglecting the consideration of the binding dynamics during molecule generation, which impacts the generation of high-quality 3D molecules. To this end, we proposed a 3D molecule generation method based on a target-aware guided diffusion model. This method uses target structure as a condition, introducing a diffusion model to simulate the dynamic evolution of molecular structures, and further refines and optimizes ligand through the structure of target-ligand complexes. Additionally, the continuous distribution of atomic coordinates and the discrete distribution of molecular features are introduced in the molecular latent space through the equivariant graph neural network, which facilitates the representation of the parameterized reverse generation process. Experimental results show that this method can continuously achieve better performance on multiple molecular generation benchmarks and can generate more realistic multiple 3D structure molecules with high binding affinity to protein targets. © 2024 IEEE.

关键词： Graph neural networks

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Aspect-based Sentiment Analysis for Improving Online Learning program Based on Student Feedback 6

Aspect-based Sentiment Analysis for Improving Online Learnin...

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6th IEEE International conference on Cybernetics and Computational Intelligence, CyberneticsCom 2022

作者： Heryadi, Yaya Wijanarko, Bambang Dwi Murad, Dina Fitria Tho, Cuk Hashimoto, Kiyota Binus Graduate Program-Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Binus Online Learning Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Binus Online Learning Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Phuket83120 Thailand

ISBN: (数字)9781665497428

ISBN: (纸本)9781665497428

This paper presents an empiric results of aspectbased sentiment analysis in education to extract and classify opinions, sentiments, evaluations, attitudes, and emotions from newly graduates of an online learning program. As part of continuous education monitoring system, the sentiment analysis process produces valuable input to leverage service quality of online learning program. In this study, the aspect-based sentiment analysis is implemented to analyze a set of feedbacks from 162 newly graduate from Binus Online program majoring in Accounting, Management, Information System, and computer Science. The important qualitative results of this study are confirmation that the main benefits of online learning from student perspective are mainly: the knowledge they gained from the program, learning guidance, reliable student team to work on thesis, quality of education support system, and learning happiness. © 2022 IEEE.

关键词： Sentiment analysis

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Analysis of Assembly Code Similarities of Different C++ Compilers

Analysis of Assembly Code Similarities of Different C++ Co...

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International conference on Advanced Engineering, Technology and Applications, ICAETA 2024

作者： Çelik, Esra Dal, Deniz Ataturk University Department of Computer Engineering Erzurum25240 Turkey

ISBN: (纸本)9783031709234

A compiler is an important system software responsible for converting high-level programming code into low-level machine code. This process involves a one-to-many relationship in which a single high-level code can produce multiple machine code variations that all share the same functionality. Compilers are able to optimize code to improve runtime performance or reduce memory requirements, depending on specific performance criteria. Today, there are a variety of compilers, each tailored to produce optimized output to meet different requirements and target platforms. MSVC++, CLANG/LLVM, and GCC g++ can be given as examples for well-known C++ compilers. The focus of our study represents a significant contribution to the literature, as it examines for the first time the similarities within assembly code outputs produced by the latest versions of MSVC++, CLANG/LLVM, and GCC g++. This investigation was facilitated by the use of the tool named Measure Of Software Similarity, also known as MOSS in short. The study was conducted in two phases: First, we assembled a set of 24 different C++ benchmarks that included well-defined control structures, data elements, and functions. Then, in the second phase, we generated three different assembly code representations for each benchmark using the corresponding compilers. The result of our analysis showed that across all benchmarks, the highest degree of code similarity was observed between GCC g++ and CLANG/LLVM, while the lowest similarity was observed between GCC g++ and MSVC++. It was also notable that MSVC++ produced a comparatively larger amount of assembly code compared to the other compilers. We anticipate that the research results of this study will help raise awareness of compiler selection and thus improve the quality of code produced for future scientific projects. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： program compilers

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