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Software supply chain security: a systematic literature review

International Journal of Computers and Applications 2024年第10期46卷 853-867页

作者： Reichert, Beatriz M. Obelheiro, Rafael R. Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

In recent years, software supply chain security has attracted significant research attention. This research subject is concerned both with the security of infrastructures used to build software and deliver it to end users and with the security of software that contains external dependencies such as third-party packages and libraries, and its chief goal is to ensure that no vulnerabilities are introduced in the path between developers and users. This paper presents a Systematic Literature Review to identify knowledge gaps in software supply chain security. For this, we considered studies published between 2012 and 2023 in the search engines of IEEE Xplore, ACM Digital Library, Engineering Village, Scopus, and arXiv. Of the 2051 studies obtained in the primary survey, only 85 are relevant for this research. Analyzing the studies, we observed gaps such as little discussion of software supply chains that involve cloud components, few proposals focused on the software distribution process, and a lack of use of threat modeling frameworks to help identify threats to the supply chain and validate the results. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Software packages

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Optimal resource allocation for survivable virtual infrastructures

Optimal resource allocation for survivable virtual infrastru...

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International Workshop on Design of Reliable Communication Networks (DRCN)

作者： Gustavo A. de S. Cavalcanti Rafael R. Obelheiro Guilherme Koslovski Graduate Program in Applied Computing Department of Computer Science Santa Catarina State University Graduate Program in Applied Computing Santa Catarina State University

Virtual infrastructures (VIs) consolidated the dynamic provisioning of computing and communication resources. A VI is a set of virtual machines interconnected by virtual links and switches/routers. Infrastructure providers (InPs) manage the physical substrates in which virtual resources requested by VIs (such as CPU, disk, memory, bandwidth) are reserved and allocated. Resource allocation is a complex problem that needs to satisfy different goals: users expect to run their applications on survivable VIs, while InPs aim to maximize profits, minimize costs and reduce substrate fragmentation. However, there is a dichotomy between minimizing substrate fragmentation, by co-locating VIs, and maximizing VI survivability, by sparsely allocating resources in order to decrease the impact of substrate failures. In this context, this paper discusses VI survivability and its impact on substrate fragmentation. We propose a mixed integer linear programming model to allocate resources considering the joint coordination of fragmentation and survivability. Experimental results suggest that it is possible to enhance VI survivability without significantly impacting substrate fragmentation.

关键词： Substrates Resource management Measurement Indium phosphide Servers Bandwidth Linear programming

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AxRSU- : Higher-Order m-Bit Approximate Encoders for Radix- Squarer Units

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Circuits, Systems, and Signal Processing 2024年第6期43卷 1-30页

作者： da Rosa, Morgana M. A. Paim, Guilherme da Costa, Eduardo A. C. Soares, Rafael Bampi, Sergio Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program in Microelectronics Federal University of RGS Porto Alegre Brazil Graduate Program in Electronics and Computer Engineering Catholic University of Pelotas Pelotas Brazil

Approximate computing has emerged as a design alternative to enhance design efficiency by capitalizing on the inherent error resilience observed in numerous applications. Various error-resilient and compute-intensive applications, such as signal, image and video processing, computer vision, and supervised machine learning, necessitate dedicated hardware accelerators for mean squared error estimation during runtime. In these application domains, using efficient arithmetic operators, particularly a squarer unit, represents one of the most effective strategies for low-power design. This work introduces an approximate Radix- $$2^{m}$$ squarer unit, denoted as AxRSU- $$2^{m}$$ . The proposed squarer unit employs m-bit approximate encoders to execute operations on m-bit data concurrently. The AxRSU- $$2^{m}$$ under consideration explores encoders with m equal to 2 (AxRSU-4), 3 (AxRSU-8), and 4 (AxRSU-16). These approximate encoders exhibit low complexity and diminish the necessary partial products operating on m bits simultaneously, thereby substantially enhancing energy efficiency and reducing circuit area in the AxRSU- $$2^{m}$$ . To illustrate the trade-off between error and quality in the AxRSU- $$2^{m}$$ , we apply it to an SSD (sum squared difference) hardware accelerator designed for video processing, with a square-accumulate serving as a case study. Our findings reveal a novel Pareto front, presenting eight optimal AxRSU- $$2^{m}$$ solutions that achieve accuracy levels ranging from 3.76 to 75.53%. These solutions yield energy savings ranging from 46.20 to 95.57% and circuit area reductions ranging from 37.68 to 66.73%.

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Concept, Technology, Barriers To Smart Village: A Systematic Literature Review 11

Concept, Technology, Barriers To Smart Village: A Systematic...

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11th International Conference on Cyber and IT Service Management, CITSM 2023

作者： Utamajaya, Joy Nashar Meyliana Prabowo, Harjanto Hidayanto, Achmad Nizar Ramadhan, Arief Bina Nusantara University Computer Science Department Binus Graduate Program - Computer Science Department Jakarta11480 Indonesia Telkom University School of Computing Bandung Indonesia

ISBN: (纸本)9798350305968

Smart villages that utilize digital technology are a solution to assist rural community services in meeting their needs, especially for developing countries. However, financial problems, namely the high cost of infrastructure, the size of the informal economy and governance are challenges in limiting the government's aspirations regarding the smart village concept. The presentation of this article examines the state of smart village development in developing countries, which includes conceptual understanding, motivations, drivers and barriers to smart villages. The purpose of this study is to find answers to research questions by reviewing several selected study articles. The method used was to search for selected studies and there were 60 selected studies identified from a search of five literature databases which initially contained 3394 articles. The results of the data were analyzed using synthetic analysis and thematic analysis. The results of this study found data related to Concept, Technology, Barriers To Smart Village which came from several articles by answering questions from the research, namely RQ1: How many articles from the 10 most populous countries discussed Smart Village, RQ2: What are the basic dimensions of Smart Village, RQ3: What new technologies are discussed in Smart Village digitization, RQ4: What are the Challenges in Smart Village. The results of this SLR can also later be used as a reference for further researchers to find out the background of research related to smart villages. The conclusion obtained in this research is the end of the explanation of this article concludes that there are still many shortcomings in this research and it is hoped that in the future many studies will be able to explore other aspects such as regulations and others that are not discussed in the article so that it is expected to be a reference for further researchers to examine information related to smart villages. in order to find an ideal and up-to-date con

关键词： Developing countries

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Business intelligence model to support a judge's decision making about legal situations 36

Business intelligence model to support a judge's decision ma...

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36th IEEE Central American and Panama Convention, CONCAPAN 2016

作者： Oconitrillo, Luis Raul Rodriguez De La Ossa Osegueda, Alvaro Graduate Program in Computing and Informatics University of Costa Rica San José Costa Rica School of Computer Science University of Costa Rica San José Costa Rica

ISBN: (纸本)9781467395786

Legal decision-making support is key for legal security in any legal system. This paper describes a new scope and method for Business Intelligence applied in the legal domain. We describe a legal case processing model based on the transformation of relevant data from a legal case file by a judge, to produce what we call the judge's perception of the case. That is a representation of the case that stresses (1) the relevance of the different attributes of the case, and (2) the relationships among attributes that the judge considers relevant for argumentation purposes. © 2016 IEEE.

关键词： Case based reasoning

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Predicting Abundance of Fish Species Populations in Manila Bay, Philippines Based on Ensemble Learning Approach 20

Predicting Abundance of Fish Species Populations in Manila B...

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20th International Joint Conference on Computer Science and Software Engineering, JCSSE 2023

作者： Rasdas, Sherrlyn M. Fajardo, Arnel C. Limbago, Jomel S. Graduate Program Technological Institute of the Philippines Manila Philippines College of Computing Science Information and Communication Technology -CCSICT Isabela State University-Cauayan Philippines Cavite Philippines

ISBN: (纸本)9798350300505

Manila Bay is a significant contributor to the Philippines' fish production, but its resources have been depleted due to overfishing, pollution, and damage, leading to a decline in fish catch and a shift towards less valuable species. Conventional approaches to fisheries stock assessment impose constraints on our comprehension of fish population dynamics. These limitations can be overcome through the utilization of machine learning techniques, which enable the forecasting and modeling of fisheries populations with improved accuracy and understanding. In this study, the commercial fisheries populations data collected from 2018 to 2021 in Manila Bay were used to predict the abundance of species fisheries production data using the K-NN - MLP - Logistic Regression (KNMLPR) model based on the majority voting ensemble approach. Analysis revealed that it is possible to combine the strengths of multiple models and improve overall predictive performance. The results also suggest that the k-nearest neighbors and logistic regression models have the best performance in predicting fish species population dynamics, while the neural network model shows slightly lower accuracy. This study provides valuable insights for fishery management and policymaking to support sustainable fishing practices in the region. Further research could focus on exploring additional machine learning algorithms and incorporating environmental factors to improve the prediction accuracy of the model. © 2023 IEEE.

关键词： Fisheries

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Model Prediction Using Random Forest Algorithm and Time Series Analysis Parts Distribution with in Indonesia Automotive Industry 8

Model Prediction Using Random Forest Algorithm and Time Seri...

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8th International Conference on Informatics and computing, ICIC 2023

作者： Andy Achmad, H. Ramadhan, Arief Warnars Harco Leslie, H. Budiharto, Widodo Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Telkom University School of Computing Bandung40257 Indonesia

ISBN: (纸本)9798350342604

Car spare parts are parts of a car that consist of components that form a certain unity and function, there are some parts that are damaged more often and therefore must be replaced more often. In this research, to predict the availability of spare parts using the times series moving average prediction method with random forest. The dataset used in this research is 19,068 consisting of location, transaction number, transaction date, part number, quantity and odo-km. Distribution of spare parts classified based on recapitulation of spare part distribution is RAE=54.5541% and RSE=63.8888%, distribution of spare parts based on location is RAE=55.5541% and RSE=65.2118%, maintenance based on ODO-KM is RAE=33.0949% and RSE=41.2241 % and distribution quantity RAE=33.749% and RSE=36.2317%. The results of spare part distribution analysis using the Confusion Matrix with probability accuracy are TP Rate=0.903, FP Rate=0.067, Precision=0.911, Recall=0.903, F-Measure=0.893, MCC=0.857, ROC Area=0.983 and PRC Area=0.948. The aim of this research is to determine the factors needed to build a machine learning-based spare parts distribution model, implementation, measurement and prediction in the automotive industry in Indonesia. © 2023 IEEE.

关键词： Automotive industry

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A Power-Efficient VLSI Multiplier Design Employing Radix-2m Squarer Unit and Adder Compressor

A Power-Efficient VLSI Multiplier Design Employing Radix-2m ...

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Leonardo Antonietti Morgana Da Rosa Rodrigo Lopes Eduardo Da Costa Rafael Soares Graduate Program on Computing - Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing - Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798350377200

ISBN: (纸本)9798350377217

Multipliers are pivotal in numerous applications, including digital signal processing, image processing, and video processing. Nonetheless, their operation substantially increases power consumption for these applications. Therefore, applying strategies that can reduce power in this arithmetic operator is paramount. This paper presents a novel approach to optimize arithmetic units, focusing on multiplier units, through the integration of the Radix- $2^{m}$ squarer unit (RSU) and 4–2 adder/subtractor compressor (AC). Compared to the state-of-the-art, the proposed multiplier unit, termed MRSU (multiplier unit RSU-based), offers significant area-and energy-savings. The synthesis results show remarkable improvements in the MRSU Dadda 4–2 architecture, which achieves 14.35× more energy-savings for 8 bits, 4.87× for 16 bits, and 2.22× for 32 bits compared to the multiplier unit automatically selected by the logic-synthesis tool. Furthermore, compared to the Booth multiplier with the Dadda compression tree, MRSU Dadda 4–2 exhibits 1.67× more energy-savings for 8 bits, 1.93× for 16 bits, and 1.95× for 32 bits.

关键词： Image coding Power demand Focusing Digital signal processing Computer architecture Very large scale integration Energy efficiency Electronic circuits Adders Arithmetic

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CompressedMediQ: Hybrid Quantum Machine Learning Pipeline for High-Dimensional Neuroimaging Data

CompressedMediQ: Hybrid Quantum Machine Learning Pipeline fo...

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Acoustics, Speech, and Signal Processing Workshops (ICASSPW), IEEE International Conference on

作者： Kuan-Cheng Chen Yi-Tien Li Tai-Yu Li Chen-Yu Liu Po-Heng Henry Lee Cheng-Yu Chen Department of Electrical and Electronic Engineering Imperial College London London UK Centre for Quantum Engineering Science and Technology (QuEST) Imperial College London London UK Translational Imaging Research Center Taipei Medical University Hospital Taipei Taiwan Research Center for Neuroscience Taipei Medical University Taipei Taiwan Ph.D. Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University Taipei Taiwan National Center for High-Performance Computing NARlabs Hsinchu Taiwan Graduate Institute of Applied Physics National Taiwan University Taipei Taiwan Department of Medical Imaging Taipei Medical University Hospital Taipei Taiwan Department of Radiology National Defense Medical Center Taipei Taiwan Department of Radiology School of Medicine College of Medicine Taipei Taiwan

ISBN: (数字)9798331519315

ISBN: (纸本)9798331519322

This paper introduces CompressedMediQ, a novel hybrid quantum-classical machine learning pipeline specifically developed to address the computational challenges associated with high-dimensional multi-class neuroimaging data analysis. Standard neuroimaging datasets, such as large-scale MRI data from the Alzheimer’s Disease Neuroimaging Initiative and Neuroimaging in Frontotemporal Dementia, present significant hurdles due to their vast size and complexity. CompressedMediQ integrates classical HPC nodes for advanced MRI pre-processing and Convolutional Neural Network (CNN)-PCA-based feature extraction and reduction, addressing the limited-qubit availability for quantum data encoding in the NISQ era. This is followed by Quantum Support Vector Machine (QSVM) classification. By utilizing quantum kernel methods, the pipeline optimizes feature mapping and classification, enhancing data separability and outperforming traditional neuroimaging analysis techniques. Experimental results highlight the pipeline’s superior accuracy in dementia staging, validating the practical use of quantum machine learning in clinical diagnostics. Despite the limitations of NISQ devices, this proof-of-concept demonstrates the transformative potential of quantum-enhanced learning, paving the way for scalable and precise diagnostic tools in healthcare and signal processing.

关键词： Neuroimaging Support vector machines Quantum computing Accuracy Magnetic resonance imaging Pipelines Machine learning Medical services Signal processing Standards

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Exploring Approximate Adders for an Energy-Efficient Pre-Processing Pan-Tompkins Algorithm VLSI Design

Exploring Approximate Adders for an Energy-Efficient Pre-Pro...

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Symposium on Integrated Circuits and Systems Design (SBCCI)

作者： Léo Ribeiro Morgana M. A. Rosa Rafael Soares Eduardo Costa Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9798350391695

ISBN: (纸本)9798350391701

This work explores a set of approximate adders (COPY adder, error-tolerant adder - ETA, lower-part OR adder - LOA, truncation - Trunc, and approximate parallel prefix adder - AxPPA) to enhance a VLSI design for ECG signal preprocessing based on Pan-Tompkins algorithm (AxPTA) to improve energy efficiency and QRS complex detection. Validation with the MIT-BIH database confirms that the AxPTA design maintains excellent sensitivity and positive predictivity with reduced energy consumption and circuit area. The AxPTA with AxPPA achieves a 10.22% reduction in circuit size and saves 85.06% energy, with an acceptable 1.32% precision deviation. These results suggest that the AxPPA significantly boosts energy efficiency in the AxPTA design for ECG analysis, supporting the development of portable devices for continuous heart monitoring and cardiovascular disease prevention.

关键词： Energy consumption Sensitivity Databases Energy conservation Electrocardiography Very large scale integration Approximation algorithms Energy efficiency Adders System analysis and design

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