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IEEE/ACM 11th international conference on Mobile Software Engineering and systems (MOBILESoft)

作者： Inayoshi, Hiroki Kakei, Shohei Saito, Shoichi Nagoya Inst Technol Nagoya Aichi Japan

ISBN: (纸本)9798400705946

Major app stores have introduced privacy labels (e.g., Google Play's data safety section since July 2022), requiring app developers to provide their privacy disclosures, including data types collected and shared by their apps and third-party SDKs they use. third-party SDK providers have published guidance pages instructing app developers what data types their SDKs use and thus must be declared to the data safety section. Availability and correctness of the guidance pages are critical issues but have yet to receive any attention. this paper presents the first study of the guidance pages. *** attempted to collect the guidance pages of 175 commercial SDKs widely used in Android apps and did not obtain them for 63% of the SDKs, suggesting that the majority of them have not provided guidance pages. Further, we develop a system that detects inconsistencies between the guidance pages and the actual data collection of SDKs. It uses machine learning and dynamic taint analysis to extract privacy practices from the guidance pages and SDKs and analyzes the outcomes to detect the critical gap. We construct datasets of 47 guidance pages and 43 SDKs' 159 sample apps and evaluate the system. the system uncovered discrepancies related to location and identifiers in the guidance pages of eight SDKs. We also evaluate the machine learning model's accuracy for unknown guidance page contents. the results show that the model performs satisfactorily for updated guidance pages, and the accuracy for newly posted ones increases as the model learns more. this study exposes the critical issues of the guidance pages and also contributes to tools and datasets for facilitating further research on guidance pages and privacy labels.

关键词： Android third-party SDK data safety section consistency analysis

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A Fast Recommendation Algorithm for Data Streams Based on Differential Privacy 11

A Fast Recommendation Algorithm for Data Streams Based on Di...

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11th international conference on Advanced Cloud and Big Data, CBD 2023

作者： Guo, Chang Wang, Xiujun Zheng, Xiao Shao, Xun Mo, Lei Yang, Gaoming AnHui University of Technology School of Computer Science and Technology Ma'Anshan243032 China Toyohashi University of Technology Department of Electrical and Electronic Information Engineering Aichi4418580 Japan Anhui University of Science and Technology School of Computer Science and Engineering Huainan232001 China

ISBN: (纸本)9798350345346

Recommendation systems are an essential tools for people to access interesting information from vast amounts of data and have a wide range of applications. However, current recommendation algorithms encounter persistent challenges, including significant time overhead and limitations in safeguarding user privacy effectively. these challenges stem from their reliance on static clustering algorithms to compress data streams. To tackle these issues, we introduce the Fast Recommendation Algorithm based on Differential Privacy (FRDP) for data streams. FRDP leverages the growing learning vector quantization technique for clustering and compressing data streams in a single pass. Additionally, FRDP dynamically introduces noise based on clustering error to protect individuals' privacy while using differentially private clustering data for recommendation analysis. Finally, we compare the FRDP algorithm with the best existing recommendation algorithms based on two real datasets. Extensive experimental results demonstrate that, while maintaining similar recommendation accuracy under the same privacy protection constraints, the FRDP algorithm achieves substantial time savings, with an average reduction in running time ranging from 55.82% to 59.89%. © 2023 IEEE.

关键词： Recommender systems

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Exploring Milk Productivity and Energy Output Dynamics across Lactation Periods in Automatic Milking systems through Multi-Algorithm Clustering 11

Exploring Milk Productivity and Energy Output Dynamics acros...

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11th European conference on Precision Livestock Farming

作者： Rebuli, K. Brotto Ozella, L. Masia, F. Vrieze, E. Giacobini, M. Department of Veterinary Sciences University of Torino TO Grugliasco Italy Farm Management Support Lely International N.V. Maassluis Netherlands

ISBN: (纸本)9791221067361

Automatic Milking systems (AMSs) are pivotal in Precision Dairy Farming. these systems collect extensive data on cow level, milk production, and herd management at each milking event. Machine Learning (ML) methods are well-suited for analyzing the large amount of data generated by AMSs, providing tools to support herd management data-driven decisions. One critical decision in dairy farming is whether to retain a cow for future lactation periods, a choice made at insemination time but whose outcome is observed only in subsequent lactation cycles. ML can assist decision-makers by identifying cows with potential for maintaining or increasing milk production. this study applies Multi-Algorithm Clustering analysis to assess the continuity of Productivity Groups (PGs), defined by Low and High milk yield and quality, over seven lactation periods across 16 AMS farms. Farms with more stable PGs were able to retain more cows for future lactation periods, although higher daily milk production was observed in farms in which Low PGs increased over time. In contrast, stable PG farms exhibited higher protein content across all lactation periods, with higher Fat-Protein Corrected Milk in the third lactation. Significant differences between stable and non-stable PG farms were primarily observed in the first lactation, when farms with non-stable PGs had smaller delivery ages and refusals by day, but higher milkings by day and days in milk. these findings suggest that cows on these farms may experience increased pressure during the first lactation, potentially leading to a greater decline in productivity and herd size over subsequent lactation periods. © 2024 11th European conference on Precision Livestock Farming. All rights reserved.

关键词： Information management

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A calculus for modular loop acceleration and non-termination proofs

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international JOURNAL ON SOFTWARE tools FOR TECHNOLOGY TRANSFER 2022年第5期24卷 691-715页

作者： Frohn, Florian Fuhs, Carsten Max Planck Inst Informat Saarland Informat Campus Saarbrucken Germany Rhein Westfal TH Aachen LuFG Informat 2 Aachen Germany Birkbeck Univ London Dept Comp Sci & Informat Syst London England

Loop acceleration can be used to prove safety, reachability, runtime bounds, and (non-)termination of programs. To this end, a variety of acceleration techniques have been proposed. However, so far all of them have been monolithic, i.e., a single loop could not be accelerated using a combination of several different acceleration techniques. In contrast, we present a calculus that allows for combining acceleration techniques in a modular way and we show how to integrate many existing acceleration techniques into our calculus. Moreover, we propose two novel acceleration techniques that can be incorporated into our calculus seamlessly. Some of these acceleration techniques apply only to non-terminating loops. thus, combining them with our novel calculus results in a new, modular approach for proving non-termination. An empirical evaluation demonstrates the applicability of our approach, both for loop acceleration and for proving non-termination.

关键词： Loop acceleration Non-termination Integer transition systems Program verification Static analysis

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Digital tools of the Economic Security System of construction Companies 11th

Digital Tools of the Economic Security System of Constructio...

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11th international Scientific conference on Digital Transformation of the Economy: Challenges, Trends and New Opportunities, ISCDTE 2024

作者： Svetkina, I.A. Gorbunova, O.A. Kravchenko, O.V. Samara State University of Economics Samara Russia Samara State Technical University Samara Russia

ISBN: (纸本)9783031656613

the contribution presents the results of a study of the digitalization processes of construction companies implementing projects. the authors analyzed the problematic issues of ensuring the continuity of the activities of these entities in an uncertain economic environment. the paper notes that currently, in order to ensure the economic security of the organization and partners associated with the construction project, the need for investment in digital technologies cannot be underestimated. It depends on them to implement the project in accordance with the requirements, increase labor productivity, and ensure optimal rates of construction of facilities. construction companies need new design and modeling tools, updating the technical base, and qualified personnel at the highest, middle and working levels. the development of the range of digital solutions for construction is significantly influenced by regulatory measures taken by the Russian government agencies. Interaction with expert and industry bodies is being transferred to the digital space, electronic document management is being introduced, ensuring communication between all subjects of the construction process. Also, one of the strategic directions is to evaluate the dynamics of production of residential and industrial construction using a digital twin. this allows for synchronization with logistics, transport and social projects and existing structures. Digital transformation is a tool to accelerate the construction cycle, making it more transparent and of high quality. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Investments

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Automated Verification for Real-Time systems via Implicit Clocks and an Extended Antimirov Algorithm 29th

Automated Verification for Real-Time Systems via Implicit Cl...

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29th international conference on tools and algorithms for the construction and analysis of systems (TACAS)

作者： Song, Yahui Chin, Wei-Ngan Natl Univ Singapore Sch Comp Singapore Singapore

ISBN: (纸本)9783031308222;9783031308239

the correctness of real-time systems depends both on the correct functionalities and the realtime constraints. To go beyond the existing Timed Automata based techniques, we propose a novel solution that integrates a modular Hoare-style forward verifier with a term rewriting system (TRS) on Timed Effects (TimEffs). the main purposes are to: increase the expressiveness, dynamically manipulate clocks, and efficiently solve clock constraints. We formally define a core language C-t, generalizing the real-time systems, modeled using mutable variables and timed behavioral patterns, such as delay, timeout, interrupt, deadline. Secondly, to capture real-time specifications, we introduce TimEffs, a new effects logic, that extends regular expressions with dependent values and arithmetic constraints. thirdly, the forward verifier reasons temporal behaviors - expressed in TimEffs - of target C-t programs. Lastly, we present a purely algebraic TRS, i.e., an extended Antimirov algorithm, to efficiently check language inclusions between TimEffs. To demonstrate the feasibility of our proposal, we prototype the verification system;prove its soundness;report on case studies and experimental results.

关键词： Real time systems

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A Combined ELM and CNN Model Architecture for Accurate Viral Family DNA Classification 11

A Combined ELM and CNN Model Architecture for Accurate Viral...

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11th IEEE international conference on Intelligent Computing and Information systems, ICICIS 2023

作者： El-Tohamy, Ahmed Maghawry, Huda Amin Badr, Nagwa Ain Shams University Faculty of Computer and Information Sciences Information Systems Department Cairo Egypt

ISBN: (纸本)9798350322101

Viruses are an important group of pathogens that can cause a wide range of diseases in humans and other organisms. Accurate and efficient classification of viruses is crucial for the development of diagnostic tools and therapies, as well as for understanding the evolutionary relationships and diversity of these viruses. there has been a surge of interest in the application of machine learning and deep learning approaches for DNA viral classification in recent years. these methods can effectively handle the large and complex datasets that are often encountered in this context. A deep learning architecture is proposed in this study for the classification of DNA virus into its respective family. the model was trained on a newly collected dataset that covers a wide variety of viral family genomes. the architecture utilizes Convolutional Neural Networks (CNN) as a feature extraction layer and Extreme Learning Machines (ELMs) as a classification layer, using k-mer encoding. the use of CNN as a feature extraction layer and ELMs for classification allows for the effective and efficient classification of DNA virus into their diverse virus families. the proposed architecture was tested on a dataset obtained in FASTA format, as provided by the National Center for Biotechnology Information (NCBI). the dataset consists of the major 10 virus families. the architecture achieved an accuracy of 94.54% on the test set, with a confusion matrix showing strong performance across all 10 virus families. A comparative analysis was also performed with other k-mer based machine learning algorithms and the proposed architecture achieved the highest accuracy amongst them. © 2023 IEEE.

关键词： Deep neural networks

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Stack-Aware Hyperproperties 29th

Stack-Aware Hyperproperties

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29th international conference on tools and algorithms for the construction and analysis of systems (TACAS)

作者： Bajwa, Ali Zhang, Minjian Chadha, Rohit Viswanathan, Mahesh Univ Illinois Urbana IL 61801 USA Univ Missouri Columbia MO 65212 USA

ISBN: (纸本)9783031308222;9783031308239

A hyperproperty relates executions of a program and is used to formalize security objectives such as confidentiality, non-interference, privacy, and anonymity. Formally, a hyperproperty is a collection of allowable sets of executions. A program violates a hyperproperty if the set of its executions is not in the collection specified by the hyperproperty. the logic HyperCTL* has been proposed in the literature to formally specify and verify hyperproperties. the problem of checking whether a finite-state program satisfies a HyperCTL* formula is known to be decidable. However, the problem turns out to be undecidable for procedural (recursive) programs. Surprisingly, we show that decidability can be restored if we consider restricted classes of hyperproperties, namely those that relate only those executions of a program which have the same call-stack access pattern. We call such hyperproperties, stack-aware hyperproperties. Our decision procedure can be used as a proof method for establishing security objectives such as noninference for recursive programs, and also for refuting security objectives such as observational determinism. Further, if the call stack size is observable to the attacker, the decision procedure provides exact verification.

关键词： Hyperproperties Temporal Logic Recursive Programs Model Checking Pushdown systems Visibly Pushdown Automata

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Application of BIM Collaborative Design Technology in Intelligent Buildings for Prefabricated Steel Structures 11th

Application of BIM Collaborative Design Technology in Intell...

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11th international conference on Applications and Techniques in Cyber Intelligence, ATCI 2023

作者： Wang, Heng Zhu, Wei Du, Yansheng Zhang, Wenling Zhou, Hao Wang, Rui Li, Wenhao Zhang, Pengfei Huang, Xiaokang Cao, Zhiliang Bao, Bingkai China Construction Science and Industry Corporation LTD. Shenzhen518000 China School of Civil Engineering Tianjin University Tianjin300072 China Department of Civil Engineering School of Civil Engineering Tsinghua University Beijing100084 China College of Civil Engineering Taiyuan University of Technology Taiyuan030024 China LTD. Tianjin300000 China

In recent years, the development of prefabricated buildings has been significantly promoted by China's policy initiatives focusing on innovation, green development, and industrialization in the construction sector. this paper explores the application of Building Information Modeling (BIM) collaborative design technology in the construction of intelligent buildings with prefabricated steel structures. Using the Zhangjiawo Sports Park Project as a case study, we detail the integration of digital design, industrial production, and intelligent construction methodologies. the project leverages BIM for precise modeling (LOD400), optimizing construction through collision analysis, and enhancing natural lighting and ventilation via simulation tools. the prefabrication process employs advanced steel structure manufacturing techniques and intelligent logistics, while on-site construction utilizes automated systems, such as ALC wall panel installation robots. these innovations not only improve construction efficiency and safety but also align with national low-carbon and sustainable development goals. the findings provide valuable insights into the benefits and implementation strategies of BIM and intelligent construction technologies in prefabricated building projects. © 2024 the Authors. Published by Elsevier B.V.

关键词： Building Information Model

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Improving Requirements in Model-Based systems Engineering through Multi-layer Goal Models 11th

Improving Requirements in Model-Based Systems Engineering Th...

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11th international conference on Model-Driven Engineering and Software Development (MODELSWARD)

作者： Ponsard, Christophe Darimont, Robert CETIC Res Ctr Charleroi Belgium Respect IT SA Louvain La Neuve Belgium

ISBN: (纸本)9783031663383;9783031663390

Model-driven methods are increasingly being adopted in many industrial sectors to support the design and development of software intensive systems. Many available model-based system engineering methods support progressive levels of functional decomposition, enabling to reason at different levels of granularity. In contrast, requirements modelling tends to stay quite monolithic in nature despite the ability to provide different forms of refinement and traceability. this work analyses how to better structure requirements across multiple levels in the scope of goal-oriented requirements engineering to provide better support for decomposition and analysis of inner subcomponents or the outer system of systems. We introduce the explicit notion of system and show how to integrate it in the widely used KAOS and i* frameworks. Our extension is prototyped on available tools and validated on two complementary case studies of a meeting scheduler and a smart city.

关键词： systems engineering MBSE Goal-oriented modelling Requirements Refinements

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