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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Florian Dehling Sebastian Koch Luigi Lo Iacono Hannes Federrath Institute of Computer Science University of Giessen Giessen Germany Security in Distributed Systems University of Hamburg Hamburg Germany

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

Keystroke dynamics are behavioral biometric traits that are frequently proposed to be used in novel authentication systems. Keystroke dynamics are based on the analysis of intervals between keystroke events originating from user input and thus directly depend on available timing information. However, modern web browsers limit the accuracy of timestamps to improve security and privacy. This study systematically investigates the impact of limited timestamp accuracies on the performance of keystroke dynamic analysis. By conducting multiple experiments with popular web browsers, we demonstrate that the minor timestamp modifications that mitigate timing side-channel attacks do not interfere with the effectiveness of keystroke dynamics analysis algorithms. Furthermore, they are surprisingly resilient to larger timestamp modifications, which results in a serious threat to users’ privacy. This research provides fundamental knowledge enabling researchers, privacy engineers, and browser vendors to study risks in keystroke dynamics-related systems and to develop mitigations against tracking methods that fingerprint users instead of devices or browsers.

关键词： Privacy Accuracy Prevention and mitigation Keystroke dynamics Authentication Side-channel attacks Robustness Browsers Timing Security

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Towards Personality Detection and Prediction using Smartphone Sensor Data

Towards Personality Detection and Prediction using Smartphon...

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Communication and computer Networking Conference (MedComNet), Mediterranean

作者： Dimitris Xenakis Eric Samikwa Jesutofunmi Ajayi Antonio Di Maio Torsten Braun Katja Schlegel Communication and Distributed Systems Institute of Computer Science University of Bern Institute of Psychology University of Bern

The emergence and adoption of mobile smartphones and their ubiquitous use by mobile phone users provide a distinctive opportunity for the collection of multi-modal sensor data. The data collected from such smartphone devices can be used to observe, recognize and predict patterns in user behaviors such as physical activity, psycho-physiological conditions such as affective state, personality traits such as extraversion, emotionality, and honesty-humility, as well as other mental health-related or psychological variables. In this work, we design and develop a system that can be used for the unobtrusive collection and storage of anonymized smartphone sensor data for personality detection and prediction. Our proposed system is developed across the two main smartphone operating systems to cover a wide range of users and to consider the available sensors across platform-dependent devices, as well as to account for distinctions in the personality traits of users of different operating systems. We present a correlation analysis and describe how the dataset collected from the smartphone sensors, which were deployed in a large-scale psychology study with about 200 participants, can be used to detect and predict different personality states.

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Privacy framework for context-aware robot development

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Paladyn 2021年第1期12卷 468-480页

作者： Heuer, Tanja Schiering, Ina Gerndt, Reinhard Department of Computer Science Ostfalia University of Applied Sciences Institute of Information Engineering Wolfenbüttel Germany Department of Computer Science Ostfalia University of Applied Sciences Institute of Distributed Systems Wolfenbüttel Germany

Privacy is an essential topic in (social) robotics and becomes even more important when considering interactive and autonomous robots within the domestic environment. Robots will collect a lot of personal and sensitive information about the users and their environment. Thereby, privacy does consider the topic of (cyber-)security and the protection of information against misuse by involved service providers. So far, the main focus relies on theoretical concepts to propose privacy principles for robots. This article provides a privacy framework as a feasible approach to consider security and privacy issues as a basis. Thereby, the proposed privacy framework is put in the context of a user-centered design approach to highlight the correlation between the design process steps and the steps of the privacy framework. Furthermore, this article introduces feasible privacy methodologies for privacy-enhancing development to simplify the risk assessment and meet the privacy principles. Even though user participation plays an essential role in robot development, this is not the focus of this article. Even though user participation plays an essential role in robot development, this is not the focus of this article. The employed privacy methodologies are showcased in a use case of a robot as an interaction partner contrasting two different use case scenarios to encourage the importance of context awareness. © 2021 Tanja Heuer et al., published by De Gruyter.

关键词： Machine design

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Fuzzy Querying in the Cloud-based Environment for Data Stream-driven Predictive Maintenance in AGV-enabled Smart Factories

Fuzzy Querying in the Cloud-based Environment for Data Strea...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Malysiak-Mrozek, Bozena Romanow, Dominik Grzesik, Piotr Benecki, Pawel Niyomugaba, Alexandre Habimana, Theodore Kostrzewa, Daniel Tokarz, Krzysztof Hung, Che-Lun Mrozek, Dariusz Silesian University of Technology Department of Distributed Systems and Informatics Devices Gliwice Poland Ines Ruhengeri - Institute of Applied Sciences Department of Computer Science Rwanda Silesian University of Technology Department of Applied Informatics Gliwice Poland Silesian University of Technology Department of Graphics Computer Vision and Digital Systems Gliwice Poland National Yang Ming Chiao Tung University Institute of Biomedical Informatics Taipei Taiwan

ISBN: (纸本)9798350362480

Fuzzy data processing enables data enrichment and increases data interpretation in industrial environments. In the cloud-based IoT data ingestion pipelines, fuzzy data processing can be implemented in several locations, closer to the IoT events gateways, stream processors, or the persistence layer before the data is visualized. Since Automated Guided Vehicles (AGV)-enabled manufacturing can produce vast amounts of data, the decision on the placement of the fuzzy data processing can be important for secondary processes performed on the enriched data, like the predictive maintenance inferencing. In this paper, we analyze two locations of fuzzy data processing in the cloud-based environment built for monitoring AGVs in smart factories - by formulating fuzzy queries against data streams on stream processing units and data at rest in a database. The querying scenarios cover fuzzy filtering with simple and complex criteria, fuzzy filtering through assignment to a linguistic variable, and joining data streams by representing joining attributes as fuzzy numbers. The experimental results show that querying the data stream can be more efficient and profitable in the scalable environment of many AGVs. However, the enrichment provided for the data at rest is also beneficial when gathering data for building future predictive maintenance models. © 2024 IEEE.

关键词： Data streams

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Blockchain Framework for Automated Life Insurance 5th

Blockchain Framework for Automated Life Insurance

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5th International Conference on Recent Innovations in Computing , ICRIC 2022

作者： Kalsgonda, Vaishali Kulkarni, Raja Kalasgonda, Shivkumar Department of Computer Science Shivraj College Maharashtra Gadhinglaj416502 India Department of Computer Studies Chhatrapati Shahu Institute of Business Education Research University Road Maharashtra Kolhapur416004 India E-Commerce Distributed Systems Seattle United States

ISBN: (纸本)9789819906000

The insurance process is done manually in India. The insurance client has to depend on an insurance agent from buying to the claim firing process which leads to wrong entry, fraudulent claims, and cost overhead on the agent’s commission. An insurance client has to maintain documents and make them available at the time of claim firing, which is very cumbersome. Blockchain smart contracts will provide a secure, automatic, cost-cutting, paperless, and real-time insurance process. This paper aims to provide a blockchain solution for life insurance claim processing, as it is the most purchased and needy insurance. An architectural illustration of a blockchain prototype is contributed to this paper. As a result, the authors found that using Hyperledger Composer, we can develop fine-grained insurance applications. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Smart contract

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Hybrid Dipper Throated and Grey Wolf Optimization for Feature Selection Applied to Life Benchmark Datasets

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computers, Materials & Continua 2023年第2期74卷 4531-4545页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Mostafa Abotaleb Abdelhameed Ibrahim Abdelaziz A.Abdelhamid D.L.Elsheweikh Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt

Selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of features using typical *** a result,a new metaheuristicsbased feature selection method based on the dipper-throated and grey-wolf optimization(DTO-GW)algorithms has been developed in this *** can result when the selection of features is subject to metaheuristics,which can lead to a wide range of ***,we adopted hybrid optimization in our method of optimizing,which allowed us to better balance exploration and harvesting chores more *** propose utilizing the binary DTO-GW search approach we previously devised for selecting the optimal subset of *** the proposed method,the number of features selected is minimized,while classification accuracy is *** test the proposed method’s performance against eleven other state-of-theart approaches,eight datasets from the UCI repository were used,such as binary grey wolf search(bGWO),binary hybrid grey wolf,and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hysteresis optimization(bHy),and binary hysteresis optimization(bHWO).The suggested method is superior 4532 CMC,2023,vol.74,no.2 and successful in handling the problem of feature selection,according to the results of the experiments.

关键词： Metaheuristics dipper throated optimization grey wolf optimization binary optimizer feature selection

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WIP: An Engaging Undergraduate Intro to Model Checking in Software Engineering Using TLA+

WIP: An Engaging Undergraduate Intro to Model Checking in So...

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Frontiers in Education (FIE) Conference

作者： Konstantin Läufer Gunda Mertin George K. Thiruvathukal Department of Computer Science Software and Systems Laboratory Loyola University Chicago Institute for Software Engineering and Programming Languages University of Lübeck

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions $(\text{TLA}^{+})$ , into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included midway into one's undergraduate studies, (3) demonstrate how to address successive “failuresy” through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding $\text { TLA }^{+}$ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in $\text { TLA }^{+}$ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudi

关键词： computer science Open Access Model checking System recovery Software Safety Logic Reliability Proposals Software engineering

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Al-Biruni Earth Radius Optimization for COVID-19 Forecasting

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computer systems science & Engineering 2023年第7期46卷 883-896页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Tatiana Makarovskikh Amal H.Alharbi Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of System Programming South Ural State University454080ChelyabinskRussia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.

关键词： COVID-19 prediction meta-heuristic optimization LSTM Al-Biruni earth radius algorithm

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Toward a reference architecture based science gateway framework with embedded e-learning support

Toward a reference architecture based science gateway framew...

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作者： Pierantoni, Gabriele Kiss, Tamas Bolotov, Alexander Kagialis, Dimitrios DesLauriers, James Ullah, Amjad Chen, Huankai Fee, David Chan You Dang, Hai-Van Kovacs, Jozsef Belehaki, Anna Herekakis, Themistocles Tsagouri, Ioanna Gesing, Sandra School of Computer Science and Engineering University of Westminster London United Kingdom Parallel and Distributed Systems Laboratory SZTAKI Budapest Hungary Institute of Astronomy Astrophysics Space Applications and Remote Sensing National Observatory of Athens Athens Greece Department of Computer Science and Engineering University of Notre Dame Notre DameIN United States

science gateways have been widely utilized by a large number of user communities to simplify access to complex distributed computing infrastructures. While science gateways are still becoming increasingly popular and the number of user communities is growing, the fast and efficient creation of new science gateways and the flexibility to deploy these gateways on-demand on heterogeneous computational resources, remain a challenge. Additionally, the increase in the number of users, especially with very different backgrounds, requires intuitive embedded e-learning tools that support all stakeholders to find related learning material and to guide the learning process. This paper introduces a novel science gateway framework that addresses these challenges. The framework supports the creation, publication, selection, and deployment of cloud-based reference architectures that can be automatically instantiated and executed even by nontechnical users. The framework also incorporates a knowledge repository exchange and learning module that provides embedded e-learning support. To demonstrate the feasibility of the proposed solution, two scientific case studies are presented based on the requirements of the plasmasphere, ionosphere, and thermosphere research communities. © 2022 The Authors. Concurrency and Computation: Practice and Experience published by John Wiley & Sons Ltd.

关键词： Ionosphere

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Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots

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Internet of Things and Cyber-Physical systems 2024年第1期4卷 19-23页

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Faculty of Computing and Data Science FLAME University Maharashtra Pune India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, offers coherent and useful replies based on analysis of large volumes of data. In this article, leading academics, scientists, distinguish researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research discusses ChatGPT capabilities and its use in the education sector, identifies potential concerns and challenges. Our preliminary evaluation shows that ChatGPT perform differently in different subject areas including finance, coding, maths, and general public queries. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023 The Authors

关键词： Machine learning

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