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Efficient and Optimized Geospatial Data Representation in Blockchain-Based Land Administration 9th

Efficient and Optimized Geospatial Data Representation in Bl...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Tahar, Attoumane Mendy, Gervais Ouya, Samuel Univ Cheikh Anta Diop Dakar Ecole Super Politech Dakar Senegal

ISBN: (纸本)9789819735617;9789819735624

The intersection of blockchain technology with geospatial data is reshaping e-governance, especially in the realm of land administration systems. This paper delves into the transformative potential of integrating geographical data into blockchain for secure, transparent, and tamper-proof land registries and cadastral data. These systems provide a robust foundation to avoid to resolve conflict in land disputes due to the immutable nature of blockchain transactions and accuracy of cadastral data in identifying land property. Our exploration encompasses various methods of encoding and storing geographical data in the blockchain, with a focus on WGS84 coordinates, Geohash, and Mapcode representations. Significantly, we address the intricate trade-offs between data size and precision, crucial considerations for efficient e-governance. In addition to surveying existing approaches, this work introduces novel geospatial data storage optimization layers, a contribution that substantially reduces data size by capitalizing on redundancy within specific representation forms. These optimization layers offer a practical and effective solution to the challenge of managing large and complex geospatial data in blockchain-based land administration systems, aligning with the core tenets of efficient e-governance. This research establishes a foundational framework for future studies in the dynamic field of blockchain land administration, emphasizing the essential need for a flexible approach to geospatial data management in e-governance systems.

关键词： Blockchain land administration Cadastral data Geospatial data storage optimization e-governance

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Mitigating Cache Pollution Attack Using Deep Learning in Named Data Networking (NDN)

Mitigating Cache Pollution Attack Using Deep Learning in Nam...

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Computing Conference

作者： Hamdi, Mohd Maizan Fishol Chen, Zhiyuan Radenkovic, Milena Univ Nottingham Malaysia Jalan Broga Semenyih 43500 Malaysia Univ Nottingham Wollaton Rd Nottingham NG8 1BB England

ISBN: (纸本)9783031622793;9783031622779;9783031622762

With the explosive growth of Internet traffic, Internet communication pays more attention to the data itself rather than where it is physically located. To better cope with Internet usage, a revolutionized shift from host-centric end-to-end communication to receiver-driven content retrieval through Information-Centric Networking (ICN) with Named Data Networking (NDN) has emerged as a big player in this new paradigm. New capabilities such as caching everywhere have made it more challenging to protect all caches from new breed of security issues especially Cache Pollution Attack (CPA). This paper presents a summary of Caching security challenges in NDN but focuses mainly on CPA. The adaptation of Machine Learning (ML) based technology is a promising emerging and proven in experimental-based simulation using ndnSIM. We show that our Python-based DL algorithm can improve the detection of CPA and outperforms some state-ofthe-art techniques that mostly works on numerical counters and probability-based algorithm.

关键词： Information-Centric Networking (ICN) Data Networking (NDN) Cache Pollution Attack (CPA) Machine Learning (ML)

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Comparison of Machine Learning-Based Intrusion Detection systems Using UNSW-NB15 Dataset

Comparison of Machine Learning-Based Intrusion Detection Sys...

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International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Sambandam, Rakoth Kandan Daniel, D. Gokulapriya, R. Vetriveeran, Divya Jenefa, J. Anuneshwar CHRIST Deemed Be Univ Dept CSE SOET Kengeri Campus Bangalore Karnataka India

ISBN: (纸本)9789819984787;9789819984794

Various machine learning classifiers have been employed recently to enhance network intrusion detection. In the literature, researchers have put forth a wide range of intrusion detection solutions. The accuracy of the machine learning classifiers' intrusion detection is limited by the fact that they were trained on dated samples. Therefore, the most recent dataset must be used to train the machine learning classifiers. In this study, UNSW-NB15, machine learning classifiers are trained using the most recent dataset. A taxonomy of classifiers based on eager and lazy learners is used to train the chosen classifiers, such as K-Means (KNN), Polynomial Features, Random Forest (RF), and Naive Bayes (NB), Linear Regression. In order to decrease the redundant and unnecessary features in the UNSW-NB15 dataset, chi-Square, a filter-based feature selection technique, is used in this study. When comparing these machine learning classifiers, performance is measured in terms of accuracy, mean squared error (MSE), precision, recall, and F1-score with or without feature selection technique.

关键词： Intrusion detection UNSW-NB15 Cyber security Machine learning

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Singular Perturbation Approximation-Based Modelling Using Frequency-Limited Balanced Gramians 5th

Singular Perturbation Approximation-Based Modelling Using Fr...

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5th International Conference on Communication and Intelligent systems (ICCIS)

作者： Kanchan, Kumari Kumar, Deepak MNNIT Allahabad EED Allahabad Uttar Pradesh India

ISBN: (纸本)9789819720521;9789819720538

In this chapter, a novel reduced-order modelling technique is presented using balanced singular perturbation approximation by developing new frequency-limited discrete-time controllability and observability Gramians. The proposed method generates stable reduced models and provides a better approximation. A reduced-order elliptic filter is designed using the suggested technique, approximating the original model reasonably well in the specified frequency interval.

关键词： Model reduction frequency-limited Gramian Singular perturbation approximation

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A Three-Layered AI-Oriented Approach for Intelligent Generation of Standardized Privacy Policies in Smart Healthcare Environments 6th

A Three-Layered AI-Oriented Approach for Intelligent Generat...

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6th International Conference on Cloud Computing and Artificial Intelligence-Technologies and Applications

作者： El Yamani, Ismail Sadki, Souad El Bakkali, Harlan Allaki, Driss Mohammed V Univ Rabat Rabat Morocco INPT Rabat Rabat Morocco

ISBN: (纸本)9783031786976;9783031786983

The adoption of cloud computing and artificial intelligence (AI) in healthcare has revolutionized patient care, necessitating robust privacy policies to safeguard individual privacy. Yet, existing policies lack standardization due to diverse actors involved. Motivated by this, we introduce in this work an AI-oriented and multilayered framework for intelligent generation of standardized privacy policies. The proposed approach actively involves stakeholders, including healthcare providers, patients, and data custodians, in the formulation of policies. To show the comprehensiveness, accuracy, and alignment of our solution with evolving regulatory frameworks, a new conversational agent called Spp-G was implemented. This inclusive approach ensures that privacy policies, shaped by collaborative efforts and input from key stakeholders, not only comply with regulatory standards but also reflect the diverse perspectives and concerns of those impacted by data-sharing practices.

关键词： Compliance Privacy Policies Standardization Data Protection Smart Healthcare Cloud Computing Artificial Intelligence

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Probabilistic Models with Invariance 15th

Probabilistic Models with Invariance

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15th International Workshop on Self-Organizing Maps, Learning Vector Quantization and Beyond (WSOM)

作者： Gepperth, Alexander Fulda Univ Appl Sci Appl Comp Sci Dept Leipzigerstr 123 D-36037 Fulda Germany

ISBN: (纸本)9783031671586;9783031671593

This proof-of-concept work generalizes the concept of invariance, as used in contrastive learning, to fully probabilistic models (such as, e.g., mixture models) that explicitly describe data distributions in an interpretable fashion, and whose main applications are density estimation (e.g., outlier detection), sampling and tractable inference. Invariance allows allows probabilistic models to operate at a lower effective model complexity, and therefore to deal with more complex (image) data. In this article, we propose iGMM, a Gaussian Mixture Model (GMM) that explicitly incorporates invariance into its loss, which is a generalization of the conventional GMM log-likelihood. When constructing hierarchies of conventional GMM and iGMM instances, we obtain invariance properties that are reminiscent of simple and complex cells in the mammalian visual cortex. We show, by experiments on the MNIST and FashionMNIST dataset, that GMM-iGMM hierarchies can faithfully sample from learned data distributions even if the iGMM is invariant to some aspects of the data, and demonstrate that outlier detection performance is strongly enhanced in GMM-iGMM hierarchies.

关键词： Contrastive Learning

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True Random Numbers from Pairs of SRAM Devices

True Random Numbers from Pairs of SRAM Devices

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Computing Conference

作者： Rios, Manuel Aguilar Partridge, Michael Jain, Saloni Cambou, Bertrand No Arizona Univ Flagstaff AZ 86011 USA

ISBN: (纸本)9783031622717;9783031622694;9783031622687

Static random-access memory (SRAM) physically unclonable functions (PUFs) have been used to design true random number generators capable of passing the National Institute of Standards and Technology (NIST) statistical test suite for randomness. These SRAM PUF-based true random number generators (TRNGs) rely on unstable cells that randomly awake as a '0' or a '1' when the power is cycled. The three issues with the previously proposed SRAM TRNGs that we aim to address are the limited number of challenge-response pairs (CRPs), the overhead required to select "flaky" cells, and the restriction of a device to support either TRNG or authentication, but not both. We present an SRAM PUF-based TRNG that passes NIST randomness tests designed with two SRAM devices and a lightweight post-processing method to enhance randomness. This design benefits from a much higher number of CRPs, does not need to identify unstable cells, and supports authentication and true random number generation. The work presented uses commercially available development boards and SRAM devices, a simple custom circuit board to connect the two, lightweight post-process, and a combination of C++ and python3 to drive the system.

关键词： TRNG Static random access memory Physical unclonable function TRNG with SRAM PUFs

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Implementation of an Information System for Document Management of the Environmental Supervision Process 13th

Implementation of an Information System for Document Managem...

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13th Computer Science Online Conference

作者： Dimas, Andres Trillo, Marco Ticona, Wilfredo Univ Tecnol Peru Lima Peru

ISBN: (纸本)9783031702846;9783031702853

Nowadays, there is great uncertainty at the international level for organizations to carry out the maintenance and preservation of the documents generated by their business processes. For this reason, it is important to be able to carry out an adequate specification of requirements in terms of document management, where it is essential to handle tools that support the development of requirements that fit any business environment. The objective of this research is to implement an information system designed for document management associated with the environmental supervision process within an auditing entity, thus facilitating a more efficient and effective management. The SCRUM framework was used, which proved to be very effective in document management. To obtain the results of the research, a satisfaction survey was applied to 69 environmental supervisors. First, the reliability of the instrument was measured by Cronbach's Alpha, the result of which was 0.938, indicating excellent internal consistency. Next, the Kolmogorov-Smirnov normality test was performed, the result of which was 0.001, indicating a non-normal distribution. Finally, the Rho Spearman test was applied, and the result was 0.511, indicating a moderate positive correlation. In conclusion, the implementation of an information system improves document management in the environmental supervision process.

关键词： Document Management Environmental Monitoring Information System Process Improvement Audit Entity SCRUM

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Attitude Control of Satellites with Reaction Wheels and Its Formation Keeping 8th

Attitude Control of Satellites with Reaction Wheels and Its ...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Johnson, Y. Thampi, M. S. Parvathy Das, Anju Binz, M. Univ Kerala Dept Futures Studies Thiruvananthapuram Kerala India Global Acad Technol Bengaluru India Visvesarayya Technol Univ CMRIT Belagavi India LMCST Thiruvananthapuram Kerala India

ISBN: (纸本)9789819713288;9789819713295

In the satellite attitude dynamics control, the reaction wheel as actuator is modeled graphically by suitably linking it with DC motor characteristics, and the attitude control is accomplished by PID and more accurately by LQR with less time. The stability properties of the attitude plant dynamics are analyzed by creating a Routh table and the general conditions for its asymptotic stability aspects are proposed. The effect of J(2) on the formation flight between two identical chief and deputy satellites in terms of change in classical orbital parameters is simulated graphically. The relative error from the initial formation is characterized in both orbital and Cartesian frames. The required amount of impulsive thrust for minimizing drift from original trajectory is calculated so as to keep the formation as such in or around a low earth orbit in the midst of J(2) perturbation effect through graphical display of error patterns.

关键词： Attitude control Feedback control PID LQR Reaction wheels

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Knowledge Graph Implementation to Enhance Micro-segmentation for Health Care

Knowledge Graph Implementation to Enhance Micro-segmentation...

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Intelligent systems Conference

作者： Pandey, Arunanshu Kumar, Shubham Singh, Nitesh ZS Associates Pune Maharashtra India

ISBN: (纸本)9783031664304;9783031664311

The field of marketing is rapidly evolving with the integration of machine learning (ML) and big data analytics. This transformation enables organizations to personalize their campaigns, gain deeper insights into consumer behavior, and enhance marketing tactics through micro-segmentation strategies. However, the dynamic nature of data poses challenges in operationalizing and maintaining micro-segments, necessitating specialized expertise and resources. To overcome this, organizations can leverage Knowledge Graphs to establish a network of linked data. This network forms the foundation for a Knowledge Graph-based machine learning pipeline, which comprises a series of steps aimed at enhancing the security, management, and performance of micro-segmentation. In this paper, we articulate the potential benefits of knowledge graph-based solutions for implementing micro-segmentation.

关键词： Knowledge graph Micro-segment Health care Clustering classification Machine learning Marketing Personalization Data analytics Consumer behavior

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