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International conference on Network and Service Management

作者： Kokthay Poeng Laurent Schumacher Faculty of Computer Science University of Namur Namur Belgium

ISBN: (数字)9783903176669

ISBN: (纸本)9798331505158

In the cloud computing era, cross-cloud deployments enable organizations to operate across multiple autonomous cloud platforms, offering advantages such as resilience, cost and performance optimization. However, lateral movement attacks, which are critical in the progression of Advanced Persistent threats (APTs), pose significant challenges in this environment. this paper proposes a Lateral Movement Identification (LMD) system to identify lateral movement attacks in cross-cloud containerized environments. the LMD system utilizes Dynamic Information Flow Tracking (DIFT) and extended Berkeley Packet Filter (eBPF) sandboxes to monitor and associate network traffic within container host kernel without kernel modification. Our experiments validate the efficiency of the LMD system in tracking ingress and egress traffic, differentiating between multiple simultaneous connections, and maintaining minimal performance overhead.

关键词： Cloud computing Costs Tracking Telecommunication traffic Organizations Information filters Kernel optimization Monitoring Resilience

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State Entropy optimization in Markov Decision Processes

State Entropy Optimization in Markov Decision Processes

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IEEE International conference on Automation Science and Engineering (CASE)

作者： Shuai Ma Li Xia Qianchuan Zhao School of Business Sun Yat-Sen University Guangzhou China Department of Automation Tsinghua University Beijing China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

We examine the state entropy optimization in both discounted and average Markov decision processes (MDPs). We suggest a total entropy optimization in a discounted setting, and solve both the entropy rate optimization and the total discounted entropy optimization with iterative algorithms. An optimal solution to entropy maximization ensures that the system remains as unpredictable as possible. Previous works apply nonlinear programming methods to either the total entropy or entropy rate optimizations. We present both value iteration and policy iteration for synthesizing entropy optimizing policies in ergodic MDPs. For each state in each iteration, the action distribution is optimized with convex optimization in entropy maximization problems. We illustrate the validity of the proposed algorithms in a numerical experiment.

关键词： Heuristic algorithms Markov decision processes Reinforcement learning Programming Entropy Convex functions Dynamic programming optimization Standards Robots

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20th International conference on Information Processing and Management of Uncertainty in Knowledge-Based systems, IPMU 2024

20th International Conference on Information Processing and ...

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20th International conference on Information Processing and Management of Uncertainty in Knowledge-Based systems, IPMU 2024

ISBN: (纸本)9783031740022

the proceedings contain 33 papers. the special focus in this conference is on Information Processing and Management of Uncertainty in Knowledge-Based systems. the topics include: Graphical Causal Models with Discretized Data and Background Information;enhancing the Intelligibility of Boolean Decision Trees with Concise and Reliable Probabilistic Explanations;towards an Interpretable Fuzzy Approach to Experimental Design;from Default to Analogical and Paralogical Reasoning. Logics of Pairs and their Multiple-Valued Extensions;lot Sizing Problem Under Lead-Time Uncertainty;forced Periodic Optimal Scheduling Policy for Graph Reinforcement Learning;similarity Relations Based Numerical Algorithm for Solving Maximin Problems;possibilistic Approach for Meta-analysis;Dual Resource Flexible Job Shop Scheduling Problems: the xBTF Algorithm;information Retrieval Using Fuzzy Fingerprints;Handling Veracity of SVM Predictions;interval Criterion-Based Evidential Set-Valued Classification;analysis of the φ-Index of Inclusion Restricted to a Set of Indexes;enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search;from Quantifying and Propagating Uncertainty to Quantifying and Propagating Both Uncertainty and Reliability: Practice-Motivated Approach to Measurement Planning and Data Processing;extending Idioms for Bayesian Network Construction with Qualitative Constraints;optimizing Causal Interventions in Hybrid Bayesian Networks: A Discretization, Knowledge Compilation, and Heuristic optimization Approach;visualization of Preference Matrices for Labeled Objects;assessing Causal Graph Uncertainty and Optimized Multivariate Discretization Strategy;exploring Word Embedding in modeling Risk Perception;similarity of Concepts in Weighted Knowledge Graphs;evidential Linear Regression for Soft Detrended Fluctuation Analysis;COPILS: COmParIson of Linguistic Summaries;groupoids in Categories of Fuzzy Topological Spaces with Continuous Fuzzy Relations;preface;On the Use of Mo

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Cooperative PSO Heuristic for system Identification Beyond MSE Boundary in Ad-Hoc Network

Cooperative PSO Heuristic for System Identification Beyond M...

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IEEE SSD International Multi-conference on systems, Signals and Devices

作者： Ali M. Almohammedi Mohamed Deriche Electrical Engineering Department King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Artificial Intelligence Research Centre Ajman University UAE

Cooperative topology of Participle Swarm optimization (PSO) heuristic (CPSO) is implemented for system identification over ad-hoc Networks. the main achievement is the development of PSO heuristic for system identification instead of the conventional diffusion topology of the Least Mean Square called DLMS algorithm which reveals a significant improvement in terms of the Mean Square Error (MSE). the CPSO heuristic demonstrates an important MSE convergence result beyond the theoretical boundary of noise variance. In the aggregation stage, each sensor exchanges the local best objective function along with the related local best estimate to near-by neighboring sensors. the simulations indicate that the developed CPSO approach achieves extraordinary MSE and MSD improvements against existing DLMS algorithms when the input block size and population are increased.

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A Distributed Multimodel Platform to Cosimulate Multienergy systems in Smart Buildings

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2021年第5期57卷 4428-4440页

作者： Schiera, Daniele Salvatore Barbierato, Luca Lanzini, Andrea Borchiellini, Romano Pons, Enrico Bompard, Ettore Patti, Edoardo Macii, Enrico Bottaccioli, Lorenzo Politecn Torino Energy Ctr Lab I-10129 Turin Italy Politecn Torino Dept Energy I-10129 Turin Italy Politecn Torino Dept Control & Comp Engn I-10129 Turin Italy Politecn Torino Interuniv Dept Reg & Urban Studies & Planning I-10129 Turin Italy

Nowadays, buildings are responsible for large consumption of energy in our cities. Moreover, buildings can be seen as the smallest entity of urban energy systems. On these premises, in this article, we present a flexible and distributed cosimulation platform that exploits a multimodeling approach to simulate and evaluate energy performance in smart buildings. the developed platform exploits the Mosaik cosimulation framework and implements the functional mock-up interface standard in order to couple and synchronize heterogeneous simulators and models. the platform combines in a shared simulation environment: 1) the thermal performance of the building simulated with EnergyPlus;2) a heat pump integrated with a proportional-integral-derivative control strategy modeled in Modelica to satisfy the heating demand of the building;3) an electrical energy storage system modeled in MATLAB Simulink;and 4) different Python models used to simulate household occupancy, electrical loads, photovoltaic production, and smart meters, respectively. the platform guarantees a plug-and-play integration of models and simulators, in which one or more models can be easily replaced without affecting the whole simulation engine. Finally, we present a demonstration example to test the functionalities, capability, and usability of the developed platform and discuss future developments of our framework.

关键词： Buildings Load modeling Analytical models Tools Resistance heating Usability Solid modeling Building energy system (BES) cosimulation cyber-physical multienergy system distributed computing electrical energy storage functional mock-up interface (FMI) heat pump Mosaik photovoltaics (PV) system simulation

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20th International conference on Grid, Cloud, and Cluster Computing, GCC 2024, 3rd International conference on Quantum Technologies, ICEQT 2024, and 21st International conference on modeling, Simulation and Visualization Methods, MSV 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

20th International Conference on Grid, Cloud, and Cluster Co...

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20th International conference on Grid, Cloud, and Cluster Computing, GCC 2024, 3rd International conference on Quantum Technologies, ICEQT 2024, and 21st International conference on modeling, Simulation and Visualization Methods, MSV 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

ISBN: (纸本)9783031858833

the proceedings contain 20 papers. the special focus in this conference is on Grid, Cloud, and Cluster Computing. the topics include: Scientific Workflow Provenance Management: system Requirements and a Reference Architecture;Enhancing Data Security with Decentralized Cloud Storage: An IPFS Approach;learning Robust Observable to Address Noise in Quantum Machine Learning;evaluating Cost-Effective Reconfigurable Hardware for Quantum Simulation;an Efficient Quantum Solver for Multidimensional Partial Differential Equations;explaining the Design of the Quantum Fourier Transform;Optimizing Depth of Quantum Circuit for Generating GHZ States;a Comparative Analysis of Hybrid-Quantum Classical Neural Networks;NRQNN: the Role of Observable Selection in Noise-Resilient Quantum Neural Networks;studying the Impact of Quantum-Specific Hyperparameters on Hybrid Quantum-Classical Neural Networks;Eclipse Qrisp QAOA: Description and Preliminary Comparison with Qiskit Counterparts;federal Cloud Computing Adoption Case Study: A Retrospective Analysis as a Precursor to Optimized Quantum Adoption Methodologies;integrating Secure Quantum Digital Signature into Quantum Communications;methodology to Accelerate Federal Agency Adoption of Quantum Technologies;understanding Public Policy Effects on Alcohol-Related Behaviors and Outcomes Using system Dynamics;Performance Investigation of Small UAV Attitude Control Based on Optimized Nonlinear Dynamic Inversion;Prediction of 1st Year Registration Renewal of General-Use JP Domain Names with the Use of Machine Learning;data Clustering and Visualization with Recursive Max k-Cut Algorithm.

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Research on DoS Attack Traffic Detection for Industrial Control system

Research on DoS Attack Traffic Detection for Industrial Cont...

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International conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Hong Chen Sisi Liu Xiaoshu Yuan Yuanyuan Huang Li Feng Energy equipment Cyber security Key Laboratory of Sichuan Province Chengdu China Chengdu University of Information Technology

the rapid development of the Internet has brought convenience to the industrial control system, but also brought serious security problems of network attacks. DoS attack is the most common network traffic attack. the traditional abnormal traffic detection method has the problems of long model training time and high false alarm rate. Aiming at these problems, this paper proposes an optimization algorithm based on decision tree CART, as well as feature coding and feature classification of data. the experimental results show that the decision tree model has better performance than other machine learning models, and achieves a higher accuracy of 98.2 %.

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Open-Source CFD Simulation of Magnetic Rotating Swimmers with Experimental Validation

Open-Source CFD Simulation of Magnetic Rotating Swimmers wit...

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IEEE International conference on Automation Science and Engineering (CASE)

作者： Yitong Lu Jocelyn Ramos Deeksha Sarda Dipan J. Shah Aaron T. Becker Julien Leclerc Electrical & Computer Engineering University of Houston TX USA Mechanical Engineering University of Houston TX USA School of Engineering Medicine Texas A&M University Houston USA Houston Methodist DeBakey Heart & Vascular Center TX USA

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Many potential medical applications for magnetically controlled tetherless devices inside the human body have been proposed, including procedures such as biopsies, blood clot removal, and targeted drug delivery. these devices are capable of wirelessly navigating through fluid-filled cavities in the body, such as the vascular system, eyes, urinary tract, and ventricular system, to reach areas difficult to access via conventional methods. Once at their target location, these devices could perform various medical interventions. this paper focuses on a special type of magnetic tetherless device called a magnetic rotating swimmer, which has internal magnets and propeller fins with a helical shape. To facilitate the design process, an automated geometry generation program using OpenSCAD was developed to create the swimmer design, while computational fluid dynamics simulations using OpenFOAM were employed to calculate the propulsive force produced by the swimmer. Furthermore, an experimental approach is proposed and demonstrated to validate the model. the results show good agreement between simulations and experiments, indicating that the model could be used to develop an automatic geometry optimization pipeline for rotating swimmers.

关键词： Geometry Magnetohydrodynamics Targeted drug delivery Computational modeling Computational fluid dynamics Pipelines Force Magnetic devices Surgery optimization

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optimization of GIS modules for processing data of gravity monitoring of subsoil in the Republic of Kazakhstan 20

Optimization of GIS modules for processing data of gravity m...

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20th International conference Geoinformatics: theoretical and Applied Aspects

作者： Nazirova, A.B. Dubovenko, Y.I. Abdoldina, F.N. Kuzminets, M.P. International University of Information Technologies Almaty Kazakhstan Institute of Geophysics by S. I. Subbotin name of National Academy of Sciences of Ukraine Kyiv Ukraine Institute of Information and Telecommunication Technologies Almaty Kazakhstan National Transport University Kyiv Ukraine

ISBN: (纸本)9789462823815

Purpose. the work of a GIS shell with a web interface is analyzed aimed to support oil-and-gas reservoirs during its development by processing the data from gravity variations monitoring. the shell is implemented based on Post¬GIS and tested on the example of processing monitoring data for one oil and gas reservoir. Method. Data processing involves a number of procedures, such as data averaging along the measurement profile by the moving average technique with the calculation of residual local anomalies, the analytical approximation of the gravity curve by a trend, the calculation of the residual field and differentiation (i.e. calculation of its horizontal and vertical gradients). Data modeling means the solution of direct gravimetry problems by the fitting. To optimize the model, mathematical models of the medium were calculated using the simulated annealing technique. Results. the GIS shell GravGIS has been developed to solve applied problems of processing monitoring data for oil-and-gas reservoirs of Kazakhstan. It provides for the calculation of gravity transformants such as first and second derivatives, horizontal and vertical gradients, mathematical norms, etc. For modeling the oil-and-gas reservoir in this shell, GeoM computing unit is introduced for solution of direct problems of gravimetry. A 1-D solution to the problem by the method of simple iteration was developed. Solutions of direct problems of gravimetry by the simulated annea¬ling technique are tested for gravitating objects specified by elementary approximating bodies (sphere, ledge, hori¬zontal and vertical prism, etc.) and are consistent with solutions of these problems by other methods. Practical value. the system allows combining data from monitoring gravity and other geophysical methods. Inte¬gration of these data and gravity inversion with the constraints of a priori parameters of the geological media allows making optimal decisions. © 2021 20th International conference Geoinformatics: theore

关键词： Monitoring

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From monolithic to microservice architecture: an automated approach based on graph clustering and combinatorial optimization

From monolithic to microservice architecture: an automated a...

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Working IEEE/IFIP conference on Software Architecture

作者： Gianluca Filippone Nadeem Qaisar Mehmood Marco Autili Fabrizio Rossi Massimo Tivoli Department of Information Engineering Computer Science and Mathematics University of L'Aquila L'Aquila Italy

Migrating from a legacy monolithic system to a microservice architecture is a complex and time-consuming process. Software engineers may strongly benefit from automated support to identify a high-cohesive and loose-coupled set of microservices with proper granularity. the automated approach proposed in this paper extracts microservices by using graph clustering and combinatorial optimization to maximize cohesion and minimize coupling. the approach performs static analysis of the code to obtain a graph representation of the monolithic system. then, it uses graph clustering to detect high-cohesive communities of nodes using the Louvain community algorithm. In parallel, the tool clusters the domain entities (i.e., classes representing uniquely identifiable concepts in a system domain) within bounded contexts to identify the required service granularity. Finally, it uses combinatorial optimization to minimize the coupling, hence deriving the microservice architecture. the approach is fully implemented. We applied it over four different monolithic systems and found valuable results. We evaluated the identified architectures through cohesion and coupling metrics, along with a comparison with other state-of-the-art approaches based on features such as granularity level, number of produced services, and methods applied. the approach implementation and the experimental results are publicly available.

关键词： Couplings Measurement Codes Software architecture Microservice architectures Clustering algorithms Computer architecture

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