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42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Ren, Tao Hu, Zheyuan He, Hang Niu, Jianwei Liu, Xuefeng Institute of Software Chinese Academy of Sciences Laboratory for Internet Software Technologies Beijing China Beihang University State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beijing China Zhongguancun Laboratory Beijing China Zhengzhou University Research Institute of Industrial Technology School of Information Engineering Zhengzhou University Zhengzhou China

ISBN: (纸本)9798350334142

Mobile edge computing (MEC) has been proposed to provide mobile devices with both satisfactory computing resources and latency. Key issues in MEC include task offloading and power allocation (TOPA), for which deep reinforcement learning (DRL) is becoming a popular methodology. However, most DRL-based TOPA approaches are typically developed in a certain environment, lacking the adaptability to unseen environments. Motivated by this, this paper proposes a Fast Environment-Adaptive TOPA (FEAT) approach that could adapt to unseen environments with little fine-tuning. Specifically, we first split MEC states into the internal state and environmental state. Then, based on these two types of states, we develop two main components of FEAT - a group of internal state-dependent TOPA meta-policies and an environmental state-embedded steerer. Meta-policies learn TOPA skills within the internal state space (allowing reusing meta-policies in different environments), while the steerer learns to choose appropriate meta-policies according to embedded environmental states. When encountering an unseen environment with the same internal state space, FEAT only needs to fine-tune the steerer using the newly embedded environmental state with few internal state explorations. Extensive experimental results on simulation and testbed demonstrate that FEAT outperforms the state-of-the-art by more than 16.4% in terms of fine-tuning speeds. © 2023 IEEE.

关键词： Mobile edge computing

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Cyberbullying Classification Using a Natural Language Processing and Machine Learning Techniques

Cyberbullying Classification Using a Natural Language Proces...

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2024 International Conference on Advances in Computing Research on Science engineering and Technology, ACROSET 2024

作者： Mankar, Nikhilesh Pramod Mahure, Tushar Joshi, Anushka A. Pande, Sagar Dhanraj Khamparia, Aditya Nathe, Ankita Shrikrushna Turjman, Fadi Al Pune India Independent Researcher Amravati India Babasaheb Bhimrao Ambedkar University Department of Computer Science Amethi India Kavikulguru Institute of Technology and Science Department of Information Technology Nagpur India Ai and Robotics Institute Near East University Artificial Intelligence Software Information Systems Engineering Departments Nicosia Cyprus University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Turkey

ISBN: (纸本)9798350388800

The usage of online entertainment has increased dramatically after some time with the enhancement of the Internet and has turned into the most compelling systems administration stage in this century. Notwithstanding, the upgrade of a social network regularly makes adverse consequences on society that add to two or three terrible peculiarities, for example, online maltreatment, badgering cyberbullying, cybercrime, and internet savaging. Cyberbullying habitually prompts genuine mental and actual misery, especially for ladies and kids, and even occasionally make them to use self-destruction methods. Multiple number of episodes have as of late happened worldwide because of online badgering, like sharing private talks, bits of hearsay, and sexual comments. In this way, the distinguishing proof of harassing messages or messages via online entertainment has gained a significant measure for development for consideration with in scientists. The ground or motive for this exploration is to create a full-fledged way or a method to differentiate online harmful and tormenting drafts by combining various methods and techniques in the domain of natural language processing and AI © 2024 IEEE.

关键词： Adversarial machine learning

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Enabling Communication-Efficient Federated Learning via Distributed Compressed Sensing 42

Enabling Communication-Efficient Federated Learning via Dist...

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42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Guan, Yixuan Liu, Xuefeng Ren, Tao Niu, Jianwei Beihang University State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beijing China Zhongguancun Laboratory Beijing China Chinese Academy of Sciences Laboratory for Internet Software Technologies Institute of Software Beijing China Zhengzhou University Research Institute of Industrial Technology School of Information Engineering Zhengzhou University Zhengzhou China

ISBN: (纸本)9798350334142

Federated learning (FL) trains a shared global model by periodically aggregating gradients from local devices. Communication overhead becomes a principal bottleneck in FL since participating devices usually suffer from limited bandwidth and unreliable connections in uplink transmission. To address this problem, the gradient compression methods based on compressed sensing (CS) theory have been put forward recently. However, most existing CS-based works compress gradients independently, ignoring the gradient correlations between participants or adjacent communication rounds, which constrains the achievement of higher compression rates. In view of the above observation, we propose a novel gradient compression scheme named FedDCS, guided by distributed compressed sensing (DCS) theory. Following the design philosophy of separate encoding and joint decoding in DCS, FedDCS compresses gradients for participants in each round separately while reconstructing them at the central server jointly via fully exploiting correlated gradients from the previous round, which are known as side information (SI). Benefiting from this design, reconstruction performance is significantly improved with fewer decoding errors also iterations under the identical compression rate, and the total uploading bits to achieve model convergence are considerably reduced. Theoretical analysis and extensive experiments conducted on MNIST and Fashion-MNIST both verify the effectiveness of our approach. © 2023 IEEE.

关键词： Compressed sensing

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State-based Sandbox Tool for Distributed Malware Detection with Avoid Techniques 13

State-based Sandbox Tool for Distributed Malware Detection w...

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13th International Conference on Dependable systems, Services and Technologies, DESSERT 2023

作者： Rehida, Pavlo Markowsky, George Sachenko, Anatoliy Savenko, Oleg Khmelnytskyi National University Department of Computer Engineering and Information Systems Khmelnytskyi Ukraine Kennesaw State University Department of Software Engineering and Game Development Marietta United States Kazimierz Pulaski University of Technology and Humanities Department of Informatics Radom Poland Research Institute for Intelligent Computer Systems West Ukrainian National Unversity Ternopil Ukraine

ISBN: (纸本)9798350396119

This paper deals with the problem of detecting the malware by using emulation approach. Modern malware include various avoid techniques, to hide its anomaly actions. Advantages of using sandbox and emulation technologies are described. Various anti-emulation techniques that are used in modern malware considered. Obfuscation as one primary approach to hide malware malicious actions described and discussed. State of emulator is presented, and the advantages of its usage are covered. Distributed model for malware detection is considered. Basic emulator and its current capabilities presented. Prepared files that represent malware are described. Experimental results for developed files that differs with included avoid techniques are presented. Disadvantages of proposed approach is described. Future research and sandbox improvement are described. © 2023 IEEE.

关键词： anti-emulation techniques malware detection obfuscation techniques sandbox

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Develop a Lightweight MEC Platform Simulator

Develop a Lightweight MEC Platform Simulator

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2023 International Russian Automation Conference, RusAutoCon 2023

作者： Filianin, Ivan Bogatyrev, Vladimir Lesonen, Matvey Itmo University Faculty of Software Engineering and Computer Engineering St. Petersburg Russia Saint-Petersburg State University of Aerospace Instrumentation Department of Information Systems Security St. Petersburg Russia Itmo University Faculty of Infocommunication Technologies St. Petersburg Russia

ISBN: (纸本)9798350345551

This paper reviews the use of Minikube in multi-node mode to work with the ETSI MEC Sandbox as a lightweight multi-access edge computing platform simulator (LWMECPS). The work included a comparative analysis of MEC platforms in terms of functionality, cost of deployment, and complexity of adoption. An experiment was also conducted to test LWMECPS as a MEC platform using a Python3 test application. The experiment confirmed the feasibility of using LWMECPS as a MEC platform by deploying a Kubernetes deployment based on the number of users on the simulated 4g-macro network service zones from the ETSI MEC Sandbox. Particular attention was paid to the analysis of existing scientific literature on the use of multi-access edge computing platforms in various use cases. © 2023 IEEE.

关键词： Edge computing

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A Survey of Graph-based Clustering Techniques

A Survey of Graph-based Clustering Techniques

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Advances in Data-Driven Analytics And Intelligent systems (ADACIS), IEEE International Conference on

作者： Zakariyaa Ait El Mouden Alae El Alami Mohammed Lahmer Abdeslam Jakimi Information and Communication Systems Engineering High School of Technology Moulay Ismail University Meknes Morocco Software Engineering Information Systems Engineering Faculty of Sciences and Techniques Moulay Ismail University Meknes Morocco

Graph clustering is a powerful technique used to identify and group similar nodes within a complex network structure. This procedure involves segmenting the graph into distinct groups, with the nodes in each group having strong interconnections or similar characteristics. In this survey, we will highlight a variety of existing approaches of graph clustering, including spectral clustering, modularity optimization and hierarchical clustering, to efficiently discover meaningful clusters, facilitating analysis and decision-making in diverse fields ranging from data science and network analysis to social sciences and bioinformatics.

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A QoE-Aware Adaptive Energy-Efficient Transmission Scheduling Method 30

A QoE-Aware Adaptive Energy-Efficient Transmission Schedulin...

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30th IEEE International Conference on Parallel and Distributed systems, ICPADS 2024

作者： Yuan, Yankun Wang, Lin Xiao, Chonghui Liu, Zijuan Dang, Fan Wang, Xu Zhao, Haitian Miao, Xin Yanshan University School of Information Science and Engineering China National Computer Network Emergency Response Technical Team/Coordination Center of China China Tsinghua University Department of Automation and BNRist China Tsinghua University Global Innovation Exchange China Tsinghua University School of Software and BNRist China

ISBN: (纸本)9798331515966

In this paper, we propose a dynamic data transmission strategy for smart home environments that aims to optimize the Quality of Experience (QoE) by adaptively adjusting the data upload frequency based on the predicted trends in sensor data. Using the home wireless sensors monitoring dataset, we implement a deep learning model for accurate time series forecasting. In addition, an anomaly detection mechanism is used to identify critical events, requiring more frequent data uploads when important changes are detected. The QoE is quantified through a weighted average of several influencing factors, including data timeliness, timely upload of critical events, and transmission frequency. Our optimization objective is to maximize QoE while minimizing the number of transmissions, with an emphasis on reducing energy consumption through intelligent scheduling. The results demonstrate that our approach effectively balances data timeliness, transmission efficiency, and energy savings, leading to improved user satisfaction in smart home applications. © 2024 IEEE.

关键词： Adaptive algorithm Anomaly detection Energy conservation IoT LSTM Models QoE

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Optimization of Precision and Speed in ADCP 14

Optimization of Precision and Speed in ADCP

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14th International Conference on Advanced Computer information Technologies, ACIT 2024

作者： Mychuda, Lesya Mychuda, Zynowij Korobeinikova, Tetiana Zhuravel, Ihor Romanyuk, Olexandr Kotlyk, Sergii Lviv Polytechnic National University Department of Information Technology Security Lviv Ukraine Lviv Polytechnic National University Department of Computerized Automatic Systems Lviv Ukraine Vinnytsia National Technical University Department of Software Engineering Vinnytsia Ukraine National University of Technology Department of Information Technology and Cybersecurity Odesa Ukraine

ISBN: (纸本)9798350350036

This article introduces a novel principle for the design of interpolating logarithmic Analog-to-Digital Functional Converters (ADFCs) that enhances conversion speed and accuracy. The proposed principle leverages the phenomena of charge redistribution and accumulation during coarse and precise conversion stages, respectively. By simplifying the conversion algorithm and eliminating the need to reproduce previous compensating voltage levels during the coarse conversion stage, the new ADFC design outperforms existing analogs in both speed and precision. The methodological foundations discussed include the selection of conversion steps and the determination of logarithm bases that directly influence the conversion error. The article presents a simplified functional diagram of the ADFC, detailing the operational amplifier's resistance configuration and the role of capacitive cells in the conversion process. The results demonstrate that the ADFC's performance can be significantly improved without compromising accuracy, offering advancements in automation, control systems, and information-measurement technology. © 2024 IEEE.

关键词： Operational amplifiers

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Weber Law Based Approach for Multi-Class Image Forgery Detection

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Computers, Materials & Continua 2024年第1期78卷 145-166页

作者： Arslan Akram Javed Rashid Arfan Jaffar Fahima Hajjej Waseem Iqbal Nadeem Sarwar Department of Computer Science Superior UniversityLahore54000Pakistan Information Technology Services University of OkaraOkara56300Pakistan Departmet of Computer Science MLC LabOkara56300Pakistan Department of CS&SE International Islamic UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science Bahria UniversityLahore CampusLahore54600Pakistan

Today’s forensic science introduces a new research area for digital image analysis formultimedia ***,Image authentication issues have been raised due to the wide use of image manipulation software to obtain an illegitimate benefit or createmisleading publicity by using tempered *** forgery detectionmethods can classify only one of the most widely used Copy-Move and splicing ***,an image can contain one or more types of *** study has proposed a hybridmethod for classifying Copy-Move and splicing images using texture information of images in the spatial ***,images are divided into equal blocks to get scale-invariant *** law has been used for getting texture features,and finally,XGBOOST is used to classify both Copy-Move and splicing *** proposed method classified three types of forgeries,i.e.,splicing,Copy-Move,and ***(CASIA 2.0,MICCF200)and RCMFD datasets are used for training and *** average,the proposed method achieved 97.3% accuracy on benchmarked datasets and 98.3% on RCMFD datasets by applying 10-fold cross-validation,which is far better than existing methods.

关键词： Copy-Move and splicing non-overlapping block division texture features weber law spatial domain xgboost

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Automated Transformation of a Domain-Specific Language for System Modeling to Stochastic Colored Petri Nets

Automated Transformation of a Domain-Specific Language for S...

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Annual IEEE systems Conference

作者： Francesco Bedini Timo Räth Ralph Maschotta Kai-Uwe Sattler Armin Zimmermann Systems & Software Engineering Technische Universität Ilmenau Ilmenau Germany Databases & Information Systems Technische Universität Ilmenau Ilmenau Germany

ISBN: (数字)9798350358803

ISBN: (纸本)9798350358810

Petri Net models are widely recognized for their ability to analyze concurrent, stochastic processes based on a solid mathematical foundation. However, one drawback of Petri Nets is their low-level abstraction: they offer only a few basic elements like places and transitions to represent all system components. While this limitation may not be an issue when working with small models, it becomes challenging when attempting to model larger processes or systems. As the complexity increases, the number of elements in the Petri Net also grows, making it difficult to distinguish and maintain them effectively. Furthermore, Petri Nets require verification to ensure that they accurately represent the behavior of the system they are intended to model. This verification process must be repeated whenever a model is created or modified. To address these challenges, this paper describes a Stochastic colored Petri Net semantics of a domain-specific language that allows modeling time-based hardware and software systems. We have developed a custom Eclipse-based framework that allows for both graphical and textual modeling, providing editors with useful features such as real-time validation of model constraints, which is not feasible at the low-level Petri Net abstraction due to the lack of contextual information. The DSL also offers the advantage of easy conversion from other modeling languages thanks to an intermediate language. From the model, valid Stochastic Colored Petri Nets (SCPNs) can be generated, which can automatically simulate certain system properties consistently. This approach aims to enhance modeling capabilities and alleviate some of the limitations associated with traditional Petri Nets.

关键词： Petri nets Pipelines Semantics Stochastic processes Mathematical models Hardware DSL

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