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Cloud Forensics Analysis Framework for Secure and Efficient Data Retrieval

Cloud Forensics Analysis Framework for Secure and Efficient ...

2024 OPJU International Technology Conference on Smart computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Revathi, V. Aishwarya, B.K. Tripathi, Manju Singh, Navdeep Alabdely, Haider Kumar, Ashwani New Horizon College of Engineering Department of Applied Sciences Bangalore India Institute of Aeronautical Engineering Hyderabad Dundigal India Ies College of Technology Department of Computer Science & Engineering M. P. Bhopal India Lovely Professional University Phagwara India The Islamic University Najaf Iraq Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India

ISBN: (纸本)9798350373783

This study's Cloud Forensics Analysis Framework seeks secure and effective data recovery methods. The framework's five strategies make digital evidence retrieval methodical and versatile. These include adaptive evidence collecting, secure data retrieval, machine learning-based anomaly detection, intelligent automation, and context-aware metadata analysis. Each approach targets a distinct forensic process step. This makes cloud forensics investigations seem difficult. The customizable Evidence gathering Algorithm adapts to cloud characteristics to collect evidence. This allows contextually aware and flexible digital evidence retrieval. The secure Data Retrieval Techniques Algorithm protects data privacy and chain of custody with advanced encryption and validation. The Machine Learning-Based Anomaly Detection Algorithm checks protected data for anomalies before sending it, making the system safer. Investigators may focus on more complex cases by simplifying and sorting basic forensic activities with the Intelligent Automation Algorithm. The Context-Aware Metadata study Algorithm weights and prioritizes cloud metadata. This completes metadata analysis. Compared to other approaches, the framework has greater Precision, Recall, F1 Score, Processing Time, Resource Utilization, and Compatibility Score. Charts convey system operation in a simple manner. This powerful and adaptable Cloud Forensics Analysis Framework improves cloud forensics by providing a thorough and effective solution to recover and safeguard data. The Cloud Forensics, This paper discusses context-aware metadata analysis, data retrieval, intelligent automation, machine learning-based anomaly detection, performance metrics, secure data retrieval techniques, support vector machines, and visual representation. © 2024 IEEE.

关键词： Cloud security

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Task-Oriented Co-Design of Communication, computing, and Control for Edge-Enabled Industrial Cyber-Physical Systems

arXiv

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arXiv 2025年

作者： Diao, Yufeng Zhang, Yichi De Martini, Daniele Zhao, Philip Guodong Li, Emma Liying School of Computing Science University of Glasgow United Kingdom Department of Computer Science University of Manchester United Kingdom Oxford Robotics Institute Department of Engineering Science University of Oxford United Kingdom

This paper proposes a task-oriented co-design framework that integrates communication, computing, and control to address the key challenges of bandwidth limitations, noise interference, and latency in mission-critical industrial Cyber-Physical Systems (CPS). To improve communication efficiency and robustness, we design a task-oriented Joint Source-Channel Coding (JSCC) using Information Bottleneck (IB) to enhance data transmission efficiency by prioritizing task-specific information. To mitigate the perceived End-to-End (E2E) delays, we develop a Delay-Aware Trajectory-Guided Control Prediction (DTCP) strategy that integrates trajectory planning with control prediction, predicting commands based on E2E delay. Moreover, the DTCP is co-designed with task-oriented JSCC, focusing on transmitting task-specific information for timely and reliable autonomous driving. Experimental results in the CARLA simulator demonstrate that, under an E2E delay of 1 second (20 time slots), the proposed framework achieves a driving score of 48.12, which is 31.59 points higher than using Better Portable Graphics (BPG) while reducing bandwidth usage by 99.19%. Copyright © 2025, The Authors. All rights reserved.

关键词： Bandwidth

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An Improved Dung Beetle Optimizer for Random Forest Optimization 6

An Improved Dung Beetle Optimizer for Random Forest Optimiza...

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6th International Conference on Frontier Technologies of Information and computer, ICFTIC 2024

作者： Tan, Lianghao Liu, Xiaoyi Liu, Dong Liu, Shubing Wu, Weixi Jiang, Huangqi W. P. Carey School of Business Arizona State University Tempe United States Ira A. Fulton Schools of Engineering Arizona State University Tempe United States Yale University Department of Computer Science New Haven United States University of North Carolina at Chapel Hill Department of Computer Science Chapel Hill United States Tandon School of Engineering New York University New York United States College of Computing Georgia Institute of Technology Atlanta United States

ISBN: (纸本)9798331541750

To improve the convergence speed and optimization accuracy of the Dung Beetle Optimizer (DBO), this paper proposes an improved algorithm based on circle mapping and longitudinal-horizontal crossover strategy (CICRDBO). First, the Circle method is used to map the initial population to increase diversity. Second, the longitudinal-horizontal crossover strategy is applied to enhance the global search ability by ensuring the position updates of the dung beetle. Simulations were conducted on 10 benchmark test functions, and the results demonstrate that the improved algorithm performs well in both convergence speed and optimization accuracy. The improved algorithm is further applied to the hyperparameter selection of the Random Forest classification algorithm for binary classification prediction in the retail industry. Various combination comparisons prove the practicality of the improved algorithm, followed by SHapley Additive exPlanations (SHAP) analysis. © 2024 IEEE.

关键词： Random forests

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Implementation of Facial Recognition (AI) and Its Impact on the Service Sector 1

Implementation of Facial Recognition (AI) and Its Impact on ...

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1st International Conference on applied Artificial Intelligence and computing, ICAAIC 2022

作者： Aravinda, T.V. Krishnareddy, K.R. Varghese, Sony Chandrika, P.V. Rao, T.Prabhakara Trofimov, Victor Sjm Institute of Technology Department of Computer Science and Engineering India Xavier Institute of Management & Entrepreneurship Management Kochi India Prin Ln Welingkar Institute of Management Development and Research Management/Economics India Godavari Institute of Engineering and Technology Department of Computer Science& Engineering Rajahmundry India Abay Myrzakhmetov Kokshetau University Department of Design Kokshetau Kazakhstan

ISBN: (纸本)9781665497107

Facial-Recognition technology is gaining a widespread adoption in the service sector present across the world with its ability to secure the user information in an efficient manner. The considerable increase in the occurrence of cyber-crime incidents over the recent years increases the need to strengthen the protection mechanisms for ensuring the security of clients' information by the organizations in different sectors including service sector to gain trust from consumers. The proposed research study concentrates on analyzing the implementation of facial recognition and its impact on the service sector. Hospitality or healthcare service sectors need to handle a wide range of information from their clients as well as employees every day. Due to this, it often becomes highly difficult for them to monitor security of all the information and prevent unauthorized access. As a result, it has become critical for organizations in this sector to focus on implementing facial-recognition technology. With the reduced chances of encountering security concerns, this technology automates different functions for achieving an increased efficiency. The proposed study investigates the relevant research literature linked with this context to create the best possible discussion. Especially, during this pandemic, when everyone is concerned regarding their security and safety, automating the check-in, check-out or employee attendance procedures can aid in regaining the trust of consumers and employees in various service sectors. This develops significant research opportunities for achieving a huge competitive advantage for organizations. However, the security issues associated with this technology can cause organizations to face legal obligations. This study identifies these challenges and recommends the best ways to address the emerging challenges. © 2022 IEEE.

关键词： Cryptography

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Can microplastic contamination affect the wing morphology and wingbeat frequency of Aedes aegypti (Diptera: Culicidae) mosquitoes?

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Environmental science and Pollution research 2024年第49期31卷 59289-59301页

作者： de Nadai, Barbara Lepretti Moura, Lidia Castro, Gleyson B. Silva, Kamila Jessie Sammarro Maletzke, André Gustavo Corbi, Juliano José Batista, Gustavo E. A. P. A. Machado, Renato Bobsin Computational Entomology Laboratory Department of Engineering and Exact Sciences Western Paraná State University Foz Do Iguaçu Brazil Environmental Engineering and Sanitation Leonardo da Vinci University Center Indaial Brazil Laboratory of Ecotoxicology and Applied Ecology Department of Hydraulic Engineering and Sanitation São Carlos School of Engineering University of Sao Paulo Sao Carlos Brazil Environmental Biophotonics Laboratory São Carlos Institute of Physics University of Sao Paulo Sao Carlos Brazil School of Computer Science and Engineering University of New South Wales Sydney Australia

Microplastics (MPs) are increasingly widespread in the environment, which raises questions about their potential effects at different biological levels. It is essential to assess the impacts on biodiversity, and it is also crucial to understand whether the presence of MPs can interfere with the biological traits of species of relevance in public health. Considering that the life-history traits of mosquitoes, such as size and the wingbeat frequency (WBF), are related to its vector competence, here, we study the effects of 106 particles L−1 (as expected concentration of MPs on the environment, using the polyethylene type) on WBF, as well as wing morphology, testing the Culicidae species found across all continents, Aedes aegypti, as an indicator. Results show that larvae survival and development were not affected by the tested concentration of MP. Geometric morphometrics showed some asymmetry in female mosquito wings, which were also smaller for individuals reared in MP suspension. As for WBF, results did not indicate any significant differences between females. Male mosquitoes, however, showed alterations in WBF and wing morphology, suggesting possible sex-specific reactions to microplastic exposure. Also, the combination of morphological parameters analyzed as covariates (wing centroid size and body weight) did not significantly affect WBF for both female and male mosquitoes. Overall, this study shows an inaugural investigation of the effects of MP on wing size and WBF on Ae. aegypti, shedding light on these parameters tested for a current pollution issue and its impact on a virus vector. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Invertebrates

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Discovery of Influential Publications Using research Article's Usage Context 4

Discovery of Influential Publications Using Research Article...

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4th International Conference on Emerging Trends in Networks and computer Communications, ETNCC 2024

作者： Kiyani, Faisal Fayyaz Hamid, Bushra Humayun, Memona Sindiramutty, Siva Raja A L Chowdhury, Sohini S&P Global Market Intelligence Islamabad Pakistan University Institute of IT PMAS Department of Computer Science Rawalpindi Pakistan School of Arts Humanities and Social Sciences University of Roehampton Department of Computing LondonSW15 5PJ United Kingdom School of Computer Science Taylor's University Subang Jaya Malaysia Lovely Professional University Division of Research and Development Phagwara144411 India KKR and KSR Institute of Technology and Sciences Andhra Pradesh Guntur India

ISBN: (纸本)9798350353266

Identification of influential research articles has been an area of interest for quite a long time. Usually, the importance of an article is measured by the number of citations it has gained. There are different techniques available to identify the importance of a given paper based on their number of citations and authors popularity (h-index), but these techniques do not truly reflect the importance of a paper with respect to their usage context. In this paper we are proposing a technique to identify the importance of a research article from it usage perspective and not just relying on its number of citations or H-Index. To identify the importance of a given paper we calculate and use the paper's context, in what sense a paper is cited. We employ machine learning techniques to classify a citation into positive, negative or neutral and based on these criteria we calculate paper importance. As a result of our research work, swe also produced and published a citations dataset manually classified into positive, negative and neutral classes. © 2024 IEEE.

关键词： Adversarial machine learning

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Natural Language Processing in Strategic Planning Analysis 2

Natural Language Processing in Strategic Planning Analysis

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2nd International Conference Computational and Characterization Techniques in engineering and sciences, IC3TES 2024

作者： Shetty, Keerthi Tyagi, Swati Jha, Anupama Rao, D N Murali Krishna Arunkumar, J.R. Lakshmikanth, R. Nmam Institute of Technology Department of Mca Udupi India University of Delaware DE United States Vivekananda Institute of Professional Studies Guru Gobind Singh Ip University Vsit Delhi India Jntuh Electrical and Electronics Engineering India Modern Institute of Technology and Research Centre Department of Computer Science and Engineering Rajasthan Alwar India Adithya Institute of Technology Department of Management Studies Coimbatore India

ISBN: (纸本)9798350364699

Natural Language Processing (NLP) has emerged as a game-changing technique in the field of strategic planning analysis. This development represents a significant step forward. Improved methods for obtaining meaningful insights from massive amounts of textual data are made available by natural language processing (NLP). According to the findings of this research project, the application of natural language processing (NLP) technology to enhance the strategic planning processes that are carried out within enterprises is being investigated. Natural language processing (NLP) approaches, such as semantic analysis, sentiment identification, and topic modeling, can be utilized to acquire a more in-depth grasp of market tendencies, consumer feedback, and internal communications. This can be accomplished by utilizing these techniques. The study demonstrates how natural language processing (NLP) can facilitate the discovery of emergent patterns, simplify the understanding of data, and encourage decision-making that is driven by data. There are a great number of case studies that demonstrate the incorporation of natural language processing (NLP) into strategic frameworks. These case studies show improvements in the accuracy of forecasting, risk management, and competitive analysis processes. The findings of this study demonstrate the potential for natural language processing (NLP) to revolutionize strategic planning by providing a more nuanced and comprehensive evaluation of qualitative data. This, in turn, will ultimately result in strategic decisions that are more informed and agile. © 2024 IEEE.

关键词： Risk management

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The Different Way of Utilizing the Intellectual of Artificial Intelligence in the Animal Farming Field Progress of AI 4

The Different Way of Utilizing the Intellectual of Artificia...

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4th IEEE International Conference on Advance computing and Innovative Technologies in engineering, ICACITE 2024

作者： Kumar, Deepak Alzubaidi, Laith H. Chandramauli, Awadhesh Unissa, Raheem Bansal, Saloni Kumar, K. Krishna Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India The Islamic University Najaf Iraq Uttaranchal Institute of Technology Uttaranchal University Department of Civil Engineering Dehradun248007 India Cmr Technical Campus Department of Cse Telangana Hyderabad India Gla University Department of Computer Engineering and Applications Mathura India Saveetha Institute of Medical and Technical Science - Simats Saveetha University Department of Conputer Science and Engineering Saveetha School of Engineering Chennai India

ISBN: (纸本)9798350360165

The goal of this project is to create a prototype smart farm using Internet of Things (IoT) technology. Developing an Internet of Things feeding control system and designing and implementing environmental monitoring and control systems for farm housing are the primary objectives. The development method uses open-source hardware and software and is conducted in pig farms in the Thai region of Nakhon Si *** ESP8266 Wi-Fi microcontroller is crucial to the system design, allowing several sensors to be connected to the server and actuators to be controlled. The MQTT protocol is used to transmit data over a secure wireless local network. The data flow is designed using Node-RED, and storage is handled using a NoSQL database such as InFluxDB. The feeding control system achieved a 100% compliance rate by following instructions continuously. End customers can utilise a web application on their PCs or cellphones to obtain real-time data and operate the system. Furthermore, the collected data is processed and analysed as big data, which facilitates the analysis of climate change trends in the vicinity of the study site and forecasting. The overall performance rating of the system received great marks from users, averaging 4.40 out of 5 with a 0.46 standard deviation. As a result, the created IoT system functions as a prototype that may be further enhanced for use in bigger farms or other agricultural environments. © 2024 IEEE.

关键词： Environmental monitoring

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Optimizing Optical Attocells Positioning of Indoor Visible Light Communication System

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computers, Materials & Continua 2023年第2期74卷 3607-3625页

作者： Mohammed S.M.Gismalla Asrul I.Azmi Mohd R.Salim Farabi Iqbal Mohammad F.L.Abdullah Mosab Hamdan Muzaffar Hamzah Abu Sahmah M.Supa’at School of Electrical Engineering Faculty of EngineeringUniversiti Teknologi MalaysiaSkudai81310Malaysia Lightwave Communications Research Group(LCRG) Faculty of Electrical EngineeringUniversiti Teknologi Malaysia(UTM)SkudaiJohorMalaysia Department of Electronics and Electrical Engineering Faculty of EngineeringInternational University of AfricaKhartoum12223Sudan Department of Communication Engineering Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Parit RajaBatu Pahat86400JohorMalaysia Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Department of Computer Science University of São PauloSão PauloBrazil

Visible light communication(VLC),which is a prominent emerging solution that complements the radio frequency(RF)technology,exhibits the potential to meet the demands of fifth-generation(5G)and beyond *** random movement of mobile terminals in the indoor environment is a challenge in the VLC *** model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio(SNR).As such,the optical attocells positions were optimized in this study with a developed try and error(TE)*** optimized optical attocells were examined and compared with previous *** novel approach had successfully increased minimum received power from−1.29 to−0.225 dBm,along with enhanced SNR performance by 2.06 *** bit error rate(BER)was reduced to 4.42×10−8 and 6.63×10−14 by utilizing OOK-NRZ and BPSK modulation techniques,*** optimized attocells positions displayed better uniform distribution,as both received power and SNR performances improved by 0.45 and 0.026,*** the results of the proposed model are optimal,it is suitable for standard office and room model applications.

关键词： Visible light communication(VLC) optical attocell received power signal-to-noise ratio(SNR) bit error rate(BER) coefficient of variation(CV)

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IoV Cyber Defense: Advancing DDoS Attack Detection with Gini Index in Tree Models 4

IoV Cyber Defense: Advancing DDoS Attack Detection with Gini...

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4th International Conference on Emerging Trends in Networks and computer Communications, ETNCC 2024

作者： Dilshad, Muhammad Almas, Bushra Tariq, Noshina Jazri, Husin Bin Alwakid, Ghadah Naif Khan, Jan Sher Kumar, Pranav Kumar, Rahul Institute of Information Technology QuaidiAzam University Islamabad Pakistan Air University Department of Avionic Engineering Islamabad Pakistan School of Computer Science Taylor's University Subang Jaya Malaysia Jouf University Department of Computer Sciences Sakaka Saudi Arabia Lovely Professional University Division of Research and Development Phagwara144411 India KKR and KSR institute of technology and sciences Andhra Pradesh Guntur India

ISBN: (纸本)9798350353266

In today's ever-changing world of cybersecurity, where smart devices and the Internet of Vehicles (IoV) are everywhere, it is crucial to have a strong defense against attacks. This paper introduces an intelligent way to detect the Distributed Denial of Service (DDoS) attacks, a severe threat that can disrupt access to essential resources. Traditional methods to handle such attacks include intrusion detection systems (IDS). However, we need new and creative solutions to increasingly complex data. Our proposed strategy is an Artificial Intelligence (AI)-based technique that uses a Decision Tree (Dt) algorithm with feature selection using the Gini index. The proposed DDoS detection system has depicted an impressive accuracy of 99.4% while tested with the CIC-DDoS2019 dataset, surpassing baseline and previous benchmarks like Random Forest and XGBoost. Our improved Gini index method smartly selects 39 essential security features from a pool of 88, cutting down on unnecessary data and preventing over-fitting. This approach efficiently demonstrates its practical use in real-world network security situations, especially IoVs. © 2024 IEEE.

关键词： Network intrusion

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