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International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)

作者： Md. Shariful Islam Md Abdur Rahim Nitun Kumar Podder Md. Najmul Hossain Md Imran Hossain Dept. of Computer Science and Engineering Pabna University of Scence and Technology Pabna Bangladesh Dept. of Electrical Electronic and Communication Engineering Pabna University of Scence and Technology Pabna Bangladesh Dept. of Inormation and Communication Engineering Pabna University of Scence and Technology Pabna Bangladesh

ISBN: (数字)9798350388282

ISBN: (纸本)9798350388299

Remittances are important economic contributors to a countryâs economy. It has increased national savings, lowered foreign exchange limits, and helped balance payments and development budgets. Migrant workers are the main source of these remittance revenues. Many workers worldwide leave their homes and move to different parts of the world for overseas employment. These workers are authorized and have documentation of their country of origin and final destination. Besides, many workers have migrated illegally globally, particularly to European Union (EU) countries via marine routes. However, illegal immigration leads to a loss of national revenue due to non-payment of taxes and social security contributions and problems with living circumstances and legal issues. Therefore, this paper aims to present a time series forecast of irregular migrants in EU countries from Bangladesh over the next five years. We used five methods to analyze this forecasting: ARIMA (an autoregressive integrated moving average), XGBoost Series, Decision Tree, Feed Forward Neural Network, and CatBoost Regressor. In addition, we used data from the European Border and Coast Guard Agency to perform the time series forecast. A field intervention is carried out to assess the gender, age, education, socioeconomic level, and skill profile of migrant workers. Moreover, a few case studies of migrant workers and a survey were conducted to investigate the underlying causes of irregular migration. Finally, this study explains the underlying cause of irregular migration and its repercussions. It can provide some ideas for decreasing the loss of human life and property by reducing irregular migration to help take essential actions in the home and destination countries.

关键词： Analytical models Time series analysis Neural networks Education Europe Market research Data models

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Fuzzy Logic-based Routing Adaptation for QoS Support in WSNs

Fuzzy Logic-based Routing Adaptation for QoS Support in WSNs

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Emerging Technologies for Dependable Internet of Things (ICETI), International Conference on

作者： Yosef A. Abdulmoghni Sharaf A. Alhomdy Yahya Al-Ashmoery Department of Information Technology Faculty of Computer Science and IT Sana’a University Sana’a Yemen Department of IT Al-Razi University Dept. Mathematics & Computer Faculty of Science Sana'a University Sana'a Yemen

ISBN: (数字)9798331533557

ISBN: (纸本)9798331533564

Wireless sensor networks (WSNs) have been widely used in dynamic environments where node failure, node mobility, or external events can cause frequent changes to the network architecture. As a result, WSNs cannot use conventional routing techniques created for wired networks. Rather, flexible routing algorithms are required, which can be adjusted according to the network circumstances and maximize a variety of parameters such as latency, productivity, power, and dependability. The objective of adaptation technique is to enhance the performance and efficiency of WSNs by adjusting them to changing conditions. Despite several studies on enhancing the quality of service (QoS) in WSNs, satisfying one of the QoS metrics has often a detrimental impact on the other metrics. The adaptation model combines artificial intelligence and cross-layer techniques for balancing energy consumption. This balancing aims to prevent gaps in the routing path that could impede data delivery or, at most, cause additional delay due to the consideration of alternative paths. It also aims to ensure that the other QoS metrics are stratified as much as possible. This is achieved by dynamically adjusting network routing protocol parameters using a fuzzy controller according to the instantaneous network conditions. The model is evaluated by simulating real multimedia data (real images) using the Omnet++ simulator. The simulation results demonstrate the effectiveness of the adaptation model in balancing QoS requirements, particularly in terms of network lifetime and the quality of the received data as represented by the peak signal-to-noise ratio (PSNR), as well as network delay and data loss rate.

关键词： Measurement Wireless sensor networks Adaptation models Visualization PSNR Simulation Quality of service Routing Routing protocols Delays

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Are Fictitious Nodes Needed at All?

SSRN

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SSRN 2023年

作者： Schweitzer, Nadav Cohen, Liad Hirst, Tirza Dvir, Amit Stulman, Ariel Ariel Cyber Innovation Center Dept. of Computer Science Ariel University Israel Department of Computer Science Jerusalem College of Technology Jerusalem Israel

Mobile ad-hoc networks (manets) are everywhere. They are the basis for many current technologies (including vanets, iot, etc.), and used in multiple domains (including military, disaster zones, etc.). For them to function, routing protocols have been defined, taking into account the high mobility of network nodes. These protocols, however, are vulnerable to devastating attacks. Many solutions have been proposed for various attacks, including DCFM (Denial Contradictions with Fictitious nodes Mechanism) for the node isolation and gray-hole variants. In this work we present a refinement for dcfm, calculate its cost, and compare alternative algorithms. It will be shown that the entire fictitious mechanism is superfluous for some required security level. © 2023, The Authors. All rights reserved.

关键词： Disasters

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Multidisease Prediction and Causality Analysis with Hospital Management System

Multidisease Prediction and Causality Analysis with Hospital...

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Applied Artificial Intelligence and Computing (ICAAIC), International Conference on

作者： Abhro Kumar Roy Subham Gayen P Renukadevi Dept. Of Computer Science and Engineering (C. Tech Department) SRM Institute of Science and Technology KTR Chennai Computer Science and Engineering (C. Tech Department) SRM Institute of Science and Technology KTR Chennai

ISBN: (数字)9798350375190

ISBN: (纸本)9798350375206

In healthcare domain, the demand for efficient diagnosis and hospital management systems has increased unprecedentedly. This research study proposes a novel Symptom Checker integrated with a Multidisease Hospital Management System, leveraging state-of-the-art Machine Learning (ML) algorithms such as Random Forest Classifier and XGB Regression. Unlike existing systems, this advanced framework outperforms conventional methods by offering increased accuracy and agility in diagnosing a multitude of medical conditions. The proposed system operates as a comprehensive tool, integrating patient symptoms with ML algorithms to accurately identify the diseases. Through the analysis of symptoms given as input by patients, the Random Forest Classifier preforms well in classifying a broad spectrum of diseases, demonstrating high precision in analysing complex symptom patterns. Furthermore, the XGB Regression model enhances the system’s predictive capabilities, enabling the estimation of disease progression and facilitating proactive treatment strategies. Moreover, the proposed approach extends beyond symptom analysis. It encompasses a robust hospital management component that streamlines administrative tasks, optimizes resource allocation, and enhances patient care.

关键词： Accuracy Machine learning algorithms Hospitals computer architecture Streaming media Classification algorithms Task analysis

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Persuasive: A Node Isolation Attack Variant for Olsr-Based Manets and its Mitigation

SSRN

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SSRN 2023年

作者： Schweitzer, Nadav Cohen, Liad Dvir, Amit Stulman, Ariel Department of Computer Science Jerusalem College of Technology Jerusalem Israel Ariel Cyber Innovation Center Dept. of Computer Science Ariel University Israel

Mobile ad hoc networks (manets) are self-creating, self-configuring, self-healing, decentralized adaptive networks. The Optimized Link State Routing protocol (olsr) is one of four base routing protocols for use in ad hoc networks. manet’s routing protocols, however, are vulnerable to various attacks. In this paper we introduce persuasive, a new, sophisticated and devastating node isolation attack variant against the olsr protocol. This attack allows for an attacker model with enhanced capabilities. We then present a novel technique to mitigate persuasive. The technique guarantees protection for all feasible topologies, incuring only local (centered around the attacker) and relatively-low overhead, independent of the network’s topology. Our new protection mechanism does not disclose its activity to the attacker, and does not impose any network overhead if an attack is not launched. The novelty of the current approach is rooted in the fact that only inherent capabilities of the olsr protocol are used. This allows for quiet discovery of the adversary, and easy integration with deployed systems. We simulate persuasive and its mitigation with ns3, comparing it with several state-of-the-art protection alternatives. We show that launching persuasive in a dynamic network while our mitigation mechanism is activated, will not only fend off the attack with success rates running between 93% for small networks and 100% for larger ones, but also enhance the victim’s connectivity. It is shown that the average end-to-end delay incurred is also better than existing alternatives, and only slightly worse than native olsr (without any protection). © 2023, The Authors. All rights reserved.

关键词： Mobile ad hoc networks

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Reducing Client-Side Cost in Secure Inner Product Evaluations

Reducing Client-Side Cost in Secure Inner Product Evaluation...

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International Conference on Information Networking

作者： Changhee Hahn Dongyoung Koo Junbeom Hur dept. Electrical and Information Engineering Seoul National University of Science and Technology South Korea dept. Convergence Security Hansung University South Korea dept. Computer Science and Engineering Korea University South Korea

ISBN: (数字)9798331506940

ISBN: (纸本)9798331506957

In the era of ubiquitous data collection and analysis, preserving privacy while utilizing data, such as inner product evaluations, poses a significant challenge. One such method is inner product functional encryption (IPFE), which enables the computation of inner products on encrypted vectors without exposing the vectors themselves. However, the computational intensity of IPFE decryption poses challenges, particularly for resource-limited client devices and high-dimensional vectors. To facilitate partial decryption, prior IPFE schemes require the client to derive a partial decryption key from an assigned secret key, incurring computation costs linear to the vector dimension. In this paper, we provide a framework for the challenges of IPFE, enabling efficient decryption outsourcing, maintaining data privacy, and facilitating key generation outsourcing in IPFE schemes. In the proposed framework, outsourced decryption using a partial decryption key generates a masked plaintext that only the client can unmask. Furthermore, the process of deriving the partial decryption key can be fully outsourced, thereby ensuring that the client’s computational burden remains constant.

关键词： Data privacy Costs Data collection Vectors Outsourcing Encryption Computational efficiency

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Identification of Children with ADHD from EEG Signals Based on Entropy Measures and Support Vector Machine

Identification of Children with ADHD from EEG Signals Based ...

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European Workshop on Visual Information Processing (EUVIP)

作者： Md. Maniruzzaman Md. Al Mehedi Hasan Taro Suzuki Jungpil Shin School of Computer Science and Engineering The University of Aizu Aizuwakamatsu Japan Dept. of Computer Science & Engineering Rajshahi University of Engineering and Technology Rajshahi Bangladesh

Attention deficit hyperactivity disorder (ADHD) is one of the major psychiatric and neurodevelopment disorders that affects 11% of children worldwide. Moreover, the prevalence of ADHD has rapidly increased over time worldwide. According to DSM-V, three types of symptoms such as inattention, hyperactivity, and combined type (inattention with hyperactivity). So, it is necessary to use a simple, non-invasive, and automatic detection system for identifying children with ADHD at an early stage. The objective of this study was to propose a machine learning (ML)based ADHD-combine type (ADHD-CT) detection system from electroencephalogram (EEG) signals. EEG signals were recorded from nineteen ADHD-CT children and fourteen healthy children. We extracted five entropy-based features such as approximate-based entropy, Shanon-based entropy, permutation-based entropy, sample-based entropy, and singular value decomposition (SVD)-based entropy from each signal. The subset of the most informative and discriminative features was selected for ADHDCT using sequential forward floating selection (SFFS). Following that, support vector machine (SVM) was implemented with leave-one-out cross-validation for the identification of ADHD-CT children and assessed its performances based on classification accuracy. Our results illustrated that SVM with polynomial kernel provided 96.87% classification accuracy to discriminate children as ADHD-CT and healthy children. Our findings showed that our proposed system can be used to detect children with ADHD-CT.

关键词：

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AI Based Monitoring System for Social Engineering 3

AI Based Monitoring System for Social Engineering

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3rd International Conference on Advancements in Computing, ICAC 2021

作者： Yapa, K. Udara, S.W.I. Wijayawardane, U.P.B. Kularatne, K.N.P. Navaratne, N.M.P.P. Dharmaphriya, W. G. V. U Sri Lanka Institute of Information Technology Dept. of Computer System Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9781665408622

Social media is one of the most predominantly used online platforms by individuals across the world. However, very few of these social media users are educated about the adverse effects of obliviously using social media. Therefore, this research project, is to develop an advisory system for the benefit of the general public who are victimized by the adverse impacts of their ignorant and oblivious behavior on social media. The system was implemented using a decision tree model with the use of customized datasets;and for the proceeding operational implementations, Python programming language, Pandas, Natural Language Processing and TensorFlow were used. This advisory system can monitor user behaviors and generate customized awareness reports for the users based on category and level of their behaviors on social media. Furthermore, the system is also capable of generating graph reports of the use behavior fluctuations for the reference of the user. With the help of these customized awareness reports and the graph reports, the users can identify their potential vulnerabilities and improve their social media habits. © 2021 IEEE.

关键词： Social networking (online)

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Assessing the Efficacy of Distributed Ledger technology for Immutable Data Logging and Fraud Prevention in IoT Retail Applications

Assessing the Efficacy of Distributed Ledger Technology for ...

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2024 International Conference on Advances in Computing Research on Science Engineering and technology, ACROSET 2024

作者： Ponnrajakumari, M. Elanangai, V. Ramprasad, S.R. Velpula, Vijaya Kumar Bhagyalakshmi, L. Prabha, A.G. Velammal Engineering College Dept. of Ece Chennai India St. Peter's Institute of Higher Education and Research. Avadi Department of Electrical and Electronics Engineering Chennai India School of Computing Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Mlr Institute of Technology Dept of Ece Hyderabad India Rajalakshmi Engineering College Dept. of Ece Chennai India

ISBN: (纸本)9798350388800

This paper presents a comprehensive framework for assessing the efficacy of Distributed Ledger technology (DLT) in IoT retail applications. The framework integrates five key algorithms: Data Validation Algorithm (DVA), Consensus Mechanism Algorithm (CMA), Fraud Detection Algorithm (FDA), Privacy-Preserving Algorithm (PPA), and Dynamic Smart Contract Algorithm (DSCA). Each algorithm addresses specific challenges, ensuring data integrity, achieving consensus, preventing fraud, preserving privacy, and enhancing smart contract adaptability. The ablation study evaluates the individual contributions of each algorithm, highlighting their significance in the overall framework. Comparative performance evaluations demonstrate the proposed framework's superiority, with higher scores across key parameters compared to existing assessment methods. The framework offers a robust solution for enhancing the security, integrity, and efficiency of DLT in IoT retail applications, addressing multifaceted challenges and requirements. © 2024 IEEE.

关键词： Distributed ledger

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An effective steganographic technique for hiding the image data using the LSB technique

Cyber Security and Applications

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Cyber Security and Applications 2025年 3卷

作者： Panigrahi, Rasmita Padhy, Neelamadhab School of Engineering and Technology Dept. of Computer Science and Engineering GIET University Gunupur Odisha Gobriguda India

Steganography is the art and science of writing secret messages so that neither the sender nor the intended recipient knows there is a hidden message. Data hiding is the art of hiding data for various reasons, such as keeping private data, secure, confidential data, etc. With increasing data exchange over a computer network, information security has become a significant issue. There are many methods used for data hiding, and steganography is a well-known technique. Steganography is the art of invisible contact and science. Steganography is the process through which the presence of a message can be kept secret. The objective of this paper is to hide data using the LSB (Least Significant Bit) technique into images that can be detected only by the specified user. We have developed a user-friendly GUI such that it can be used with the utmost ease. This paper is motivated to hide the message stated by the user in the dialog box given within the picture. The secret text is converted to the ciphertext to make it more stable. The sender selects the cover image, and it is used to generate the secured Stegno image, which is identical to the cover image. With the support of a private or public communication network, on the other hand, the stegno image can be saved and sent to the designated user, i.e., the recipient downloads the stegno image and can retrieve the secret text concealed in the stegno image using that same application. As for the watermarking, we have visible and invisible we have used the same LSB technique. In visible watermarking, text or image is embedded in the cover image, which can be noticed easily. As for invisible watermarking, some specific text is inserted into an image, and while retrieving it, it generates a QR code^, which can be scanned to get the watermarked text. We used the three different types of cover images i.e. Gray, and RGB also estimated the performance metrics. SNR, MSE, and PSNR the three performance metrics are used, and fou

关键词： Embedding Encode, Decode Least significant bits QR Code Steganographic techniques Stego image watermarking

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