International Conference on Cyber Security, Privacy and Networking (ICSPN 2022)

Name: International Conference on Cyber Security, Privacy and Networking (ICSPN 2022)
Brand: Springer
Price: 245.03 EUR
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Nadia Nedjah Gregorio Martínez Pérez B. B. Gupta(Editor)

Springer (Publisher)

1st Edition

Published on 20. February 2023

XIII, 418 pages

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978-3-031-22018-0 (ISBN)

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Nadia Nedjah received the engineering degree in computer science and the M.Sc. degree in system engineering and computation from the University of Annaba, Algeria, and the Ph.D. degree in computation from the University of Manchester Institute of Science and Technology, Manchester, UK. She is Associate Professor with the Department of Electronics Engineering and Telecommunications, Faculty of Engineering, State University of Rio de Janeiro, Brazil. Her research interests include functional programming, embedded systems and reconfigurable hardware design, as well as cryptography.
Gregorio Martínez Pérez is currently Full Professor with the University of Murcia, Murcia, Spain, since 2014. His scientific activity is mainly devoted to cyber security and data science. He is working on different national and European IST research projects related to these topics, being Principal Investigator for UMU in most of them. He received the Ph.D. degree in computer science with the University of Murcia.
Prof. Brij B. Gupta is working as Director of International Center for AI and Cyber Security Research, Incubation and Innovations, and Full Professor with the Department of Computer Science and Information Engineering (CSIE), Asia University, Taiwan. In more than 17 years of his professional experience, he published over 450 papers in journals/conferences including 25 books and 10 Patents with over 16900 citations. He has received numerous national and international awards including Canadian Commonwealth Scholarship (2009), Faculty Research Fellowship Award (2017), MeitY, GoI, IEEE GCCE outstanding and WIE paper awards and Best Faculty Award (2018 and 2019), NIT KKR, respectively. He is also selected in the 2021 and 2020 Stanford University's ranking of the world's top 2% scientists. He is also Visiting/Adjunct Professor with several universities worldwide. He is also IEEE Senior Member (2017) and also selected as 2021 Distinguished Lecturer in IEEE CTSoc. Dr Gupta is also serving as Member-in-Large, Board of Governors, IEEE Consumer Technology Society (2022-2024). Prof Gupta is also leading IJSWIS, IJSSCI, STE and IJCAC as Editor-in-Chief. Moreover, he is also serving as Lead-Editor of a book series with CRC and IET press. He also served as TPC members in more than 150 international conferences also serving as Associate/Guest Editor of various journals and transactions. His research interests include information security, cyber physical systems, cloud computing, blockchain technologies, intrusion detection, AI, social media and networking.

Content

Intro
Preface
Organization
Contents
Data Mining Techniques for Intrusion Detection on the Internet of Things Field
1 Introduction
2 Related Works
3 The Proposed Approach
4 Experimental Phase
5 Conclusions and Future Works
References
Detecting Rumors Transformed from Hong Kong Copypasta
1 Introduction
2 Existing Works
3 Design of Our Copypasta Detection Tool
3.1 Overall System Architecture
3.2 The Machine Learning Models
3.3 User Interface of the Browser Extension
4 Evaluation
4.1 Performance of the Machine Learning Models
4.2 User Evaluation
5 Conclusion and Future Work
References
Predictive Model Building for Pain Intensity Using Machine Learning Approach
1 Introduction
2 Related Work
3 Dataset
4 Feature Selection Process
5 Classification
6 Conclusion
References
Analysis of N-Way K-Shot Malware Detection Using Few-Shot Learning
1 Introduction
1.1 Literature Review
1.2 Research Limitations
1.3 Research Contributions
2 Methodology
2.1 Relation Network
2.2 Prototypical Network
2.3 Matching Network
3 Performance Evaluation and Analysis
3.1 Benchmark Datasets for Malware Detection
3.2 Performance Evaluation of the Three FSL Approaches
4 Conclusion and Future Research Directions
References
Efficient Feature Selection Approach for Detection of Phishing URL of COVID-19 Era
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Dataset Collection
3.2 Pre-processing
3.3 Features Selection and Extraction
3.4 Machine Learning Algorithms
3.5 Experimental Results and Discussion
4 Conclusion and Future Work
References
Optimal Feature Selection to Improve Vehicular Network Lifetime
1 Introduction
2 Related Works
3 Dataset
4 Methodology
4.1 Problem Statement
4.2 Proposed Model
5 Results and Discussions
6 Conclusion and Future Directions
References
Machine Learning Based Two-Tier Security Mechanism for IoT Devices Against DDoS Attacks
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 First Stage
3.2 Second Stage
4 Results and Discussions
4.1 Data Set Prepossessing
4.2 Analysis
5 Conclusion
References
An Analysis of Machine Learning Algorithms for Smart Healthcare Systems
1 Introduction
2 Machine Learning in BioMedical
3 Selected and Applied Classifiers
3.1 Logistic Regression
3.2 KNN (K Nearest Neighbors)
3.3 Gaussian Naive Bayes
4 Performance Metrics and Result Discussion
5 Conclusion
References
Blockchains and Cross-Blockchains: Privacy-Preserving Techniques
1 Introduction
1.1 Contribution
2 Blockchain, Cross-Blockchain, and Privacy Security
2.1 Blockchain
2.2 Cross-Blockchain
2.3 Privacy Services
3 Privacy-Preserving Techniques
3.1 Privacy-Preserving for Blockchain and Cross-Blockchains
3.2 Comparison of Techniques
4 Conclusion
References
A Hybrid Approach for Protection Against Rumours in a IoT Enabled Smart City Environment
1 Introduction
2 Related Work
3 Proposed Approach
4 Rumor-Gathering Strategies
5 Performance and Evaluation
6 Evaluation Metrics
7 Conclusion
References
ImmuneGAN: Bio-inspired Artificial Immune System to Secure IoT Ecosystem
1 Introduction
1.1 Network Intrusion Detection
1.2 Data Security in IoT Network Ecosystem
2 Related Work on Artificial Immune Systems
3 Proposed Self-adaptive AIS Architecture
3.1 Innate Immune Mechanism of AIS
3.2 Self-adaptive Immunity Layer of AIS
3.3 ImmuneGAN Architecture
3.4 ImmuneGAN Training
4 Experiments
5 Results and Discussion
6 Conclusions
7 Future Perspective and Research Propagation
References
A Systematic Review of Recommendation System Based on Deep Learning Methods
1 Introduction
2 Research Methods
2.1 Data Collection
2.2 Pre-processing of Papers
3 Rating Prediction and Ranking Prediction
3.1 Rating Prediction Metrics
3.2 Ranking Prediction Metrics
3.3 Prediction Diversity Metrics
3.4 Datasets and Domain
4 Characteristics and Challenges
5 Conclusion
References
COVID-19 Patient Recovery Prediction Using Efficient Logistic Regression Model
1 Introduction
2 Related Work
2.1 ML in COVID-19 Prediction
2.2 Works on COVID-19 Patient Recovery
3 COVID-19 Patient Dataset
4 Machine Learning Algorithms
4.1 Logistic Regression
4.2 C5.0 Decision Tree Classifier
4.3 Support Vector Machine-RBF
4.4 Random Forest
4.5 Efficient Logistic Regression (ELR)
5 Results and Analysis
5.1 Experimental Design
5.2 Results
6 Conclusion
References
Ensemble Feature Selection for Multi-label Classification: A Rank Aggregation Method
1 Introduction
2 Related Works
3 Weighted Borda Count Method
4 Proposed Method
5 Experimental Studies
5.1 Datasets
5.2 Multi-label Evaluation Measures
5.3 Experimental Results
5.4 Discussion
6 Conclusion
References
Fire Neutralizing ROBOT with Night Vision Camera Under IoT Framework
1 Introduction
2 Literature Survey
3 Methodology
3.1 Software Requirement
3.2 Hardware Requirement
4 Implementation and Results
5 Future Scope
6 Conclusion
References
Multi-dimensional Hybrid Bayesian Belief Network Based Approach for APT Malware Detection in Various Systems
1 Introduction
1.1 Advanced Persistent Threat
1.2 Malware Analysis
2 Related Work
3 Proposed System
3.1 Static Analysis BBN
3.2 Dynamic Analysis BBN
3.3 Event Analysis BBN
4 Model Evaluation and Result Analysis
5 Conclusion and Future Work
References
Software Quality Attributes Assessment and Prioritization Using Evidential Reasoning (ER) Approach
1 Introduction
2 Background
2.1 Requirement Assessment and Prioritization Techniques
3 Methodology
4 Case Study and Results
5 Conclusion
References
Analysis of Digital Twin Based Systems for Asset Management on Various Computing Platforms
1 Introduction
2 Research Methodology
2.1 Eligibility Criteria
2.2 Restrictions
2.3 Data Source
2.4 Search Query Selection
3 Evaluation of Digital Twin Sector
3.1 Analysis Document Distribution
3.2 Analysis Topic and Type
3.3 Analysis of Country Distribution
4 Theoretical and Practical Implications
4.1 Characteristics of Digital Twin
5 Conclusion
References
IoT Data Validation Using Blockchain and Dedicated Cloud Platforms
1 Introduction
2 Proposed Methodology
2.1 Experimental Case
2.2 Smart Contract Definition
2.3 Data Validation
3 Conclusions
References
Security on Social Media Platform Using Private Blockchain
1 Introduction
2 Backgrounds
2.1 Blockchain Technology
2.2 The Upsides of Distributed Ledger Technology
2.3 Security Issue in Social Media Platform
2.4 Security over Block Chain
3 Authentication Using the Zig-Zag Arrangement for Security of Social Media Platform
4 Conclusion
5 Future Work
References
Plant Disease Detection using Image Processing
1 Introduction
2 Related Work
3 Proposed Methodology
4 Experimental Details
4.1 Experiment Setup and Data Sets
5 Result and Performance Evaluation
6 Conclusion
References
A Deep Learning Based Approach to Perform Fingerprint Matching
1 Introduction
2 Related Work
3 Proposed Technique
3.1 Data Preprocessing
3.2 Vision Transformer Model
3.3 Siamese Network with ViT
4 Experimental Analysis
4.1 Data Augmentation
4.2 Training of the Proposed Model
4.3 Results Analysis
5 Conclusions
References
Convolutional Neural Network and Deep One-Class Support Vector Machine with Imbalanced Dataset for Anomaly Network Traffic Detection
1 Introduction
1.1 Literature Review
1.2 Research Limitations
1.3 Research Contributions
2 Methodology
2.1 Overview of CNN-DOCSVM
2.2 Design and Components of CNN for Feature Extraction
2.3 ANTD Classification using DOCSVM with Customized Kernel via MKL
3 Results
3.1 Performance Evaluation of the CNN-DOCSVM
3.2 Performance Comparison between CNN-DOCSVM and Existing Works
4 Conclusion and Future Research Directions
References
A Comprehensive Comparative Study of Machine Learning Classifiers for Spam Filtering
1 Introduction
2 Related Work
2.1 Research Gaps in Spam Filtering
3 Methodology
4 Machine Learning Methods for Spam Filtering
5 Results and Discussion
5.1 Dataset
5.2 Results
6 Conclusion
References
A Novel Approach for Social Media Content Filtering Using Machine Learning Technique
1 Introduction
2 Related Work
3 Research Methodology
4 Results and Discussion
5 Conclusion
References
A Comprehensive Review on Automatic Detection and Early Prediction of Tomato Diseases and Pests Control Based on Leaf/Fruit Images
1 Introduction
2 Literature Review
2.1 Artificial Intelligence
2.2 HSL Color Model
2.3 Conversion from RGB Color Model to HSL Color Model
2.4 Image Processing
2.5 Digital Processing
2.6 Image Segmentation
2.7 Characterization Extraction with LBP
2.8 Properties Based on the Intensity of the Pixels
3 Methodology and Result
3.1 Image Acquisition
3.2 Pre-processing
3.3 Segmentation
3.4 Interpretation
3.5 Classification
4 Discussion
5 Conclusion
References
Big Data and Deep Learning with Case Study: An Empirical Stock Market Analysis
1 Introduction
2 Related Work
3 Hadoop
4 Big Data with Deep Learning
4.1 Stock Market Prediction Analysis
5 Conclusion
References
Automated Machine Learning (AutoML): The Future of Computational Intelligence
1 AutoML - Introduction
2 Working of AutoML
3 Advantages of AutoML
4 Security Threats to AutoML
4.1 Threats to Machine Learning Models Before the Model training
4.2 Threats to Machine Learning Systems After the ML Model has been Trained
5 Challenges of AutoML
6 Future Research Direction
References
Semi-supervised Federated Learning Based Sentiment Analysis Technique Across Geographical Region
1 Introduction
2 Related Work
2.1 Federated Learning
2.2 Transfer Learning
3 Problem Formation
3.1 Labeling a Dataset
3.2 Privacy Preserving Model
4 Proposed Approach
4.1 Multi Stage Semi-supervised Labeling
4.2 Federated Learning
5 Experiment and Results
5.1 Dataset
5.2 Implementation and Result
6 Conclusion
References
Sustainable Framework for Metaverse Security and Privacy: Opportunities and Challenges
1 Introduction
2 Related Work
3 Privacy Issues in Metaverse Found by Analysis
3.1 User Profiling in the Metaverse
3.2 User Privacy
3.3 Countermeasures
4 Security Issues in the Metaverse Found by Analysis
4.1 Humans In and Out of the Loop
4.2 Trustworthiness and Verification in the Metaverse
4.3 Polarization and Radicalization in the Singleton World
4.4 Distributed Denial of Service
4.5 Device Vulnerability
5 Proposed Mechanism
5.1 Confusion - Making a Cloud of Duplicates
5.2 Towards a Framework of Privacy Plans
6 Conclusion
References
Email Spam Detection Using Naive Bayes and Random Forest Classifiers
1 Introduction
2 Related Work
3 Proposed Methodology
4 Experimental Details
4.1 Experiment Setup and Data Sets
4.2 Machine Learning Classifiers
5 Result and Performance Evaluation
6 Conclusion
References
A Proposed Darknet Traffic Classification System Based on Max Voting Algorithms
1 Introduction
2 Related Work
3 The Proposed System
3.1 Dataset Description: CIC-Darknet2020 Dataset ch325023sps7,ch325023sps8
3.2 Data Pre-processing
3.3 Algorithms List
4 Designing Phase and Experimental Results
5 Conclusion
References
Role of Artificial Intelligence in Agriculture-A Paradigm Shift
1 Introduction
2 General Framework of Artificial Intelligence
3 Conclusion
References
A Novel Attack Detection Technique to Protect AR-Based IoT Devices from DDoS Attacks
1 Introduction
2 Literature Survey
3 Methodology
3.1 First Phase
3.2 Second Phase
4 Results and Discussion
5 Conclusion
References
Application of Artificial Neural Network (ANN) in the Estimation of Financial Ratios: A Model
1 Introduction
2 Review of Literature
3 Research Methodology and Data Collection
4 Conclusion
4.1 Practical Implications
4.2 Limitations and Future Scope
References
GAN-Based Unsupervised Learning Approach to Generate and Detect Fake News
1 Introduction
2 Related Work
3 Proposed Approach
4 Experimentation and Result
5 Conclusion and Future Work
References
Metaverse: A New Tool for Real-Time Monitoring of Dynamic Circumstances in the Physical Production System
1 Introduction
2 Research Methodology
2.1 Data Source
2.2 Search Query Selection
3 Evaluation of Metaverse
3.1 Analysis Document Distribution
3.2 Analysis of Country Distribution
3.3 Trending Research Topics
4 Theoretical and Practical Implications
4.1 Limitation of Digital Avatars
4.2 Documents Distribution
5 Conclusion
References
Security of Android Banking Mobile Apps: Challenges and Opportunities
1 Introduction
2 Vulnerability Analysis
2.1 The Risk Involved in Information Transferring Over the Network
2.2 Two Factor Authentication Problem
3 Tools for Detecting Vulnerabilities and Their Difficulties
4 Mobile Banking Apps Security and Threats
4.1 Issues Involved with Wireless Application Protocol(WAP)
4.2 Virus/Malware Attacks in Mobile Banking or Financial Applications
5 Mobile Banking Applications
5.1 Starbuck App
5.2 Bank of China Application (Hong Kong)
6 Research Model Analysis
7 Security Measures
8 Conclusion
References
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International Conference on Cyber Security, Privacy and Networking (ICSPN 2022)

Description

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