Advances in Cybersecurity, Cybercrimes, and Smart Emerging Technologies (Engineering Cyber-Physical Systems and Critical Infrastructures, 4)

✍ Scribed by Ahmed A. Abd El-Latif (editor), Yassine Maleh (editor), Wojciech Mazurczyk (editor), Mohammed ELAffendi (editor), Mohamed I. Alkanhal (editor)

• Publisher: Springer
• Tongue: English
• Leaves: 336
• Category: Library

✦ Synopsis

This book gathers the proceedings of the International conference on Cybersecurity, Cybercrimes, and Smart Emerging Technologies, held on May 10–11, 2022, in Riyadh, Saudi Arabia. The conference organized by the College of Computer Science of Prince Sultan University, Saudi Arabia. This book provides an opportunity to account for state-of-the-art works, future trends impacting cybersecurity, cybercrimes, and smart emerging technologies, that concern to organizations and individuals, thus creating new research opportunities, focusing on elucidating the challenges, opportunities, and inter-dependencies that are just around the corner. This book is helpful for students and researchers as well as practitioners.

 

CCSET 2022 was devoted to advances in cybersecurity, cybercime, and smart emerging technologies. It was considered a meeting point for researchers and practitioners to implement advanced information technologies into various industries. There were 89 paper submissions from 25 countries. Each submission was reviewed by at least three chairs or PC members and 26 regular papers (30%) were accepted. Unfortunately, due to limitations of conference topics and edited volumes, the Program Committee was forced to reject some interesting papers, which did not satisfy these topics or publisher requirements.

✦ Table of Contents

Committes
Preface
Contents
Advances in Cybersecurity and Cybercrimes
Malware Detection Using RGB Images and CNN Model Subclassing
1 Introduction
2 Related Works
3 Malware Visualization Technique
4 CNN Model Subclassing for Malware Detection
4.1 The Proposed Architecture
4.2 Model Optimizers
5 Experimentation and Result
6 Conclusion
References
Ensemble Feature Selection for Android SMS Malware Detection
1 Introduction
2 Proposed Method
2.1 System Model
2.2 Dataset
2.3 Data Preprocessing
2.4 Feature Selection
2.5 Performance Metrics
3 Experimental Results
4 Conclusions
References
Analyzing Malware From API Call Sequences Using Support Vector Machines
1 Introduction
1.1 Our Contributions
1.2 Paper Organization
2 Related Work
3 System Modeling
4 Results and Analysis
5 Conclusion
References
Android Ransomware Attacks Detection with Optimized Ensemble Learning
1 Introduction
2 Android Ransomware
3 Proposed System Design
3.1 Ensemble Learning
3.2 Bagging Classifier
3.3 Proposed Ransomware Detection Framework
4 Experimental Results
5 Conclusions
References
A Dual Attack Tree Approach to Assist Command and Control Server Analysis of the Red Teaming Activity
1 Introduction
2 Literature Review
3 Virtual Lab Setup
4 Methodology
4.1 Preparation
4.2 Reconnaissance
4.3 Intrusion
4.4 Exploitation
4.5 Privilege Escalation
5 Results
6 Conclusions and Future Directions
References
A Propagation Model of Malicious Objects via Removable Devices and Sensitivity Analysis of the Parameters
1 Introduction
2 Proposed SEIR-RSRI Model
3 Equilibrium Point and Reproduction Number
4 Stability Analysis: Local and Global
5 Sensitivity Analysis
6 Simulations Based Analysis
6.1 System Behavior with Respect to Time
6.2 Stability Analysis
6.3 Impact of Parameters
7 Conclusion
References
Improving Deep Learning Model Robustness Against Adversarial Attack by Increasing the Network Capacity
1 Introduction
2 Methodology
2.1 Creating Robust Deep Learning Models
3 Experimental Results
3.1 PGD Attack and PAT Defense
3.2 The Wide ResNet Model
3.3 Experimental Setup
3.4 Evaluation Metrics
4 Results and Discussions
4.1 Attack Utility Metrics
4.2 Defence Utility Metrics
5 Conclusions
References
Intelligent Detection System for Spoofing and Jamming Attacks in UAVs
1 Introduction
2 Related Works
3 An Overview of Machine Learning
4 Research Methodology
4.1 Dataset Source Phase
4.2 Dataset Preprocessing Phase
4.3 Splitting and Classifying the Dataset Phase
4.4 Performance Metric Phase
5 Results and Discussion
6 Conclusion and Future Works
References
AST-Based LSTM Neural Network for Predicting Input Validation Vulnerabilities
1 Introduction
2 Background and Related Works
2.1 Input Validation Vulnerabilities
2.2 Long Short Term Memory (LSTM)
2.3 Abstract Syntax Tree
2.4 Tokenization
2.5 Related Works
3 Methodology
3.1 Abstract Syntax Tree
3.2 Tokenization
3.3 Neural Network Model
4 Evaluation
4.1 Dataset
4.2 Experimental Environment
4.3 Evaluation Metrics
4.4 Results
5 Discussion
6 Conclusion
References
IoT Trust Management as an SIoT Enabler Overcoming Security Issues
1 Introduction
2 Trust Definition and Characteristics
3 IoT Trust Management in Literature
3.1 Trust Importance in IoT Security
3.2 Increasing Interest in IoT Trust Management
3.3 Trust Models Classification
4 Trust Management
4.1 Trust Composition (Metrics)
4.2 Trust Aggregation
5 Implementing Trust System Challenges
5.1 Metrics and Method Selection
5.2 Trust Category Issues
5.3 Trust-Related Attacks
6 Conclusion
References
An Overview of the Security Improvements of Artificial Intelligence in MANET
1 Introduction
2 Security Attacks in MANET
3 Existing MANET Security Algorithms
3.1 Protecting Routing Schemes
3.2 Data Security Schemes
4 Problems in Existing MANET Security Solutions
5 Artificial Intelligence's Approaches in MANET Security
6 Advantages of AI in Security of MANET
7 Conclusion and Future Work
References
Cloud Virtualization Attacks and Mitigation Techniques
1 Introduction
2 Virtualization and Its Architecture
3 Virtualization Breach
3.1 Hypervisor Based Attack
3.2 Virtual Machine Based Attack
4 Prevention of Virtualization Attacks
4.1 Prevention of Host OS Attack
4.2 Prevention of Guest OS Attack
4.3 Prevention of Cross VM Side Channel
4.4 Prevention of VM Creation Attack
4.5 Prevention of VM Migration Attack
4.6 Prevention of Scheduler-Based Attack
5 Conclusion
References
Advances in Smart Emerging Technologies
Short Survey on Using Blockchain Technology in Modern Wireless Networks, IoT and Smart Grids
1 Introduction
2 Blockchain Architecture
3 Blockchain for Wireless Networks
4 Blockchain for Internet of Things
5 Blockchain for Smart Grids
6 Open Challenges
7 Conclusion
References
Predicting Sleeping Quality Using Convolutional Neural Networks
1 Introduction
2 Related Work
3 Datasets
3.1 Dataset 1: Sleep-Study
3.2 Dataset 2: Sleep Deprivation
3.3 Dataset 3: Sleep Cycle Data
3.4 Data Pre-processing
4 Methodology
4.1 1D Convolutional Neural Networks
5 Experimental Results
5.1 Evaluation Metrics
5.2 Classification Results
6 Conclusions
References
A Dynamic Routing for External Communication in Self-driving Vehicles
1 Introduction
2 Literature Reviews
3 Ad Hoc On-Demand Distance Vector (AODV)
4 The Proposed Dynamic AODV Routing Protocol
5 Experimental Results
6 Conclusions
References
Analysis of the Air Inlet and Outlet Location Effect on Human Comfort Inside Typical Mosque Using CFD
1 Introduction
2 Modeling
3 Results and Discussions
4 Conclusion
References
Hybrid Feature-Based Multi-label Text Classification—A Framework
1 Introduction
2 Background Study
2.1 Multi-label Classification (MLC)
2.2 Multi-label Text Classification (MLTC)
3 Characteristics of the HMTCS Framework
4 Hybrid Feature-Based Multi-label Text Classification System (HMTCS)
5 Conclusions
References
Voice Recognition and User Profiling
1 Introduction
2 Voice Recognition
3 Profiling and Human Voice
4 Voice Recognition Techniques
5 Voice Recognition Over Big Data Era
6 Application Profiling Use Cases
6.1 Law Enforcement
6.2 Security
6.3 Health Services
6.4 Social and Commercial Services
6.5 Gaming and Entertainment
7 Challenges
7.1 General Challenges
7.2 Technological Challenges
7.3 Deployment Challenges
8 Conclusion
References
Compression-Based Data Augmentation for CNN Generalization
1 Introduction
2 Related Work
3 Experiment
4 Results and Analysis
5 Conclusion
References
A Study of Scheduling Techniques in Ad Hoc Cloud Using Cloud Computing
1 Introduction
2 Motivation
3 Ad-Hoc Cloud Architecture
3.1 Related Works
4 Methodology
4.1 Data Representation
4.2 Regression Model
4.3 Classification Model
4.4 Non-dominated Sorting Genetic Algorithm II
5 Simulation Results
5.1 Results of Up-Time Prediction Model
5.2 Results of the Job Allocation Model
5.3 Real-Life Scenario
6 Conclusion
References
Performance Improvement of SAC-OCDMA Network Utilizing an Identity Column Shifting Matrix (ICSM) Code
1 Introduction
2 ICSM Code Construction
3 System Performance and Analysis
4 Results and Debate
5 Conclusion
References
Localization of Pashto Text in the Video Frames Using Deep Learning
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset
3.2 Data Acquisition and Annotation
3.3 Implementation
4 YOLO
4.1 YOLO Architecture
5 Loss Function
6 Results and Discussion
6.1 Recall
6.2 Intersection over Union (IoU)
7 Comparison with Existing Predictor
8 Conclusion and Future Work
References
Exploration of Epidemic Outbreaks Using Machine and Deep Learning Techniques
1 Introduction
2 Machine and Deep Learning Uses in Epidemic Outbreaks
2.1 Dengue Virus
2.2 Congo Virus
2.3 Zika Virus
2.4 Coronavirus
3 Comparison of Reviewed Approaches
4 Challenges and Future Work
5 Conclusion
References
Propaganda Identification on Twitter Platform During COVID-19 Pandemic Using LSTM
1 Introduction
2 Related Work
3 Methodology
3.1 Data
3.2 Preprocessing
3.3 Feature Engineering
3.4 Classification
4 Experimental Results and Discussion
4.1 Comparative Study
5 Conclusion
References
Model of the Internet of Things Access Network Based on a Lattice Structure
1 Introduction
2 Problem Statement
3 Problem Solution
4 Conclusions
References
Study of Methods for Remote Interception of Traffic in Computer Networks
1 Introduction
2 Problematics
3 Materials and Methods
4 Methodology for Analyzing Efficiency Evaluation
5 Practical Performance Analysis
6 Conclusion
References