sign in

Username Password

Forget Password ? ? Click Here

Don't Have An Account ? Create One

sign up

name Username Email Mobile Password

To contact us, you can contact us via the following mobile numbers by calling and WhatsApp

+989115682731 Connect To WhatsApp
+989917784643 Connect To WhatsApp
EnglishEnglish SpanishSpanish PortuguesePortuguese FrenchFrench GermanGerman ChineseChinese

Unlimited Access

For Registered Users

Secure Payment

100% Secure Payment

Easy Returns

10 Days Returns

24/7 Support

Call Us Anytime

Artificial Intelligence for Cyber Security: Methods, Issues and Possible Horizons or Opportunities 2021 book

Artificial Intelligence for Cyber Security: Methods, Issues and Possible Horizons or Opportunities

Details Of The Book

Artificial Intelligence for Cyber Security: Methods, Issues and Possible Horizons or Opportunities

edition: 1 
serie: Studies in Computational Intelligence, 972 
ISBN : 303072235X, 9783030722357 
publisher: Springer 
publish year: 2021 
pages: 467 
language: English 
ebook format : PDF (It will be converted to PDF, EPUB OR AZW3 if requested by the user) 
file size: 16 MB 

price : $10.8 15 With 28% OFF

Your Rating For This Book (Minimum 1 And Maximum 5):

User Ratings For This Book:       

You can Download Artificial Intelligence for Cyber Security: Methods, Issues and Possible Horizons or Opportunities Book After Make Payment, According to the customer's request, this book can be converted into PDF, EPUB, AZW3 and DJVU formats.

Abstract Of The Book

Table Of Contents

A Deep Learning Framework to Preserve Privacy in Federated (Collaborative) Learning
	1 Introduction
	2 Problem Statement
		2.1 System Model
		2.2 Attack Model
	3 Literature Review
		3.1 General
		3.2 Problem Specific
	4 Preliminaries
		4.1 Homomorphic Encryption
		4.2 Additive Homomorphic Encryption
		4.3 More Approaches to Related Problem
	5 Solution Design
		5.1 Initialization
		5.2 Upload Parameters
		5.3 Secure Cryptographic Protocol Between Server `A' and Server `B'
		5.4 Retrieve Parameters
	6 Security Analysis
		6.1 The Partial DLP
	7 Experimental Setup and Analysis
		7.1 Increased Communication Factor Analysis
		7.2 Implementation Details
		7.3 Comparison of Different Techniques
	8 Conclusion and Future Work
Significance of Feature Selection and Pruning Algorithms in Machine Learning Classification of E-Mails
	1 Introduction
	2 Related Works
	3 Theoretical Background
		3.1 Feature Selection Architecture
		3.2 Feature Ranking Methods
	4 Proposed Methodology
		4.1 System Model
		4.2 Feature Selection and Pruning Algorithms
	5 Results and Analysis
		5.1 Experiment 1: Feature Selection Using Feature Evaluator Method
		5.2 Experiment 2: Feature Selected Classifier
		5.3 Experiment 3: Scheme-Independent Feature Selection
		5.4 Experiment 4: Fast Feature Selection Using Ranking
		5.5 Experiment 5 and 6: Counting the Cost and Cost-Sensitive Classification Versus Cost-Sensitive Learning
	6 Conclusion
Biometric Fingerprint Generation Using Generative Adversarial Networks
	1 Introduction
	2 Related Work
		2.1 Deep Learning
		2.2 Deep Generative Modelling
		2.3 Generative Adversarial Networks (GANs)
		2.4 How GANs Work
		2.5 Training a GAN
		2.6 Cost Function for the GAN
		2.7 Deep Convolutional Generative Adversarial Network (DCGAN)
		2.8 Cybersecurity and GANs
	3 Model Architecture for the Biometric Fingerprint GAN
		3.1 Generator Architecture
		3.2 Discriminator Architecture
	4 Model Training
		4.1 Biometric Fingerprint Dataset
		4.2 Fingerprint Feature Extraction and Matching
		4.3 Experimental Setup
	5 Results
		5.1 NFIQ2 Fingerprint Quality Analysis
		5.2 BOZORTH3 Fingerprint Matching Results
		5.3 NFIQ2 Quality Analysis on Matched Samples
	6 Conclusion and Future Works
Assessing Cybersecurity Economic Risks in Virtual Power Plant UsingDeep Learning Techniques
	1 Introduction
	2 Assessing Cybersecurity Economics, Economics Risk and Frameworks in VPP
		2.1 Measuring Cybersecurity Costs and Quantifying
		2.2 Modelling and Measuring the Economic Risks in Cybersecurity
		2.3 ROI Models
		2.4 Cyber Risk Quantification and Cyber Risk Mitigation Frameworks
	3 Proposed Model
		3.1 Data and Methodology
	4 Results and Discussions
	5 Conclusions
	Appendix: NIST Cybersecurity Frameworks (in Brief)
Biometric E-Voting System for Cybersecurity
	1 Introduction
	2 Related Work
		2.1 The Present Voting System
		2.2 Enabling Technology for Bio-EVS
	3 System Analysis and Methodology
		3.1 Analysis of the Proposed Biometric-Based E-Voting System
		3.2 Specifications and Designs
	4 System Implementation and Evaluation
		4.1 System Implementation
		4.2 System Testing
	5 Conclusion and Future Work
Wrapper Based Approach for Network Intrusion Detection Model with Combination of Dual Filtering Technique of Resample and SMOTE
	1 Introduction
	2 Review of Literature
		2.1 Introduction
		2.2 Machine Learning
		2.3 Imbalance Dataset
	3 Research Method
		3.1 Data Source
		3.2 Feature Selection
		3.3 Class Imbalance
	4 Implementation, Results and Experimental Work
		4.1 Performance Metrics (Measurement)
		4.2 Experimental Result Analysis
		4.3 Performance Comparison
	5 Conclusion
Proactive Network Packet Classification Using Artificial Intelligence
	1 Introduction
	2 Background and Literature Survey
	3 Proposed System
	4 Implementation
	5 Conclusion and Future Scope
Security and Information Assurance for IoT-Based Big Data
	1 Introduction
	2 Security and Privacy of Internet of Things
		2.1 Security of IoT and Big Data
	3 Cryptography and the Three-Des Algorithm
		3.1 Triple DES
	4 Related Work
	5 Methodology
		5.1 Application of Triple Data Encryption Standard
		5.2 Data Gathered from IoT
		5.3 The GATEWAY
	6 Result and Discussions
	7 Conclusion and Future Direction
Privacy Preservation Approaches for Social Network Data Publishing
	1 Introduction
	2 Social Network Data Publishing
	3 Privacy Breaches
	4 Privacy Preservation Approaches
	5 K-Degree Anonymization Approach
		5.1 Graph Clustering
	6 k-NMF Anonymization Approach
	7 Differential Privacy Approach
	8 Conclusion
An Obfuscation Technique for Malware Detection and Protection in Sandboxing
	1 Introduction
	2 Related Works
	3 Background Information
	4 Proposed Methodology
	5 Results and Discussions
	6 Conclusion and Future Work
Secure Data Sharing with Interplanetary File System for Pharmaceutical Data
	1 Introduction
	2 Materials/Techniques
		2.1 Role of RFID in Pharmaceutical Industry
		2.2 Security Issues in IoT
		2.3 Block Chain Technology
		2.4 Working of Interplanetary File System
		2.5 Block Chain Architecture for Secure Pharmaceutical Data Storage with IPFS
		2.6 System Flow for Secure Storage and Access in the Proposed Consortium Block Chain Network
		2.7 Consortium Block Chain Smart Contract Design-Block Based Node Authentication and Access Policy
		2.8 Scope of LSTM over RNN
	3 Implementation
		3.1 Entities Used in Simulation
	4 Results and Discussions
		4.1 AES-256 Encryption and Decryption of QR Code Information
		4.2 Comparison of Security Analysis with Other Related Works
	5 Conclusion
Blockchain-Enabled Verification System
	1 Introduction
	2 Terms, Definitions and Related Work
		2.1 Related Work
	3 Research Method and Requirements Definition
	4 Verification Concept
		4.1 Blockchain for Verification
		4.2 Taxonomy
		4.3 Claiming Tokens
		4.4 Voting Process
	5 Architecture
		5.1 Scenarios
		5.2 Physical View
		5.3 Deployment View
		5.4 Logical View
		5.5 Process View
	6 Prototype and Evaluation
		6.1 Technology Stack
		6.2 Functioning of the Prototype
		6.3 Evaluation
	7 Conclusion
		7.1 Future Work
Threat Artificial Intelligence and Cyber Security in Health Care Institutions
	1 Introduction
	2 Preliminaries
		2.1 Artificial Neural Networks
		2.2 The General Data Protection Regulation
	3 Case Study—An Entropic Approach to Data Attainment and Processing
	4 Threat Consciousness
		4.1 The Best-Case Scenario
		4.2 The Worst-Case Scenario
	5 Conclusions and Future Work
Description of a Network Attack Ontology Presented Formally
	1 Introduction
	2 Taxonomy
	3 A Formal Description of the Network Attack Ontology
		3.1 Concepts of Network Attacks
		3.2 Relations
		3.3 Constraints on Classes
		3.4 Denial of Service Scenario
	4 Attack Scenario Examples: The SCO Attack, SpamHaus and Solarwinds
		4.1 SCO Attack
		4.2 Spamhaus DDoS Attack
		4.3 Solarwinds Supply Chain Attack
	5 Conclusions and Future Work
A Long Short Term Memory Model for Credit Card Fraud Detection
	1 Introduction
	2 Related Works
	3 System Design
		3.1 Datasets Description and Source
		3.2 Data Pre-processing
		3.3 Feature Conversion
		3.4 PCA (Principal Component Analysis)
		3.5 Data Normalization
		3.6 LSTM-Recurrent Neural Network Classification
	4 Implementation Technique
		4.1 Loading Datasets
		4.2 LSTM-RNN Implementation
		4.3 Classification
		4.4 System Evaluation
		4.5 Comparison of Proposed System with Some Existing Works Using Detection Rate/Precision, Accuracy and Recall
	5 Conclusion
Application of Machine Learning for Ransomware Detection in IoT Devices
	1 Introduction
	2 The Fundamental Concepts of IoT
		2.1 The Security Issues of the Internet of Things
		2.2 Research Trends in IoT and Artificial Intelligence (A.I.) Techniques
	3 Overview Concepts of Ransomware
		3.1 Ransomware Lifecycle
		3.2 Taxonomy of IoT Security
	4 Practical Case of Ransomware Detection in IoT Devices Using Machine Learning Techniques
		4.1 Modeling the Power Consumption
		4.2 Refining the Model for the Wi-Fi Consumption
		4.3 The CPU Consumption
		4.4 The Long Short-Term Memory (LSTM)
	5 Proposed Method
	6 Results and Discussion
	7 Conclusion and Future Work
Machine Learning Algorithm for Cryptocurrencies Price Prediction
	1 Introduction
	2 The Function of Money
		2.1 Research Trends in Cryptocurrencies and Artificial Intelligence (AI) Techniques
		2.2 Prediction Models for Cryptocurrency
		2.3 Machine Learning Comparison for Cryptocurrencies Price Prediction
	3 Motivation—The Rationale for Choosing Machine Learning Techniques for Cryptocurrencies Price Prediction
	4 Practical Case of Cryptocurrency Prediction with Machine Learning Techniques
		4.1 Data Description and Preprocessing
		4.2 Long Short-Term Memory (LSTM)
	5 The Proposed LSTM
	6 Results and Discussion
	7 Conclusion and Future Research Direction
Metaheuristic Techniques in Attack and Defense Strategies for Cybersecurity: A Systematic Review
	1 Introduction
	2 Methods
	3 Results
		3.1 Malware Detection
		3.2 Cipher Attacks
		3.3 Distributed Denial of Service
		3.4 Data Injection Attacks
		3.5 Intrusion Detection System and Intrusion Prevention System
		3.6 Security Audit Trail Analysis Problem
		3.7 Other Techniques of Attacks and Defense
	4 Conclusion and Future Work
		4.1 Future Work

First 10 Pages Of the book

Comments Of The Book