Proceedings of the International Conference on Applied CyberSecurity (ACS) 2021

Name: Proceedings of the International Conference on Applied CyberSecurity (ACS) 2021
Brand: Springer
Price: 181.89 EUR
Availability: OnlineOnly

Hani Ragab Hassen Hadj Batatia(Herausgeber*in)

Springer (Verlag)

Erschienen am 1. Februar 2022

X, 143 Seiten

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978-3-030-95918-0 (ISBN)

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Beschreibung

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Inhalt

Intro
Preface
Conference Organization
Honorary Chair
General Chair
General Co-chair
Steering Committee
International Co-chair
Organizing Committee
Contents
Vulnerability and Infection Detection using Machine Learning
Android Malware Detection Using API Calls: A Comparison of Feature Selection and Machine Learning Models
1 Introduction
2 Framework Overview
2.1 Dataset
2.2 ML Models
2.3 Feature Selection Methods
3 Experimental Results and Analysis
4 Conclusion
References
Intrusion Detection for CAN Using Deep Learning Techniques
1 Introduction
2 Previous Work
3 Dataset and Feature Engineering
4 Neural Network Architectures
5 Results
6 Conclusion
References
A Comparative Study of Machine Learning Binary Classification Methods for Botnet Detection
1 Introduction
2 Background
2.1 Intrusion Detection System (IDS)
2.2 Datasets
3 Our Method
4 Experiments
4.1 Environment and Librairies
4.2 Evaluation Metrics
4.3 Results and Discussion
5 Conclusion
References
Detecting Vulnerabilities in Source Code Using Machine Learning
1 Introduction
2 Related Work
3 Background
3.1 Class Imbalance
3.2 Random Forest
3.3 Word2Vec
4 Proposed Methodology
5 Experimental Study
5.1 Dataset
5.2 Training
5.3 Results
6 Conclusion and Future Work
References
Android Malware Detection Using Long Short Term Memory Recurrent Neural Networks
1 Introduction
2 Related Work
3 Implementation
3.1 Data Set
3.2 Feature Extraction
3.3 Data Embedding
4 Feature Set Creation
5 Training Detail
6 Evaluation
7 Conclusion
References
Vulnerability Detection Using Deep Learning
1 Introduction
2 Background
2.1 Recurrent Neural Networks
2.2 Convolutional Neural Networks
2.3 Transformers
2.4 Gap Identification
3 Future Work
References
Feature Selection Approach for Phishing Detection Based on Machine Learning
1 Introduction
2 Related Works
3 Phishing Websites Feature Analysis
4 Phishing Detection Based on ML
5 Feature Selection Approach
5.1 Approach Description
5.2 Experimental Results
6 Conclusion
References
Phishing Email Detection Using Bi-GRU-CNN Model
1 Introduction
2 Related Work
3 Proposed Approach
3.1 Word Embedding
3.2 Bidirectional Gated Recurrent Units (Bi-GRU)
3.3 Convolutional Neural Network (CNN)
3.4 Our Model
4 Experimental Evaluation
4.1 Dataset
4.2 Results
5 Conclusion
References
Securing and Hardening Information Systems
Using Physically Unclonable Function for Increasing Security of Internet of Things
1 Introduction
1.1 Hardware-Based Security
1.2 PUF as a Key
1.3 Hardware Fingerprint
2 Physical Unclonable Function
2.1 A Brief History of PUF
2.2 PUF Highlights
2.3 PUF Structure
2.4 PUF's Taxonomy
3 The Applications of PUFs
4 Conclusion
References:
Multi-face Recognition Systems Based on Deep and Machine Learning Algorithms
1 Introduction
2 Deep Learning-Based System
2.1 Histogram of Oriented Gradients
2.2 Convolutional Neural Network
2.3 Proposed CNN-Based system
3 Machine Learning-Based System
3.1 Face Detection Using Haar Cascade
3.2 LBP Approach Classification
3.3 Proposed LBP-Based System
4 Experiment Results
5 Conclusion
References
A Novel Approach Integrating Design Thinking Techniques in Cyber Exercise Development
1 Introduction
2 Related Work
3 Design Thinking for Cyber Exercises
4 Evaluation
5 Conclusions and Future Work
References
Availability in Openstack: The Bunny that Killed the Cloud
1 Introduction
2 Openstack Architecture
2.1 Core Services
2.2 Environment Essentials
3 Our Experimental Setup
4 Results and Discussion
5 Conclusion and Future Work
References
Distributed and Reliable Leader Election Framework for Wireless Sensor Network (DRLEF)
1 Introduction
2 Related Work
3 Distributed and Reliable Leader Election Framework (DRLEF)
3.1 Notations
3.2 Assumptions
3.3 DRLEF Algorithm
4 Simulation
4.1 Environment
4.2 Results
5 Conclusion and Future Work
References
Author Index

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