13th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2020)

Name: 13th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2020)
Brand: Springer
Price: 171.19 EUR
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Álvaro Herrero Carlos Cambra Daniel Urda Javier Sedano Héctor Quintián Emilio Corchado(Editor)

Springer (Publisher)

Published on 27. August 2020

XVII, 472 pages

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978-3-030-57805-3 (ISBN)

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This book contains accepted papers presented at CISIS 2020 held in the beautiful and historic city of Burgos (Spain), in September 2020.

The aim of the CISIS 2020 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of computational intelligence, information security, and data mining. The need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall event.

After a thorough peer-review process, the CISIS 2020 International Program Committee selected 43 papers which are published in these conference proceedings achieving an acceptance rate of 28%. Due to the COVID-19 outbreak, the CISIS 2020 edition was blended, combining on-site and on-line participation. In this relevant edition, a special emphasis was put on the organization of five special sessions related to relevant topics as Fake News Detection and Prevention, Mathematical Methods and Models in Cybersecurity, Measurements for a Dynamic Cyber-Risk Assessment, Cybersecurity in a Hybrid Quantum World, Anomaly/Intrusion Detection, and From the least to the least: cryptographic and data analytics solutions to fulfil least minimum privilege and endorse least minimum effort in information systems.

The selection of papers was extremely rigorous in order to maintain the high quality of the conference and we would like to thank the members of the Program Committees for their hard work in the reviewing process. This is a crucial process to the creation of a high standard conference, and the CISIS conference would not exist without their help.

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Content

Intro
Preface
Organization
General Chair
General Co-chair
International Advisory Committee
Program Committee Chairs
Program Committee
Special Sessions
Fake News Detection and Prevention
Special Session Organizers
Program Committee
Mathematical Methods and Models in Cybersecurity
Special Session Organizers
Program Committee
Measurements for a Dynamic Cyber-risk Assessment
Special Session Organizers
Program Committee
Cibersecurity in a Hybrid Quantum World
Special Session Organizers
Program Committee
Anomaly/Intrusion Detection
Special Session Organizers
Program Committee
Organising Committee Chairs
Organising Committee
Contents
I Cryptocurrencies and Blockchain
Attacking with Bitcoin: Using Bitcoin to Build Resilient Botnet Armies
1 Introduction
2 Related Work and Background
2.1 Botnet Armies
2.2 Blockchain
2.3 Bitcoin
3 Attacking with Bitcoin
4 Implementation
4.1 Dynamic Shell Sessions
4.2 Writing Arbitrary Data to Bitcoin Blockchain
4.3 Reading Arbitrary Data from the Blockchain
5 The Good, the Bad, and the Ugly
6 Conclusion
A Payload and Listener
B Calc.exe Launched from Meterpreter
C Dynamic Transport Connection
D Simple Block Explorer
E Full Node Block Explorer
References
Blockchain-Based Systems in Land Registry, A Survey of Their Use and Economic Implications
1 Introduction
2 Blockchain and Land Registry Around the World
3 Benefits of Blockchain Technology in Land Registry
3.1 Time
3.2 Economic Resources
3.3 Inconsistencies and Corruption
4 Discussion
5 Conclusions
References
The Evolution of Privacy in the Blockchain: A Historical Survey
1 Introduction
2 Bitcoin as a Case Study
3 Loss of Privacy in Transactions
3.1 Mixing Protocols for Bitcoin
3.2 The Knowledge Limitation Protocols
4 Conclusions
References
Securing Cryptoasset Insurance Services with Multisignatures
1 Introduction
2 State of the Art
2.1 Risks Related to Cryptoasset Security
2.2 Countermeasures to Cryptoasset Security Risks
3 Cryptoasset Insurance System
3.1 Architecture
3.2 ICA Protocols
3.3 Discussion
4 Conclusions
References
Building an Ethereum-Based Decentralized Vehicle Rental System
1 Introduction
1.1 Background
2 Related Works
3 DApp Ecosystem
4 User Application
4.1 Smart Contracts
4.2 Implementation
5 Security Analysis Draft
6 Conclusions and Future Works
References
I Machine Learning
Off-Line Writer Verification Using Segments of Handwritten Samples and SVM
1 Introduction
2 Segments from Characters and Pressure Descriptor
3 Materials and Methods
3.1 Image Segment Repository
3.2 Classification Scheme
4 Identification Results
4.1 Using All the Basic Segments Together
5 Conclusions and Future Work
References
A Comparative Study to Detect Flowmeter Deviations Using One-Class Classifiers
1 Introduction
2 Case Study
2.1 Industrial Plant for Wind Turbine Blades Material
2.2 Dataset
3 Soft Computing Methods to Validate the Proposal
3.1 One-Class Techniques
3.2 Flowmeter Measurement Deviations.
4 Experiments and Results
4.1 Experiments Setup
4.2 Results
5 Conclusions and Future Works
References
IoT Device Identification Using Deep Learning
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 Approach
3.2 Data Preprocessing
3.3 Dataset and Environment
3.4 Model Architecture
3.5 Evaluation Matrix
4 Evaluation
5 Conclusion
References
Impact of Current Phishing Strategies in Machine Learning Models for Phishing Detection
1 Introduction
2 State of the Art
2.1 List-Based
2.2 Machine Learning
3 The Dataset: Phishing Index Login URL
4 Methodology
5 Experimentation
5.1 Datasets
5.2 Experimental Setup
6 Results and Discussion
7 Conclusions and Future Works
References
Crime Prediction for Patrol Routes Generation Using Machine Learning
1 Introduction
2 Related Works
3 Materials and Methods
3.1 Materials: Database of the National Police of Ecuador
3.2 Methods
4 Prediction Model and Patrol Routes
4.1 Crime Prediction Strategy
5 A Real Case-Study
6 Conclusions and Further Works
References
I Applications
Health Access Broker: Secure, Patient-Controlled Management of Personal Health Records in the Cloud
1 Introduction
2 Related Work
3 Health Access Broker
3.1 The HAB Workflow
3.2 HAB Algorithms
3.3 HAB Security
4 Prototype Implementation and Evaluation
5 Conclusion
References
Short Message Multichannel Broadcast Encryption
1 Introduction
2 Broadcast Encryption
2.1 Syntax
2.2 Security Model
3 Proposed Solutions
3.1 Basic Security
3.2 Strong Security
4 Security vs Efficiency
4.1 Bandwidth Efficiency
4.2 Channel Utilization Efficiency
5 Conclusions
References
Cybersecurity Overview of a Robot as a Service Platform
1 Introduction
2 Technological Background
2.1 Containerization Solutions
3 Proposed Architecture
3.1 SimUlation Framework for Education in Robotics (SUFFER)
3.2 Technical Approach
3.3 Container Hardening
4 Conclusions
References
Probabilistic and Timed Analysis of Security Protocols
1 Introduction
2 Probabilistic Timed Automaton
3 Probabilistic Timed Model for Security Protocols
3.1 Tuples Model
3.2 PTA Model
4 Experiments
5 Conclusions
References
Domain Knowledge: Predicting the Kind of Content Hosted by a Domain
1 Introduction
2 Data and Model
3 Application
3.1 Browsing Data: Concerns and Solutions
3.2 Bad Domains
3.3 Consumption of Pornography
4 Discussion
References
Evidence Identification and Acquisition Based on Network Link in an Internet of Things Environment
1 Introduction
2 Related Work
3 Proposed Approach
3.1 Device Identification
3.2 Event Detection
3.3 Hidden Link Identification
4 Evaluation
4.1 Step One: Device Identification
4.2 Step Two: Event Detection
4.3 Step Three: Hidden Link Detection
5 Conclusion and Future Work
References
Proposition of Innovative and Scalable Information System for Call Detail Records Analysis and Visualisation
1 Introduction
2 Related Work
3 General Approach, Architecture and Technology Stack
3.1 Data Pre-processing and Visual Analysis
3.2 Feature Extraction
3.3 Distributed Machine Learning
4 Experiments and Evaluation
4.1 Dataset and the Scenario
4.2 Quantitative Evaluation
5 Data Protection as Well as Legal, Privacy and Societal Aspects
6 Conclusions and Perspectives
References
Automatic Detection of Sensitive Information in Educative Social Networks
1 Introduction
2 Related Work
3 Information Sensitivity Assessment
4 Experiments
4.1 Dataset
4.2 Evaluation
5 Conclusions
References
I Special Session: Fake News Detection and Prevention
Detection of Artificial Images and Changes in Real Images Using Convolutional Neural Networks
1 Introduction
1.1 Review of the Most Common Forgery Types
1.2 Review of Forgery Detection
2 Convolutional Neural Network
3 Structure of Research Networks
4 Research Device
5 Database
6 Research and Results
7 Conclusion and Future Works
References
Distributed Architecture for Fake News Detection
1 Introduction
2 Platform Architecture
2.1 Physical Nodes Comprising the System
2.2 Verification Services
2.3 Messaging and Event Processing
3 Text Verification Services
3.1 Deep Recurrent Neural Network
3.2 Random Forest Combined with Word Embeddings
4 Experiments
5 Conclusions
References
Multi-stage News-Stance Classification Based on Lexical and Neural Features
1 Introduction
2 Related Work
3 Methodology
3.1 Lexical Features
3.2 Neural Features
4 Experiments
4.1 Multi-stage Classification Approaches
4.2 Multi-stage Model Settings
4.3 Data
5 Results
6 Conclusion
References
Fake News Detection
1 Introduction
2 Examination
3 Analysis
3.1 NLP Approaches
3.2 Deep Learning Approaches
4 Reporting
5 Conclusions and Future Work
References
Application of the BERT-Based Architecture in Fake News Detection
1 Introduction
2 BERT Overview
3 Proposed Application of the BERT
4 Evaluation of the Presented Method
4.1 Data Collections
4.2 Data Preprocessing
4.3 Experimental Settings
4.4 Results
5 Conclusion
References
I Special Session: Mathematical Methods and Models in Cybersecurity
Simulating Malware Propagation with Different Infection Rates
1 Introduction
2 A New Model with Two Different Transmission Rates
2.1 Description of the Model
2.2 Equilibrium Points
2.3 Basic Reproductive Number
2.4 Stability of the Equilibrium Points
3 Numerical Simulations
4 Design and Analysis of Control Measures
5 Comparison with the Original Model Where aI=aC
6 Conclusions
References
A Data Quality Assessment Model and Its Application to Cybersecurity Data Sources
1 Introduction
2 Experimental Section
2.1 Dataset
2.2 Technical Specifications
3 Data Quality Assessment Tool
3.1 Data Quality Dimensions
3.2 Data Quality Model
3.3 Data Quality Assessment Software
4 Cybersecurity Case Study
5 Conclusions
References
Towards Forecasting Time-Series of Cyber-Security Data Aggregates
1 Introduction
2 Forecasting Network Activity. Cybersecurity Reports
3 The Forecasting Technique
4 Some Experiments
5 Conclusion
References
Hybrid Approximate Convex Hull One-Class Classifier for an Industrial Plant
1 Introduction
2 Case Study
2.1 Laboratory Plant
2.2 Dataset Description
3 Classifier Approach
4 Description of the Techniques Used for the Experiment
4.1 Clustering Techniques
4.2 One-Class Classifier: Approximate Polytope Ensemble
5 Experiments and Results
6 Conclusions and Future Works
References
I Special Session: Measurements for a Dynamic Cyber-risk Assessment
Traceability and Accountability in Autonomous Agents
1 Introduction
2 Accountability Overview
2.1 Formalization
2.2 Practical Accountability Dimensions
2.3 Example
3 Experimental
3.1 Accountable Logging
3.2 Accountable Events
3.3 Accountable Behaviors
3.4 Accountability Process
4 Conclusions
References
The Order of the Factors DOES Alter the Product: Cyber Resilience Policies' Implementation Order
1 Introduction
2 Methodology
2.1 Identification of the Relevant Policies
2.2 Preliminary Implementation Order
2.3 Experts' Iterative Evaluation
3 Results
3.1 Risk Identification
3.2 Compliance
3.3 Strategy Development
3.4 Mitigation and Protection
3.5 Continuity Testing
3.6 Configuration Control
3.7 Training and Awareness
3.8 Collaboration
4 Discussion
5 Conclusions
References
Deep Learning Defenses Against Adversarial Examples for Dynamic Risk Assessment
1 Introduction
2 Related Work
2.1 Adversarial Training (Reactive)
2.2 Dimensionality Reduction (Proactive)
2.3 Prediction Similarity (Proactive)
3 Adversarial Attack Generation
4 Defenses to Adversarial Attacks
4.1 Dimensionality Reduction
4.2 Prediction Similarity
5 Results
6 Lessons Learned
References
A New Approach for Dynamic and Risk-Based Data Anonymization
1 Introduction
2 State of the Art
3 Dynamic and Risk-Based Anonymization
3.1 A Two-Phased Anonymization Process
3.2 K-Based Privacy Metrics
4 Experiments and Results
5 Conclusions and Future Work
References
I Special Session: Cybersecurity in a Hybrid Quantum World
An Innovative Linear Complexity Computation for Cryptographic Sequences
1 Introduction
2 LFSR-Based Sequence Generators: The Generalized Self-shrinking Generator
2.1 The Generalized Self-shrinking Generator
3 Binomial Sequences, Sierpinski's Triangle and Cellular Automata
3.1 Binomial Sequences
3.2 Sierpinski's Triangle and Cellular Automata
4 An Efficient Algorithm for Computing the LC
4.1 Application of the Algorithm to the Generalized Sequences
5 Conclusion
References
Randomness Analysis for GSS-sequences Concatenated
1 Introduction
2 Preliminaries
3 Statistical Randomness Analysis
3.1 Graphical Tests
3.2 Statistical Batteries of Tests
4 Conclusions and Future Work
References
Study of the Reconciliation Mechanism of NewHope
1 Introduction
2 Lattice-Based Cryptography
3 NewHope Key-Exchange Algorithm
4 Error Reconciliation Method
4.1 One Dimension
4.2 Two Dimensions
4.3 Three Dimensions
4.4 Four Dimensions
5 Conclusions
References
Securing Blockchain with Quantum Safe Cryptography: When and How?
1 Introduction
2 The Threat of Quantum Computing to Blockchain
3 Securing Blockchain with Quantum-Safe Solutions
3.1 QKD as a Cryptographic Primitive
3.2 Post-quantum Cryptographic Primitives
4 Applicable Scenarios of a Hybrid Approach
5 Conclusions
References
Blockchain in Education: New Challenges
1 Introduction
2 Blockchain Technology
3 Blockchain and Education
3.1 First Approaches
3.2 Some Areas of Applicability
3.3 Related Projects
4 Conclusions and Future Work
References
I Special Session: Anomaly/Intrusion Detection
Impact of Generative Adversarial Networks on NetFlow-Based Traffic Classification
1 Introduction
2 Related Work
3 Foundations
3.1 NetFlow
3.2 Long- and Short-Term Memory Networks
3.3 Wasserstein Generative Adversarial Network
4 Approach
4.1 Data Transformation
4.2 The LSTM-WGAN-GP Model
5 Experiments
5.1 Experimental Setup
5.2 Evaluation
5.3 Results
6 Discussion
7 Conclusion
References
Hybrid Model for Improving the Classification Effectiveness of Network Intrusion Detection
1 Introduction
1.1 Problem Statement
1.2 Contributions
1.3 Organization
2 Proposed Solution: Model Architecture
2.1 Selection of Dataset
2.2 Feature Engineering Using Classic AutoEncoder
2.3 Classification Using Deep Neural Network
3 Experimental Results and Analysis
3.1 Performance Evaluation
4 Conclusions and Future Work
References
Adaptive Approach for Density-Approximating Neural Network Models for Anomaly Detection
1 Introduction
2 Prior Art
3 Proposed Method
3.1 Auxiliary Set Construction
3.2 Training of the Model
4 Experimental Evaluation
4.1 Data Set
4.2 Evaluation Setup
4.3 Detection Accuracy Results
5 Discussion
6 Conclusion
References
Systematic Mapping of Detection Techniques for Advanced Persistent Threats
1 Introduction
2 Methodology
2.1 Search Planning
2.2 Search Process
2.3 Samples Selection
2.4 Data Extraction
3 Results
4 Conclusions
References
Neural Network Analysis of PLC Traffic in Smart City Street Lighting Network
1 Introduction
2 The Proposed Solution: Anomaly/Attacks Detection System
2.1 Outliers' Detection and Elimination Based on Cook's Distance
2.2 The PLC Traffic Features Forecasting Using Neural Networks
2.3 The Condition of Neural Network Model's Update
3 Experimental Results
4 Conclusions
References
Beta-Hebbian Learning for Visualizing Intrusions in Flows
1 Introduction
2 Related Work
3 Neural Projection Models for Intrusion Visualization
3.1 Cooperative Maximum Likelihood Hebbian Learning
3.2 Beta Hebbian Learning
4 Description of the Case Study
5 Experiments and Results
5.1 Results for Dataset Segment 545
5.2 Results for Dataset Segment 30
5.3 Results for Dataset Segment 107
5.4 Results for Dataset Segment 131
6 Conclusions and Future Work
References
Detecting Intrusion via Insider Attack in Database Transactions by Learning Disentangled Representation with Deep Metric Neural Network
1 Introduction
2 Related Works
3 The Proposed Method
3.1 Feature Vector Extraction from User Query
3.2 Learning Triplet Neural Network for Expressing Feature Space
4 Experimental Results
5 Conclusions
References
Author Index

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13th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2020)

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