
Selected Papers from the 12th International Networking Conference
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Content
- Intro
- Message from Conference Chairs
- Contents
- Security
- Malware Behavior Through Network Trace Analysis
- 1 Introduction
- 2 Background and Related Work
- 2.1 Static Analysis
- 2.2 Dynamic Analysis on Host
- 2.3 Dynamic Analysis of Network Behavior
- 3 Capturing Malware Network Behavior
- 3.1 Analysis Environment
- 4 Sample Embedding
- 4.1 Application Data Unit (ADU)
- 4.2 Payload Byte Frequency
- 4.3 Malware Similarity
- 5 Evaluation of Contemporary Malware
- 5.1 Experiment Setup
- 6 Clustering Flow Embeddings Using Machine Learning
- 6.1 Clustering by ADU Sequence
- 6.2 Clustering by Payload Sizes
- 6.3 Sample Diversity
- 7 Discussion and Future Work
- 8 Conclusion
- References
- RC4D: A New Development of RC4 Encryption Algorithm
- 1 Introduction
- 2 Literature Review
- 3 Description of RC4
- 4 The Cryptanalysis of RC4
- 5 Modified RC4 Algorithm
- 6 Performance Evaluation
- 6.1 Distant-Equalities Statistical Test
- 6.2 Randomness Test
- 7 Implementation
- 8 Conclusions
- References
- A Novel Multimodal Biometric Authentication System Using Machine Learning and Blockchain
- 1 Introduction
- 2 Related Work
- 3 Proposed Approach
- 3.1 Biometrics Acquisition
- 3.2 Biometrics Verification and Normalisation
- 3.3 Machine Learning and Confidence Level
- 3.4 Blockchain
- 4 Experimental Analysis
- 4.1 Experiment Setup
- 4.2 Discussion and Results
- 5 Conclusion
- References
- User Attribution Through Keystroke Dynamics-Based Author Age Estimation
- 1 Introduction
- 2 Background
- 3 Method
- 3.1 Keystroke Dynamics Dataset
- 3.2 Feature Extraction and Feature Selection
- 3.3 Experimental Procedure and Validation of Models
- 4 Experiments and Results
- 4.1 Evaluation and Comparison of Results
- 5 Future Research Directions
- 6 Conclusion
- References
- 802.11 Man-in-the-Middle Attack Using Channel Switch Announcement
- 1 Introduction
- 2 Previous Attacks and Limitations
- 2.1 ARP Poisoning
- 2.2 Deauthentication
- 2.3 Disassociation Attack
- 2.4 Jamming Attack
- 3 Testbed and Results
- 3.1 Scenario Description
- 3.2 Rogue AP's Received Signal Strength Higher Than Legitimate AP
- 3.3 Legitimate AP's Received Signal Strength Higher Than Rogue AP
- 4 Conclusions
- References
- IoT
- Machine Learning Based IoT Intrusion Detection System: An MQTT Case Study (MQTT-IoT-IDS2020 Dataset)
- 1 Introduction
- 2 Dataset
- 3 Experiments and Results
- 4 Conclusion and Future Work
- References
- Smart Lamp or Security Camera? Automatic Identification of IoT Devices
- 1 Introduction
- 2 Motivation
- 3 Device Classification
- 4 Proof of Concept
- 4.1 Classification of Device Type
- 5 Evaluation
- 6 Legal Issues
- 7 Discussion
- 8 Related Work
- 9 Conclusion
- References
- Intelligent Self-reliant Cyber-Attacks Detection and Classification System for IoT Communication Using Deep Convolutional Neural Network
- 1 Introduction
- 2 Dataset of Cyber-Attacks
- 3 System Modeling
- 3.1 Implementation of Feature Engineering (FE) Subsystem
- 3.2 Implementation of Feature Learning (FL) Subsystem
- 3.3 Implementation of Detection and Classification (DC) Subsystem
- 3.4 System Integration
- 4 Simulation Environment
- 5 Results and Discussion
- 6 Conclusions and Future Directions
- References
- On Federated Cyber Range Network Interconnection
- 1 Introduction
- 2 Related Works
- 3 CR Interconnection Framework
- 3.1 Framework Metrics
- 3.2 CR Federation Requirements
- 3.3 Interconnection Requirements
- 3.4 Interconnection Techniques
- 3.5 Network Architecture
- 4 Results
- 4.1 Tests Parameters
- 5 Conclusions
- References
- Routing and Transport
- Multi-level Hierarchical Controller Placement in Software Defined Networking
- 1 Introduction
- 2 General Formulation of the Controller Placement Problem
- 2.1 Average-Case Latency
- 2.2 Worst-Case Latency
- 2.3 Formulation Constraints
- 3 Proposed Architecture and Methodology
- 4 Evaluation and Results
- 4.1 Western European NRENs Topology
- 4.2 First Optimization: Clustering-Based
- 4.3 Second Optimization: Master Controllers (MCs) Placement
- 4.4 Applicability Case Study
- 5 Conclusion
- References
- A Novel Congestion Avoidance Algorithm Using Two Routing Algorithms and Fast-Failover Group Table in SDN Networks
- 1 Introduction
- 2 Related Works
- 3 Proposed Algorithm
- 4 Performance Evaluation
- 4.1 Test Environment
- 4.2 Base Algorithm
- 4.3 Sample Topology
- 4.4 TCP Mode Performance
- 4.5 UDP Mode Performance
- 5 Conclusions
- References
- Impact of TCP Congestion Control Algorithms on HTTP/x Performance
- 1 Introduction
- 1.1 Motivation and Goals
- 2 Background and Related Work
- 3 Methodology
- 4 Experiments
- 4.1 Data
- 5 Results
- 5.1 continuous_flow Dataset
- 5.2 flags Dataset
- 5.3 Twitter Dataset
- 5.4 Netflix Dataset
- 5.5 Summary by Dataset
- 6 Conclusions
- References
- Wireless Networking
- Design and Preliminary Functionality Test of Road Network Traffic Monitoring System Based on Indoor SDWMN In-band Architecture
- 1 Introduction
- 2 Design of Indoor SDWMN In-band Architecture
- 2.1 Design of Indoor SDWMN In-band Testbed
- 2.2 Implementation of Indoor SDWMN In-band Testbed
- 3 Functionality Testing of Indoor SDWMN In-band Testbed
- 4 Conclusion
- References
- Power Optimized Source-Based-Jamming for Secure Transmission through Untrusted AF Relays
- 1 Introduction
- 2 System Description and Proposed Transmission Scheme
- 3 Secrecy Rate Analysis
- 3.1 Relay Selection
- 3.2 System Secrecy Rate
- 3.3 Secrecy Rate of Worst Case Scenario (WC)
- 4 Nelder-Mead Power Optimization Method (N-M)
- 5 Results and Discussion
- 6 Conclusions
- References
- Cyber Security Attacks on Identity and Location of Vehicle Ad-Hoc Networks
- 1 Introduction
- 1.1 VANET Architecture
- 1.2 VANET Communication
- 1.3 Methodology
- 1.4 Literature Review
- 2 Cyber Security Attack on Identity and Positioning
- 2.1 Single-Vehicle Faked Location (SVFL)
- 2.2 Multi-vehicle Faked Location (MVFL)
- 2.3 Single-Path Faked Location (SPFL)
- 2.4 Multi-path Faked Location (MPFL)
- 3 Cybersecurity Attack Experiment
- 3.1 Configuration of the Experiment on the Simulation
- 3.2 The Machine Learning Software
- 3.3 Classification Algorithms
- 3.4 The Generated Dataset
- 4 Cybersecurity Attack Results
- 4.1 Naïve Bayes Classifier Results
- 4.2 Random Tree Classifier Results
- 4.3 LogitBoost Classifier Results
- 4.4 Bagging Classifier Results
- 4.5 J48 Classifier Result
- 5 Discussion and Results
- 5.1 Time and Accuracy Performance
- 5.2 VANET Attack Detection Flowchart
- 5.3 The Generated Dataset
- 5.4 Detection's Time and Accuracy Performance
- 6 Conclusion and Future Work
- References
- Challenges in Developing a Wireless Sensor Network for an Agricultural Monitoring and Decision System
- 1 Introduction
- 2 Relevance of WSNs in the Field of Agriculture Monitoring and Decision Systems
- 3 Requirements and Constraints
- 4 Challenges
- 5 Proposed Approach
- 5.1 Sensor Selection
- 5.2 Sensor Node Concept
- 5.3 Energy Management and Supply Concept
- 5.4 Data Management
- 6 Conclusion
- References
- Author Index
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