Advances in Digital Forensics XVII

Name: Advances in Digital Forensics XVII | 17th IFIP WG 11.9 International Conference, Virtual Event, February 1-2, 2021, Revised Selected Papers
Brand: Springer
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17th IFIP WG 11.9 International Conference, Virtual Event, February 1-2, 2021, Revised Selected Papers

Gilbert Peterson Sujeet Shenoi(Herausgeber*in)

Springer (Verlag)

Erschienen am 14. Oktober 2021

XIV, 267 Seiten

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Inhalt

Intro
Contents
Contributing Authors
Preface
I THEMES AND ISSUES
Chapter 1 DIGITAL FORENSIC ACQUISITION KILL CHAIN - ANALYSIS AND DEMONSTRATION
1. Introduction
2. Related Work
3. Digital Forensic Acquisition Kill Chain
3.1 Background
3.2 Kill Chain Overview
3.3 Kill Chain Phases
4. Case-Motivated Kill Chain Example
5. Conclusions
Acknowledgement
References
Chapter 2 ENHANCING INDUSTRIAL CONTROL SYSTEM FORENSICS USING REPLICATION-BASED DIGITAL TWINS
1. Introduction
2. Background
2.1 Digital Twin
2.2 Digital Twin Security
2.3 Digital Forensics
3. Related Work
4. Replication Using Digital Twins
4.1 Replication and Replay Theorems
4.2 Conceptual Framework
5. Implementation and Evaluation
5.1 Implementation and Experimental Setup
5.2 Results and Evaluation
6. Discussion
7. Conclusions
Acknowledgement
References
Chapter 3 COMPARISON OF CYBER ATTACKS ON SERVICES IN THE CLEARNET AND DARKNET
1. Introduction
2. Background
3. Common Targets and Attacks
4. Related Work
5. Honeypot Deployment
5.1 Security Considerations
5.2 Deployment Process
6. Implementation Details
6.1 Virtual Machine Architectures
6.2 Honeypot Services
7. Experiments and Results
7.1 Service Deployments
7.2 Announcements
7.3 Observed Web Requests
7.4 Observed SSH and Telnet Access
7.5 Observed SMTP Requests
7.6 Observed FTP Requests
7.7 Discussion
8. Conclusions
Acknowledgement
References
II APPROXIMATE MATCHING TECHNIQUES
Chapter 4 USING PARALLEL DISTRIBUTED PROCESSING TO REDUCE THE COMPUTATIONAL TIME OF DIGITAL MEDIA SIMILARITY MEASURES
1. Introduction
2. Previous Work
3. Jaccard Indexes of Similarity
3.1 Jaccard Index
3.2 Jaccard Index with Normalized Frequency
4. Jaccard Index with Split Files
5. Results and Validation
6. Conclusions
References
Chapter 5 EVALUATION OF NETWORK TRAFFIC ANALYSIS USING APPROXIMATE MATCHING ALGORITHMS
1. Introduction
2. Foundations and Related Work
2.1 Current State of Approximate Matching
2.2 Approximate Matching Algorithms
3. Controlled Study
3.1 All vs. All Evaluation
3.2 Evaluation Methodology
4. Experimental Results and Optimizations
5. Conclusions
Acknowledgement
References
III ADVANCED FORENSIC TECHNIQUES
Chapter 6 LEVERAGING USB POWER DELIVERY IMPLEMENTATIONS FOR DIGITAL FORENSIC ACQUISITION
1. Introduction
2. USB Power Delivery Protocol
3. Research Methodology
4. Results
4.1 Information Gathering
4.2 Passive Monitoring
4.3 Firmware Files
4.4 Firmware Reverse Engineering
4.5 Apple Vendor-Defined Protocol
4.6 Firmware Modification and Rollback
5. Conclusions
Acknowledgements
References
Chapter 7 DETECTING MALICIOUS PDF DOCUMENTS USING SEMI-SUPERVISED MACHINE LEARNING
1. Introduction
2. Background and Related Work
2.1 PDF Document Structure
2.2 Document Entropy
2.3 Malicious PDF Document Detection
3. Malicious PDF Document Detection Method
3.1 Structural Features
3.2 Entropy-Based Statistical Features
3.3 Classification
4. Experiments and Results.
4.1 Dataset Creation and Experimental Setup
4.2 Evaluation Metrics
4.3 Feature Set Analysis
4.4 Classifier Analysis
4.5 Detection Method Comparison
5. Conclusions
Acknowledgement
References
Chapter 8 MALICIOUS LOGIN DETECTION USING LONG SHORT-TERM MEMORY WITH AN ATTENTION MECHANISM
1. Introduction
2. Related Work
3. Preliminaries
3.1 Detection Method Overview
3.2 Threat Model
4. Proposed Method
4.1 Host Vector Learning
4.2 Feature Extraction
4.3 Attention Mechanism
4.4 Classification Model Optimization
5. Experimental Evaluation
5.1 Dataset Description
5.2 Experimental Setup
5.3 Evaluated Models
5.4 Evaluation Results
5.5 Optimization and Learning Rate
6. Conclusions
References
IV NOVEL APPLICATIONS
Chapter 9 PREDICTING THE LOCATIONS OF UNREST USING SOCIAL MEDIA
1. Introduction
2. Related Work
3. Location Extraction from Web Forum Data
3.1 Web Forum Dataset
3.2 Dictionary-Based Semi-Supervised Learning
3.3 BiLSTM-CRF Model
3.4 n-Gram-ARM Algorithm
4. Experiments and Results
5. Conclusions
References
Chapter 10 EXTRACTING THREAT INTELLIGENCE RELATIONS USING DISTANT SUPERVISION AND NEURAL NETWORKS
1. Introduction
2. Related Work
2.1 Threat Intelligence Datasets
2.2 Threat Intelligence Information Extraction
3. Proposed Framework
3.1 Overview
3.2 Problem Specification
3.3 Dataset
3.4 Neural Network Model
4. Experiments and Results
4.1 Experiment Details
4.2 Comparison with Baseline Models
4.3 Extraction Results
5. Conclusions
Acknowledgement
References
Chapter 11 SECURITY AUDITING OF INTERNET OF THINGS DEVICES IN A SMART HOME
1. Introduction
2. Preliminaries
2.1 Security Standards and Best Practices
2.2 Security Auditing Challenges
2.3 Threat Model
3. Security Auditing Methodology
3.1 Step 1: Build a Knowledge Base
3.2 Step 2: Translate to Security Rules
3.3 Step 3: Audit IoT Device Security
4. Auditing Smart Home Security
4.1 Security Rule Definition
4.2 Data Collection
4.3 Formal Language Translation
4.4 Verification
4.5 Evidence Extraction
5. Security Auditing Framework
6. Experiments and Results
6.1 Experimental Setup
6.2 Experimental Results
7. Discussion
8. Related Work
9. Conclusions
References
V IMAGE FORENSICS
Chapter 12 INDIAN CURRENCY DATABASE FOR FORENSIC RESEARCH
1. Introduction
2. Related Work
3. Indian Currency Security Features
4. Indian Currency Database
4.1 Sample Collection
4.2 Security Feature Identification
4.3 Database Creation
5. Conclusions
References
Chapter 13 SECURITY AND PRIVACY ISSUES RELATED TO QUICK RESPONSE CODES
1. Introduction
2. QR Code Structure
3. QR Code Evolution
4. Key Issues
4.1 Authentication with QR Codes
4.2 Attacks Using QR Codes
4.3 Security and Privacy of QR Codes
5. Innovative Applications
5.1 Self-Authenticating Documents
5.2 Color QR Codes
5.3 Anti-Counterfeiting QR Codes
6. Conclusions
References

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