Digital Forensics and Cyber Crime
Springer International Publishing (Verlag)
978-3-031-56579-3 (ISBN)
The 41 revised full papers presented in these proceedings were carefully reviewed and selected from 105 submissions. The papers are organized in the following topical sections:
Volume I:
Crime profile analysis and Fact checking, Information hiding and Machine learning.
Volume II:
Password, Authentication and Cryptography, Vulnerabilities and Cybersecurity and forensics.
Crime profile analysis and Fact checking.- A Canary in the Voting Booth: Attacks on a Virtual Voting Machine.- Catch Me if You Can: Analysis of Digital Devices Artifacts Used in Murder Cases.- Enhancing Incident Management by an improved Understanding of Data Exfiltration: Definition, Evaluation, Review.- Identify Users on Dating Applications: A Forensic Perspective.- Removing Noise (Opinion Messages) For Fake News De-tection In Discussion Forum Using BERT Model.- Retruth Reconnaissance: A Digital Forensic Analysis of Truth Social.- Information hiding.- A Multi-Carrier Information Hiding Algorithm Based on Dual 3D Model Spectrum Analysis.- A Multi-Carrier Information Hiding Algorithm Based on Layered Compression of 3D Point Cloud Model.- Point cloud model information hiding algorithm based on multi-scale transformation and composite operator.- An Information Hiding Algorithm Baed on Multi-Carrier Fusion State Partitioning of 3D Models.- Machine learning.- CCBA: Code Poisoning-based Clean-Label Covert Backdoor Attack against DNNs.- Decoding HDF5: Machine Learning File Forensics and Data Injection.- DEML: Data-enhanced Meta-Learning Method for IoT APT Traffic Detection.- Finding Forensic Artefacts in Long-term Frequency Band Occupancy Measurements using Statistics and Machine Learning.- IoT Malicious Traffic Detection based on Federated Learning.- Persistent Clean-label Backdoor on Graph-based Semi-supervised Cybercrime Detection.- Backdoor Learning on Siamese Networks using Physical Triggers: FaceNet as a Case Study.- Research on Feature Selection Algorithm of Energy Curve.- Power Analysis Attack Based on GA-based Ensemble Learning.
| Erscheinungsdatum | 03.04.2024 |
|---|---|
| Reihe/Serie | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering |
| Zusatzinfo | XV, 325 p. 129 illus., 101 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Netzwerke ► Sicherheit / Firewall |
| Schlagworte | Applications • Computer Science • conference proceedings • Informatics • Research |
| ISBN-10 | 3-031-56579-7 / 3031565797 |
| ISBN-13 | 978-3-031-56579-3 / 9783031565793 |
| Zustand | Neuware |
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