The two-volume set LNICST 570 and 571 constitutes the refereed post-conference proceedings of the 14th EAI International Conference on Digital Forensics and Cyber Crime, ICDF2C 2023, held in New York City, NY, USA, during November 30, 2023.
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.
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Zielgruppe
Illustrationen
101
28 s/w Abbildungen, 101 farbige Abbildungen
XV, 325 p. 129 illus., 101 illus. in color.
Maße
Höhe: 235 mm
Breite: 155 mm
Dicke: 19 mm
Gewicht
ISBN-13
978-3-031-56579-3 (9783031565793)
DOI
10.1007/978-3-031-56580-9
Schweitzer Klassifikation
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.
