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Titlebook: Digital Forensics and Cyber Crime; 14th EAI Internation Sanjay Goel,Paulo Roberto Nunes de Souza Conference proceedings 2024 ICST Institute

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發(fā)表于 2025-3-21 16:50:52 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Digital Forensics and Cyber Crime
副標(biāo)題14th EAI Internation
編輯Sanjay Goel,Paulo Roberto Nunes de Souza
視頻videohttp://file.papertrans.cn/280/279326/279326.mp4
叢書名稱Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engi
圖書封面Titlebook: Digital Forensics and Cyber Crime; 14th EAI Internation Sanjay Goel,Paulo Roberto Nunes de Souza Conference proceedings 2024 ICST Institute
描述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..
出版日期Conference proceedings 2024
關(guān)鍵詞Computer Science; Informatics; Conference Proceedings; Research; Applications
版次1
doihttps://doi.org/10.1007/978-3-031-56580-9
isbn_softcover978-3-031-56579-3
isbn_ebook978-3-031-56580-9Series ISSN 1867-8211 Series E-ISSN 1867-822X
issn_series 1867-8211
copyrightICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024
The information of publication is updating

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Catch Me if?You Can: Analysis of?Digital Devices and Artifacts Used in?Murder Casesn. Guilty verdicts made up 64.15% of the examined cases and 98.11% of the evidence was deemed inculpatory, or evidence that proves guilt. This work seeks to provide a refined outlook as to how digital evidence is used when conducting a criminal investigation to ameliorate the efficiency of the digit
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發(fā)表于 2025-3-22 03:27:38 | 只看該作者
Enhancing Incident Management by?an?Improved Understanding of?Data Exfiltration: Definition, Evaluatt step we evaluate three frequently used methods for cyber threat intelligence: Microsoft Threat Modeling Tool, the Malware Information and Sharing Platform (MISP), and the MITRE Adversarial Tactics, Techniques and Common Knowledge (ATT &CK) framework. Our evaluation goal is to find out whether thes
地板
發(fā)表于 2025-3-22 08:16:31 | 只看該作者
Identify Users on Dating Applications: A Forensic Perspective lines of inquiry for investigators are limited in identifying the offender’s real identity. There has been no study in literature into what investigators could obtain from these apps to identify another user if you only had one account, such as an account from a victim of a crime. Therefore, in thi
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發(fā)表于 2025-3-22 12:04:27 | 只看該作者
Removing Noise (Opinion Messages) for Fake News Detection in Discussion Forum Using BERT Modelritten Traditional Chinese from the most popular discussion forum in Hong Kong, namely, LIHKG, relating to local Government officials, then used the Bidirectional Encoder Representations from Transformers (BERT) model to identify opinion contents which achieve 98.7% accuracy, and generalized well in
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發(fā)表于 2025-3-22 13:35:12 | 只看該作者
A Multi-carrier Information Hiding Algorithm Based on Dual 3D Model Spectrum Analysisss indicators, the algorithm improves its BCR values by 17.78%, 12.46%, 10.19%, 7.00%, 14.44%, 10.79%, 14.05%, 10.54%, 19.53%, 13.70%, 14.17%, and 10.26%, respectively, when compared with the two comparison algorithms in the face of 12.5° rotation, 0.7% noise addition, 50% simplification, 40% cuttin
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發(fā)表于 2025-3-23 00:30:38 | 只看該作者
DEML: Data-Enhanced Meta-Learning Method for IoT APT Traffic Detectionperiments on a hybrid dataset where benign traffic comes from IoT-23 and APT traffic comes from Contagio. Experimental results show that our method outperforms the existing data enhancement methods. In addition, DEML achieves a detection accuracy of 99.35%, which is better than the baseline models i
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發(fā)表于 2025-3-23 04:50:15 | 只看該作者
Finding Forensic Artefacts in?Long-Term Frequency Band Occupancy Measurements Using Statistics and?Mutliers. Furthermore, we created two datasets of long-term frequency band occupancy measurements that were used to evaluate our approach. We also evaluated our datasets with different machine learning techniques, which demonstrate that Random Forest has the highest classification accuracy and sensit
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發(fā)表于 2025-3-23 08:53:37 | 只看該作者
IoT Malicious Traffic Detection Based on?Federated Learningl data for model training and testing, and the central server for model aggregation. The experimental results show that FlIMT achieves high detection accuracy on real data collected from IoT devices, and significantly lessens communication rounds.
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