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Proceedings of the International Conference on Applied Cybersecurity (ACS) 2023 [[electronic resource] /] / edited by Hind Zantout, Hani Ragab Hassen



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Autore: Zantout Hind Visualizza persona
Titolo: Proceedings of the International Conference on Applied Cybersecurity (ACS) 2023 [[electronic resource] /] / edited by Hind Zantout, Hani Ragab Hassen Visualizza cluster
Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Edizione: 1st ed. 2023.
Descrizione fisica: 1 online resource (73 pages)
Disciplina: 620.00285
Soggetto topico: Engineering - Data processing
Computational intelligence
Data protection
Data Engineering
Computational Intelligence
Data and Information Security
Altri autori: Ragab HassenHani  
Nota di contenuto: Intro -- Preface -- Conference Organization -- Contents -- Malicious Activity Detection Using AI -- DroidDissector: A Static and Dynamic Analysis Tool for Android Malware Detection -- 1 Introduction -- 2 Static Analysis Tool -- 3 Dynamic Analysis Tool -- 3.1 Feature Extraction -- 4 Conclusions -- References -- Android Malware Detection Using Control Flow Graphs and Text Analysis -- 1 Introduction -- 2 Related Work -- 3 Framework -- 3.1 Dataset -- 3.2 Data Extraction and Preprocessing -- 4 Experimental Results -- 5 Conclusion -- References -- NTFA: Network Flow Aggregator -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Evaluation -- 5 Conclusion -- References -- AI Applications in Cybersecurity -- A Password-Based Mutual Authentication Protocol via Zero-Knowledge Proof Solution -- 1 Introduction -- 2 Related Work -- 3 Proposed Technique -- 4 Scheme Analysis and Performance -- 5 Conclusion -- References -- A Cross-Validated Fine-Tuned GPT-3 as a Novel Approach to Fake News Detection -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Model Description -- 5 Fine-Tuning -- 6 Results -- 7 Validation -- 8 Conclusion -- References -- Enhancing Efficiency of Arabic Spam Filtering Based on Gradient Boosting Algorithm and Manual Hyperparameters Tuning -- 1 Introduction -- 2 Related Works -- 3 Proposed Spam Filter -- 3.1 Pre-processing and Feature Extraction -- 3.2 Classification -- 4 Experimentation -- 4.1 Dataset -- 4.2 Results -- 5 Conclusion -- References -- Cyberbullying: A BERT Bi-LSTM Solution for Hate Speech Detection -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Preprocessing -- 3.2 BERT-Bi-LSTM -- 4 Experiment and Results -- 5 Conclusion -- References -- Author Index.
Sommario/riassunto: This book presents the proceedings of the International Conference on Applied Cyber Security 2023 (ACS23), held in Dubai on the April 29, containing seven original contributions. Cybersecurity is continuously attracting the world’s attention and has gained in awareness and media coverage in the last decade. Not a single week passes without a major security incident that affects a company, sector, or governmental agencies. Most of the contributions are about applications of machine learning to accomplish several cybersecurity tasks, such as malware, network intrusion, and spam email detection. Similar trends of increasing AI applications are consistent with the current research and market trends in cybersecurity and other fields. We divided this book into two parts; the first is focused on malicious activity detection using AI, whereas the second groups AI applications to tackle a selection of cybersecurity problems. This book is suitable for cybersecurity researchers, practitioners, enthusiasts, as well as fresh graduates. It is also suitable for artificial intelligence researchers interested in exploring applications in cybersecurity. Prior exposure to basic machine learning concepts is preferable, but not necessary.
Titolo autorizzato: Proceedings of the International Conference on Applied Cybersecurity (ACS) 2023  Visualizza cluster
ISBN: 3-031-40598-6
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910746091603321
Lo trovi qui: Univ. Federico II
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Serie: Lecture Notes in Networks and Systems, . 2367-3389 ; ; 760