Proceedings of the International Conference on Artificial Intelligence, Security, and Networking (CAISN 2024) : Innovative Approaches in AI, Security, and Networking / edited by Mohamed Lazaar, Youssef Fakhri, Adil El Makrani.

Format:

Book

Author/Creator:

Lazaar, Mohamed.

Contributor:

Anthonysamy.

Series:

Lecture Notes in Networks and Systems, 2367-3389 ; 1606

Language:

English

Subjects (All):

Engineering--Data processing.

Engineering.

Computational intelligence.

Big data.

Artificial intelligence.

Data Engineering.

Computational Intelligence.

Big Data.

Artificial Intelligence.

Local Subjects:

Data Engineering.

Computational Intelligence.

Big Data.

Artificial Intelligence.

Physical Description:

1 online resource (795 pages)

Edition:

1st ed. 2026.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2026.

Summary:

This book presents a selection of 42 original and peer-reviewed research papers from the International Conference on Artificial Intelligence, Security and Networking (CAISN 2024) held at the Faculty of Sciences, Ibn Tofail University, Kenitra, Morocco. Covering cutting-edge topics in AI, cybersecurity, communication networks, cloud computing, embedded systems, and their applications in smart cities and industrial automation, this book highlights recent advances and emerging trends in intelligent systems and secure technologies. CAISN 2024 brought together a diverse group of researchers and professionals from academia and industry to share innovations and challenges shaping the future of intelligent and secure systems. This book serves as a valuable reference for students, researchers, engineers, and practitioners seeking insights into the rapidly evolving fields of artificial intelligence, networking, and security.

Contents:

1.Comparing LSTM, CNN, and BERT Models in Oil Price Forecasting

2.Advanced Intrusion Detection Systems: A Comparative Study of Deep Learning and Ensemble Learning Models for IIoT Networks

3.Enhancing Large Language Models with Retrieval Augmented Generation for a Trusted Help Desk Solution

4.A New Contextual Model to Overcome the Recommender Systems Issues: An Exploratory Study

5.Comparative Study between YOLOv5 and YOLOv8 in Object Detection and Re-Identification using the DukeMTMC-reID Dataset

41.MAGENTA+: Detection of Arabic Machine-Generated Text across Domains

42.Deep Learning-Based Classification of Brain Tumor MRI Images: A Comparative Study.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

3-032-03695-X

9783032036957

OCLC:

1572195680