Bücher von Yousef Farhaoui

This book is to provide a comprehensive reference for professionals in the field of data science and applications: artificial intelligence, big data, IoT, and blockchain. In summary, this book is expected to function as a helpful resource and manual, enabling readers to navigate the intricate domain of artificial intelligence, the Internet of things (IoT), and blockchain in smart environments. This book covers many topics related to integrating AI, IoT, blockchain, and smart environments. It begins by laying a solid foundation, introducing each technology's fundamental concepts and principles. Subsequent chapters explore applications and real-world use cases, demonstrating how AI, IoT, and blockchain can effectively address critical challenges within data science and applications.

This book reviews the state of the art of big data analysis, artificial intelligence, and smart environments. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science, artificial intelligence, and smart environments inspire novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. This book reviews the state of the art of big data analysis, artificial intelligence, and smart environments. It includes issues that pertain to signal processing, probability models, machine learning, data mining, database, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart city, etc. The papers in this book were the outcome of research conducted in this field of study. The latter makes use of applications and techniques related to data analysis in general and big data and smart city in particular.The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers, and industrial researchers, as well as anyone interested in big data analysis and artificial intelligence.

L'efficacité d'un système de détection d'intrusion dépend de sa ¿configurabilité¿, de sa robustesse et de la faible quantité de faux positifs (fausses alertes) et de faux négatifs (attaques non détectées) qu'il génère. Une lutte entre techniques d¿intrusion et IDS s¿est engagée, les IDS ayant pour conséquence une plus grande technicité des attaques sur IP, et les attaques actuelles imposant aux IDS d¿être plus complets et plus puissants. Néanmoins, comme tous les outils techniques, ils ont des limites que seule une analyse humaine peut compenser. A la manière des pare-feu, les détecteurs d'intrusion s¿améliorent chaque jour grâce à l'expérience acquise, mais ils deviennent aussi de plus en plus sensibles aux erreurs de configuration et de paramétrage. Par conséquent, il est plus que fondamental de former correctement les personnes chargées de la mise en ¿uvre et de l'exploitation des IDS. Malheureusement, il semble que subsiste là une grande partie de la difficulté. A ce jour, aucun outil ne permet de remplacer l'être humain dans un test d'intrusion.