Machine Learning and Deep Learning

Autor:	Dietmar P. F. Möller
Rok vydání:	2023
Předmět:	business.industry Computer science Deep learning Big data Digital transformation Machine learning computer.software_genre Intrusion Code (cryptography) The Internet Artificial intelligence business computer Cyber threats Network analysis
Zdroj:	Advances in Information Security ISBN: 9783031268441 Cybersecurity in Digital Transformation ISBN: 9783030605698
DOI:	10.1007/978-3-031-26845-8_8
Popis:	This chapter discusses the importance of Machine Learning and Deep Learning, two methodologies which have gained importance due to the impact of Digital Transformation and the increasing growth of data sets to Big Data generated through the Internet connectivity. Machine Learning is a subset of Artificial Intelligence used to create algorithms which can modify itself without human intervention to generate a desired output. Deep Learning is also a sub-set of Artificial Intelligence used to create algorithms and functions similar to those in Machine Learning, but there are numerous layers of these algorithms which provide different interpretation to the data it feeds on. Machine Learning and Deep Learning methods can be used for computer system or network analysis in case of cyber threat intrusion incidents detection. This is essential to prevent intrusion of malicious code and to enhance cybersecurity.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d72eb12f25bc1951bee325c83080f989 https://doi.org/10.1007/978-3-031-26845-8_8 Zobrazit plný text záznamu