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Machine learning for cybersecurity: innovative deep learning solutions

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As cybersecurity threats keep growing exponentially in scale, frequency, and impact, legacy-based threat detection systems have proven inadequate. This has prompted the use of machine learning (hereafter, ML) to help address the problem. But as organizations increasingly use intelligent cybersecurity techniques, the overall efficacy and benefit analysis of these ML-based digital security systems remain a subject of increasing scholarly inquiry. The present study seeks to expand and add to this growing body of literature by demonstrating the applications of ML-based data analysis techniques to various problem domains in cybersecurity. To achieve this objective, a rapid evidence assessment (REA) of existing scholarly literature on the subject matter is adopted. The aim is to present a snapshot of the various ways ML is being applied to help address cybersecurity threat challenges.

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Ketersediaan

Informasi Detail

Judul Seri

SpringerBriefs in Computer Science

No. Panggil

006.3 MAR m

Penerbit

Switzerland : Springer., 2022

Deskripsi Fisik

53 hlm

Bahasa

English

ISBN/ISSN

9783031158933

Klasifikasi

006.3

Tipe Isi

text

Tipe Media

-

Tipe Pembawa

-

Edisi

Ed. 1

Subjek

FT
ebook

Info Detail Spesifik

-

Pernyataan Tanggungjawab

Marwan Omar

Versi lain/terkait

Lampiran Berkas

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