Big Data Cyber Security Using Machine Learning

Name: Big Data Cyber Security Using Machine Learning
Brand: LAP LAMBERT Academic Publishing
SKU: 9786206783206
Price: 14756 HUF
Availability: InStock

Szerző: Anuradha Chinta, Kunchala Little Flower

Nyelv:

Kötés: Puha kötésű

Kiadó: LAP LAMBERT Academic Publishing

Elérhetőség: Beszállítói készleten

Küldés 5-8 napon belül

14 756 Ft

Cyber security in the context of big data is known to be a critical problem and presents a great cha...

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Szerző

Anuradha Chinta, Kunchala Little Flower

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2023

oldal

EAN

9786206783206

ISBN

6206783200

Enbook ID

44251813

Kiadó

LAP LAMBERT Academic Publishing

Súly

113

Méretek

150 x 220 x 4

Teljes leírás

Cyber security in the context of big data is known to be a critical problem and presents a great challenge to the research community. Machine learning algorithms have been suggested as candidates for handling big data security problems. Among these algorithms, support vector machines (SVMs) have achieved remarkable success on various classification problems. However, to establish an effective SVM, the user needs to deny the proper SVM configuration in advance, which is a challenging task that requires expert knowledge and a large amount of manual effort for trial and error. Here we formulate the SVM configuration process as a bi-objective optimization problem in which accuracy and model complexity are considered as two conflicting objectives. We propose a novel hyper-heuristic framework for bi-objective optimization that is independent of the problem domain. This is the first time that a hyper-heuristic has been developed for this problem. The proposed hyper-heuristic framework consists of a high-level strategy and low-level heuristics.

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Big Data Cyber Security Using Machine Learning

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