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Security Enhancement of Big Data Analysis using Artificial Intelligence
Paperback

Security Enhancement of Big Data Analysis using Artificial Intelligence

$36.99
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

In this book, Protecting the privacy of computer networks containing consumer data is a vital concern for people, businesses, and governments. There has been a spike in threats/attacks on famous websites as attacks against networked networks are becoming more frightening and new techniques to target them are being used every day. Additionally, intrusion protection is used to prevent outside attempts by hackers and scammers. One approach to developing an intrusion detection system (IDS) is by learning from human-written traffic logs. Currently, the IDS needs two essential, discriminating and representative characteristics, all in order to have a high accuracy. An example is the "sparse" or "dimensionality" reduction strategies AE and PCA (PCA). The attribute extraction strategies employed by the speech recognition market are then used to create an RF classification simulation technique with K-Mean Cluster. The attempt to reduce the features of the dataset "CICIDs" from 78 to 45 is going to reduce the features of the dataset from 78 to 45 while maintaining a high precision of 99.7% in the Random Forest classifier with k-means clustering.

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MORE INFO
Format
Paperback
Publisher
Notion Press, Inc.
Country
United States
Date
9 September 2022
Pages
146
ISBN
9798888059517

This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

In this book, Protecting the privacy of computer networks containing consumer data is a vital concern for people, businesses, and governments. There has been a spike in threats/attacks on famous websites as attacks against networked networks are becoming more frightening and new techniques to target them are being used every day. Additionally, intrusion protection is used to prevent outside attempts by hackers and scammers. One approach to developing an intrusion detection system (IDS) is by learning from human-written traffic logs. Currently, the IDS needs two essential, discriminating and representative characteristics, all in order to have a high accuracy. An example is the "sparse" or "dimensionality" reduction strategies AE and PCA (PCA). The attribute extraction strategies employed by the speech recognition market are then used to create an RF classification simulation technique with K-Mean Cluster. The attempt to reduce the features of the dataset "CICIDs" from 78 to 45 is going to reduce the features of the dataset from 78 to 45 while maintaining a high precision of 99.7% in the Random Forest classifier with k-means clustering.

Read More
Format
Paperback
Publisher
Notion Press, Inc.
Country
United States
Date
9 September 2022
Pages
146
ISBN
9798888059517