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Symmetry-Adapted Machine Learning for Information Security

By Park, James (Jong Hyuk)

Product Image: Symmetry-Adapted Machine Learning for Information Security

Symmetry-Adapted Machine Learning for Information Security

By Park, James (Jong Hyuk)

0 - Default Title
Description
Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis.
Product details
Number of Pages:
202
Release Date:
2020-08-07
Publication Date:
2020-08-07
Publisher:
MDPI AG
Languages:
Original: English
ISBN10:
3039366424
ISBN13:
9783039366422
GPSR Manufacturer Reference:
[email protected]
Weight:
705 g
Height:
175 cm
Width:
250 cm
Thickness:
18 cm
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