Symmetry-Adapted Machine Learning for Information Security

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Tác giả: James Park

Ngôn ngữ: eng

ISBN-13: 978-3039366422

Ký hiệu phân loại:

Thông tin xuất bản: Basel, Switzerland : MDPI - Multidisciplinary Digital Publishing Institute, 2020

Mô tả vật lý: 1 electronic resource (202 p.)

Bộ sưu tập: Tài liệu truy cập mở

ID: 225036

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.
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