Machine learning techniques for cybersecurity (Record no. 33389)

000 -LEADER
fixed length control field a
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 241114b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031282584
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.8
Item number BER
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Bertino, Elisa
245 ## - TITLE STATEMENT
Title Machine learning techniques for cybersecurity
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Springer,
Date of publication, distribution, etc 2023
Place of publication, distribution, etc Cham :
300 ## - PHYSICAL DESCRIPTION
Extent xii, 165 p. ;
Other physical details ill.,
Dimensions 25 cm.
365 ## - TRADE PRICE
Price amount 2969.00
Price type code
Unit of pricing 01
490 ## - SERIES STATEMENT
Series statement Synthesis lectures on information security, privacy, and trust
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references.
520 ## - SUMMARY, ETC.
Summary, etc This book explores machine learning (ML) defenses against the many cyberattacks that make our workplaces, schools, private residences, and critical infrastructures vulnerable as a consequence of the dramatic increase in botnets, data ransom, system and network denials of service, sabotage, and data theft attacks. The use of ML techniques for security tasks has been steadily increasing in research and also in practice over the last 10 years. Covering efforts to devise more effective defenses, the book explores security solutions that leverage machine learning (ML) techniques that have recently grown in feasibility thanks to significant advances in ML combined with big data collection and analysis capabilities. Since the use of ML entails understanding which techniques can be best used for specific tasks to ensure comprehensive security, the book provides an overview of the current state of the art of ML techniques for security and a detailed taxonomy of security tasks and corresponding ML techniques that can be used for each task. It also covers challenges for the use of ML for security tasks and outlines research directions. While many recent papers have proposed approaches for specific tasks, such as software security analysis and anomaly detection, these approaches differ in many aspects, such as with respect to the types of features in the model and the dataset used for training the models. In a way that no other available work does, this book provides readers with a comprehensive view of the complex area of ML for security, explains its challenges, and highlights areas for future research. This book is relevant to graduate students in computer science and engineering as well as information systems studies, and will also be useful to researchers and practitioners who work in the area of ML techniques for security tasks
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer security
Topical term or geographic name as entry element Access control policies
Topical term or geographic name as entry element Autoencoders
Topical term or geographic name as entry element Anomaly detection
Topical term or geographic name as entry element Code coverage
Topical term or geographic name as entry element Control Flow Graph
Topical term or geographic name as entry element Firewall
Topical term or geographic name as entry element Hyperparameters
Topical term or geographic name as entry element Malware detection
Topical term or geographic name as entry element ML techniques
Topical term or geographic name as entry element Network Security Policies
Topical term or geographic name as entry element Random Forest
Topical term or geographic name as entry element Ransomware
Topical term or geographic name as entry element Reinforcement learning
Topical term or geographic name as entry element Static analysis
Topical term or geographic name as entry element Zero-day attacks
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Bhardwaj, Sonam
Personal name Cicala, Fabrizio
Personal name Gong, Sishuai
Personal name Karim, Imtiaz
Personal name Katsis, Charalampos
Personal name Lee, Hyunwoo
Personal name Li, Adrian Shuai
Personal name Mahgoub, Ashraf Y
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent location Current location Date acquired Source of acquisition Cost, normal purchase price Full call number Barcode Date last seen Koha item type
          DAU DAU 2024-11-12 Amazon 2969.00 005.8 BER 035143 2024-11-14 Books

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