Machine Learning for Cybersecurity: Innovative Deep Learning Solutions: SpringerBriefs in Computer Science
Autor Marwan Omaren Limba Engleză Paperback – 25 sep 2022
This SpringerBrief presents the underlying principles of machine learning and how to deploy various deep learning tools and techniques to tackle and solve certain challenges facing the cybersecurity industry.
By implementing innovative deep learning solutions, cybersecurity researchers, students and practitioners can analyze patterns and learn how to prevent cyber-attacks and respond to changing malware behavior.
The knowledge and tools introduced in this brief can also assist cybersecurity teams to become more proactive in preventing threats and responding to active attacks in real time. It can reduce the amount of time spent on routine tasks and enable organizations to use their resources more strategically. In short, the knowledge and techniques provided in this brief can help make cybersecurity simpler, more proactive, less expensive and far more effective
Advanced-level students in computer science studying machine learning with a cybersecurity focus will find this SpringerBrief useful as a study guide. Researchers and cybersecurity professionals focusing on the application of machine learning tools and techniques to the cybersecurity domain will also want to purchase this SpringerBrief.
Din seria SpringerBriefs in Computer Science
- Preț: 446.47 lei
- 20% Preț: 296.17 lei
- Preț: 475.83 lei
- 20% Preț: 325.63 lei
- 20% Preț: 166.97 lei
- 20% Preț: 335.65 lei
- 20% Preț: 406.90 lei
- 20% Preț: 323.00 lei
- 20% Preț: 323.00 lei
- 20% Preț: 322.81 lei
- 20% Preț: 322.17 lei
- 20% Preț: 322.35 lei
- 20% Preț: 321.85 lei
- Preț: 375.45 lei
- 20% Preț: 232.68 lei
- 20% Preț: 324.17 lei
- 20% Preț: 323.00 lei
- 20% Preț: 323.34 lei
- 20% Preț: 322.50 lei
- 20% Preț: 324.17 lei
- 20% Preț: 323.46 lei
- 20% Preț: 322.17 lei
- 20% Preț: 322.02 lei
- 20% Preț: 323.46 lei
- Preț: 374.08 lei
- Preț: 408.23 lei
- Preț: 341.50 lei
- 20% Preț: 324.49 lei
- Preț: 344.47 lei
- Preț: 376.80 lei
- Preț: 377.18 lei
- 20% Preț: 324.17 lei
- 20% Preț: 352.26 lei
- 20% Preț: 321.32 lei
- 20% Preț: 322.17 lei
- 20% Preț: 324.17 lei
- 20% Preț: 322.02 lei
- Preț: 374.46 lei
- 20% Preț: 320.21 lei
- 20% Preț: 323.34 lei
- 20% Preț: 324.17 lei
- 20% Preț: 231.84 lei
- 20% Preț: 294.95 lei
- 20% Preț: 322.50 lei
- 20% Preț: 321.52 lei
- 20% Preț: 323.34 lei
- 20% Preț: 323.00 lei
- 20% Preț: 323.80 lei
- 20% Preț: 323.80 lei
- 20% Preț: 324.49 lei
Preț: 320.67 lei
Preț vechi: 400.84 lei
-20% Nou
Puncte Express: 481
Preț estimativ în valută:
61.38€ • 63.83$ • 51.43£
61.38€ • 63.83$ • 51.43£
Carte tipărită la comandă
Livrare economică 14-28 martie
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9783031158926
ISBN-10: 303115892X
Pagini: 48
Ilustrații: VIII, 48 p. 32 illus., 22 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.1 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Computer Science
Locul publicării:Cham, Switzerland
ISBN-10: 303115892X
Pagini: 48
Ilustrații: VIII, 48 p. 32 illus., 22 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.1 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Computer Science
Locul publicării:Cham, Switzerland
Cuprins
1. Application of Machine Learning (ML) to Address Cyber Security Threats.- 2. New Approach to Malware Detection Using Optimized Convolutional Neural Network.- 3. Malware Anomaly Detection Using Local Outlier Factor Technique.
Notă biografică
Dr. Marwan Omar is an Associate Professor of Cybersecurity at Illinois Institute of Technology since August, 2022. Dr. Omar received a Master’s degree in Information Systems and Technology from the University of Phoenix, 2009 and a Doctorate Degree in Digital Systems Security from Colorado Technical University, 2012. Dr. Omar has a track record of publications in the area of cyber security along with extensive teaching experience as well as industry experience. Dr. Omar recently earned a Post-Doctoral certificate from the University of Fernando Pessoa, Portugal and holds numerous industry certifications including CEH, Sec+, GASF, and CDPSE, among others.
Textul de pe ultima copertă
This SpringerBrief presents the underlying principles of machine learning and how to deploy various deep learning tools and techniques to tackle and solve certain challenges facing the cybersecurity industry.
By implementing innovative deep learning solutions, cybersecurity researchers, students and practitioners can analyze patterns and learn how to prevent cyber-attacks and respond to changing malware behavior.
The knowledge and tools introduced in this brief can also assist cybersecurity teams to become more proactive in preventing threats and responding to active attacks in real time. It can reduce the amount of time spent on routine tasks and enable organizations to use their resources more strategically. In short, the knowledge and techniques provided in this brief can help make cybersecurity simpler, more proactive, less expensive and far more effective
Advanced-level students in computerscience studying machine learning with a cybersecurity focus will find this SpringerBrief useful as a study guide. Researchers and cybersecurity professionals focusing on the application of machine learning tools and techniques to the cybersecurity domain will also want to purchase this SpringerBrief.
Caracteristici
Learn emerging machine learning techniques to manage data and defend your information system networks using the Python ecosystem Apply Deep Learning to malware anomaly detection, intrusion detection system(IDS) by leveraging the Python ecosystem Implement innovative deep learning solutions to address emerging cybersecurity problems Learn machine learning techniques and cybersecurity fundamentals