Machine Learning and Security
Clarence chio/david freeman
Résumé
Clarence Chio has a B.S. and M.S. in Computer Science from Stanford, specializing in data mining and artificial intelligence. He has given presentations, workshops, and trainings on machine learning and/or security at DEF CON and other infosec/software engineering conferences/meetups across 13 countries since 2015. Clarence is the co-founder of KaiTrust, a user security company working on an intelligent assistant that helps humans make better security decisions. He had previously been a member of the security research team at Shape Security, a community speaker with Intel, and a security consultant for Oracle. Clarence advises a handful of startups on security data science, and is also the founder and organizer of the “Data Mining for Cyber Security” meetup group, the largest gathering of security data scientists in the San Francisco Bay Area.
Machine learning has become a hot topic in computer security in the past couple of years as a technique that can counter advances in attacker competency. This book will provide security and software practitioners with a practical guide to approaching modern security with machine learning. If you have a surface-level understanding of machine learning, you’re ready to get started.
By explore a range of data mining techniques for solving security problems in security, such as spam, authentication, abuse, and malware, you’ll learn how to build scalable systems to combat intruders—and perhaps put an end to the cat-and-mouse game between attackers and defenders.
- Learn why and when machine learning is useful in the context of security
- Get a broad range of examples across different use cases
- Scale security data mining systems for deployment on web-scale platforms
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | O'Reilly |
| Auteur(s) | Clarence chio/david freeman |
| Parution | 15/02/2018 |
| Nb. de pages | 300 |
| Format | 15 x 25 |
| Poids | 666g |
| EAN13 | 9781491979907 |
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