Halder / Ozdemir Hands-On Machine Learning for Cybersecurity

Safeguard your system by making your machines intelligent using the Python ecosystem
1. Auflage 2018
ISBN: 978-1-78899-096-7
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 318 Seiten

No detailed description available for "Hands-On Machine Learning for Cybersecurity".

Autoren/Hrsg.

Halder, Soma

Ozdemir, Sinan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Inhaltsverzeichnis

Table of Contents - Basics of Machine Learning in Cyber Security

- Time series analysis and Ensemble modelling
- Segregating legitimate and lousy URLs
- Knocking down captchas
- Using Data Science to catch email frauds and spams
- Efficient Network Anomaly detection using K Means

- Decision Tree and context based malicious event detection
- Catching impersonators and hackers red handed
- Change the game with Tensorflow
- Financial frauds and how deep learning can mitigate them
- Practical Case Studies in Cyber Security

Über Autor(innen)

Halder Soma:

Soma Halder is the data science lead of the big data analytics group at Reliance Jio Infocomm Ltd, one of India's largest telecom companies. She specializes in analytics, big data, cybersecurity, and machine learning. She has approximately 10 years of machine learning experience, especially in the field of cybersecurity. She studied at the University of Alabama, Birmingham where she did her master's with an emphasis on Knowledge discovery and Data Mining and computer forensics. She has worked for Visa, Salesforce, and AT&T. She has also worked for start-ups, both in India and the US (E8 Security, Headway ai, and Norah ai). She has several conference publications to her name in the field of cybersecurity, machine learning, and deep learning.Ozdemir Sinan:

Sinan is an active lecturer focusing on large language models and a former lecturer of data science at the Johns Hopkins University. He is the author of multiple textbooks on data science and machine learning including "Quick Start Guide to LLMs". Sinan is currently the founder of LoopGenius which uses AI to help people and businesses boost their sales and was previously the founder of the acquired Kylie.ai, an enterprise-grade conversational AI platform with RPA capabilities. He holds a Master's Degree in Pure Mathematics from Johns Hopkins University and is based in San Francisco.