Hands-On Machine Learning for Cybersecurity (eBook)

Safeguard your system by making your machines intelligent using the Python ecosystem
eBook Download: EPUB
2018
318 Seiten
Packt Publishing (Verlag)
978-1-78899-096-7 (ISBN)

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Hands-On Machine Learning for Cybersecurity -  Ozdemir Sinan Ozdemir,  Halder Soma Halder
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Get into the world of smart data security using machine learning algorithms and Python libraries




Key Features



  • Learn machine learning algorithms and cybersecurity fundamentals


  • Automate your daily workflow by applying use cases to many facets of security


  • Implement smart machine learning solutions to detect various cybersecurity problems





Book Description



Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain.






The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not.






Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems




What you will learn



  • Use machine learning algorithms with complex datasets to implement cybersecurity concepts


  • Implement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problems


  • Learn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDA


  • Understand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimes


  • Use TensorFlow in the cybersecurity domain and implement real-world examples


  • Learn how machine learning and Python can be used in complex cyber issues



Who this book is for



This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book


Get into the world of smart data security using machine learning algorithms and Python librariesKey FeaturesLearn machine learning algorithms and cybersecurity fundamentalsAutomate your daily workflow by applying use cases to many facets of securityImplement smart machine learning solutions to detect various cybersecurity problemsBook DescriptionCyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain.The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not.Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systemsWhat you will learnUse machine learning algorithms with complex datasets to implement cybersecurity conceptsImplement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problemsLearn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDAUnderstand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimesUse TensorFlow in the cybersecurity domain and implement real-world examplesLearn how machine learning and Python can be used in complex cyber issuesWho this book is forThis book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book
Erscheint lt. Verlag 31.12.2018
Sprache englisch
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Apache Spark • Big Data • Computer Security • decision trees • Ensemble Techniques • K-means • machine learning • machine learning algorithms • Naive Bayes • NLP • NumPy • Pandas • Python • Regression Analysis • Time-series analysis
ISBN-10 1-78899-096-X / 178899096X
ISBN-13 978-1-78899-096-7 / 9781788990967
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