Hands-on Machine Learning for Cyber Security: Safeguard your system by making your machines intelligent using Python ecosystem
Soma Halder, Sinan Ozdemir
- 出版商: Packt Publishing
- 出版日期: 2018-12-28
- 售價: $1,940
- 貴賓價: 9.5 折 $1,843
- 語言: 英文
- 頁數: 318
- 裝訂: Paperback
- ISBN: 1788992288
- ISBN-13: 9781788992282
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相關分類:
Python、程式語言、Machine Learning、資訊安全
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相關翻譯:
網絡安全之機器學習 (Hands-on Machine Learning for Cyber Security: Safeguard your system by making your machines intelligent using Python ecosystem) (簡中版)
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相關主題
商品描述
Get into the world of smart data security using the power of machine learning algorithms
Key Features
- Apply machine learning algorithms and cyber security fundamentals to secure your organization data using practical approach
- Be a Data Ninja by performing big data manipulation on any data size to secure your system
- Automate your daily workflow by applying the use cases to many facets of security
- Implement smart solutions to your existing cyber security products and effectively build intelligent solutions
Book Description
Machine Learning is a growing trend in every technological field including computer security. Many research and practical applications are in line which has a potential to change the way how data is secured. With this book, you will stand a chance to mark your developments in cyber security domain using machine learning capabilities.
This book begins with giving you the basics of machine learning in cyber security using python and their extensive libraries support. You will explore various machine learning domains such as time series analysis, ensemble modeling to get your foundations right. You will implement your learning in various examples such as building system to identify malicious URLs, bypass defensive technologies, and build a program for detecting email frauds and spam using supervised learning and Naive Bayes algorithm. Later you will learn to make effective use of K means algorithm, to develop a solution to detect and alert any malicious activity going on the network. Next, you will be building weightless and complex decision tree and you will implement Digital biometrics and fingerprint from users interaction 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 in creating models and training the system from previous fraudulent events so that they can be mitigated in future.
By the end of this book, you will be able to build, apply, and evaluate machine learning algorithms to identify potential threats such as intrusion detection and malware. You will be introduced to cutting-edge big data tools and GPU processing to show how these techniques can be applied to extremely large data sets to detect traffic and end-point behavior.
What you will learn
- Gain the knowledge on using machine learning algorithms to get started with the concepts in cyber security using complex datasets.
- Solve real world concerns of cyber security using Machine learning algorithms such as Clustering, K means, Linear regression, Naive Bayes etc
- Explore the beauty of Digital biometrics and fingerprinting for validating whether the user is impersonator or a legitimate user.
- Learn how to speed up the system using Python GPU libraries with NumPY, Scikit-learn and CUDA programs
- Learn to use deep learning in detecting financial frauds and train your system effectively so that they can be mitigated in future.
- Understand the power of Tensorflow in cybersecurity domain and implement real world examples
Who This Book Is For
This book is for the data scientists, machine learning developers, security researchers, and anyone who is curious to apply machine learning to up-skill computer security. Having some working knowledge of Python, basics of machine learning and cyber security fundamentals will help to get the most out of the book.
商品描述(中文翻譯)
進入智能數據安全世界,利用機器學習算法的力量
主要特點:
- 使用實用方法應用機器學習算法和網絡安全基礎知識來保護組織的數據
- 通過對任何數據大小進行大數據操作,成為數據忍者,以保護您的系統
- 通過應用用例自動化您的日常工作流程,應用於安全的多個方面
- 將智能解決方案應用於現有的網絡安全產品,並有效地構建智能解決方案
書籍描述:
機器學習是包括計算機安全在內的各個技術領域中的一個增長趨勢。許多研究和實際應用都有潛力改變數據安全的方式。通過本書,您將有機會利用機器學習能力在網絡安全領域取得發展。
本書首先介紹了使用Python和其廣泛的庫支持在網絡安全中應用機器學習的基礎知識。您將探索各種機器學習領域,如時間序列分析、集成建模,以建立您的基礎。您將在各種示例中實施所學知識,例如構建系統以識別惡意URL、繞過防禦技術,以及使用監督學習和朴素貝葉斯算法構建檢測電子郵件欺詐和垃圾郵件的程序。然後,您將學習如何有效使用K均值算法,開發檢測和警報網絡上任何惡意活動的解決方案。接下來,您將構建輕量級和複雜的決策樹,並實施從用戶互動中提取數字生物特徵和指紋,以驗證用戶是否為合法用戶。最後,您將了解如何通過Tensorflow改變遊戲規則,並學習深度學習如何在創建模型和訓練系統以應對未來的欺詐事件方面發揮作用。
通過閱讀本書,您將能夠構建、應用和評估機器學習算法,以識別潛在的威脅,如入侵檢測和惡意軟件。您將介紹尖端的大數據工具和GPU處理,展示這些技術如何應用於極大數據集以檢測流量和終端行為。
你將學到什麼:
- 獲得使用機器學習算法開始瞭解網絡安全概念的知識,並應用於複雜數據集。
- 使用機器學習算法(如聚類、K均值、線性回歸、朴素貝葉斯等)解決現實世界的網絡安全問題。
- 探索數字生物特徵和指紋驗證的美妙之處,以驗證用戶是否為冒名頂替者或合法用戶。
- 學習如何使用Python GPU庫(如NumPY、Scikit-learn和CUDA程序)加快系統速度。
- 學習如何使用深度學習檢測金融欺詐,並有效地訓練系統以應對未來的欺詐事件。
- 了解Tensorflow在網絡安全領域的威力,並實施真實世界的示例。
本書適合對象:
本書適合數據科學家、機器學習開發人員、安全研究人員以及對將機器學習應用於提升計算機安全性感興趣的任何人。具備一些Python工作知識、機器學習基礎知識和網絡安全基礎知識將有助於更好地理解本書內容。