10 Machine Learning Blueprints You Should Know for Cybersecurity: Protect your systems and boost your defenses with cutting-edge AI techniques

Work on 10 practical projects, each with a blueprint for a different machine learning technique, and apply them in the real world to fight against cybercrime

Purchase of the print or Kindle book includes a free PDF eBook

Key Features:

• Learn how to frame a cyber security problem as a machine learning problem
• Examine your model for robustness against adversarial machine learning
• Build your portfolio, enhance your resume, and ace interviews to become a cybersecurity data scientist

Book Description:

Machine learning in security is harder than other domains because of the changing nature and abilities of adversaries, high stakes, and a lack of ground-truth data. This book will prepare machine learning practitioners to effectively handle tasks in the challenging yet exciting cybersecurity space.

The book begins by helping you understand how advanced ML algorithms work and shows you practical examples of how they can be applied to security-specific problems with Python - by using open source datasets or instructing you to create your own. In one exercise, you'll also use GPT 3.5, the secret sauce behind ChatGPT, to generate an artificial dataset of fabricated news. Later, you'll find out how to apply the expert knowledge and human-in-the-loop decision-making that is necessary in the cybersecurity space. This book is designed to address the lack of proper resources available for individuals interested in transitioning into a data scientist role in cybersecurity. It concludes with case studies, interview questions, and blueprints for four projects that you can use to enhance your portfolio.

By the end of this book, you'll be able to apply machine learning algorithms to detect malware, fake news, deep fakes, and more, along with implementing privacy-preserving machine learning techniques such as differentially private ML.

What You Will Learn:

• Use GNNs to build feature-rich graphs for bot detection and engineer graph-powered embeddings and features
• Discover how to apply ML techniques in the cybersecurity domain
• Apply state-of-the-art algorithms such as transformers and GNNs to solve security-related issues
• Leverage ML to solve modern security issues such as deep fake detection, machine-generated text identification, and stylometric analysis
• Apply privacy-preserving ML techniques and use differential privacy to protect user data while training ML models
• Build your own portfolio with end-to-end ML projects for cybersecurity

Who this book is for:

This book is for machine learning practitioners interested in applying their skills to solve cybersecurity issues. Cybersecurity workers looking to leverage ML methods will also find this book useful. An understanding of the fundamental machine learning concepts and beginner-level knowledge of Python programming are needed to grasp the concepts in this book. Whether you're a beginner or an experienced professional, this book offers a unique and valuable learning experience that'll help you develop the skills needed to protect your network and data against the ever-evolving threat landscape.

這本書的標題是「機器學習在網路安全中的應用」，它提供了10個實用專案的藍圖，每個專案都運用不同的機器學習技術，並將其應用於現實世界中對抗網路犯罪。

購買紙本或Kindle版本的書籍將包含一本免費的PDF電子書。

主要特點：
- 學習如何將網路安全問題轉化為機器學習問題
- 檢查模型在對抗對手機器學習攻擊方面的韌性
- 建立個人作品集，增強履歷，並在面試中脫穎而出，成為一名網路安全數據科學家

書籍描述：
由於對手的能力和性質不斷變化、風險高，以及缺乏確定性的數據，網路安全領域的機器學習比其他領域更加困難。本書將幫助機器學習從業者有效處理具有挑戰性但令人興奮的網路安全任務。

本書首先幫助讀者了解先進的機器學習算法的工作原理，並通過使用開源數據集或指導讀者創建自己的數據集，展示了如何將這些算法應用於安全特定問題的實際範例。在其中一個練習中，讀者還將使用ChatGPT背後的秘密武器GPT 3.5生成一個人工數據集，用於製造假新聞。隨後，讀者將了解在網路安全領域中所需的專業知識和人為決策。本書旨在解決對於有興趣轉職為網路安全數據科學家的個人而言，缺乏適當資源的問題。書末還提供了案例研究、面試問題和四個專案的藍圖，可用於增強個人作品集。

通過閱讀本書，您將能夠應用機器學習算法來檢測惡意軟體、假新聞、深度偽造等問題，並實施保護隱私的機器學習技術，如差分隱私。

學到的內容：
- 使用圖神經網絡（GNN）構建功能豐富的圖形以進行機器人檢測，並設計圖形驅動的嵌入和特徵
- 發現如何在網路安全領域應用機器學習技術
- 應用最先進的算法，如Transformer和GNN，解決與安全相關的問題
- 利用機器學習解決現代安全問題，如深度偽造檢測、機器生成文本識別和文體分析
- 應用保護隱私的機器學習技術，使用差分隱私保護用戶數據在訓練機器學習模型時
- 通過進行網路安全的端到端機器學習專案，建立個人作品集

本書適合機器學習從業者有興趣應用其技能解決網路安全問題的讀者。同時，希望利用機器學習方法的網路安全從業人員也會發現本書有用。閱讀者需要對基本的機器學習概念有一定的了解，並具備初級的Python編程知識，以理解本書中的概念。無論您是初學者還是經驗豐富的專業人士，本書都提供了獨特而有價值的學習體驗，將幫助您發展所需的技能，以保護您的網路和數據免受不斷變化的威脅。