Chatgpt For Cybersecurity Cookbook
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ChatGPT for Cybersecurity Cookbook
Author: Clint E. Bodungen
language: en
Publisher: Packt Publishing
Release Date: 2024-03-29
Catapult your cybersecurity expertise to new heights using expert-backed recipes.
ChatGPT for Cybersecurity Cookbook
Author: Clint Bodungen
language: en
Publisher: Packt Publishing Ltd
Release Date: 2024-03-29
Master ChatGPT and the OpenAI API and harness the power of cutting-edge generative AI and large language models to revolutionize the way you perform penetration testing, threat detection, and risk assessment. Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Enhance your skills by leveraging ChatGPT to generate complex commands, write code, and create tools Automate penetration testing, risk assessment, and threat detection tasks using the OpenAI API and Python programming Revolutionize your approach to cybersecurity with an AI-powered toolkit Book DescriptionAre you ready to unleash the potential of AI-driven cybersecurity? This cookbook takes you on a journey toward enhancing your cybersecurity skills, whether you’re a novice or a seasoned professional. By leveraging cutting-edge generative AI and large language models such as ChatGPT, you'll gain a competitive advantage in the ever-evolving cybersecurity landscape. ChatGPT for Cybersecurity Cookbook shows you how to automate and optimize various cybersecurity tasks, including penetration testing, vulnerability assessments, risk assessment, and threat detection. Each recipe demonstrates step by step how to utilize ChatGPT and the OpenAI API to generate complex commands, write code, and even create complete tools. You’ll discover how AI-powered cybersecurity can revolutionize your approach to security, providing you with new strategies and techniques for tackling challenges. As you progress, you’ll dive into detailed recipes covering attack vector automation, vulnerability scanning, GPT-assisted code analysis, and more. By learning to harness the power of generative AI, you'll not only expand your skillset but also increase your efficiency. By the end of this cybersecurity book, you’ll have the confidence and knowledge you need to stay ahead of the curve, mastering the latest generative AI tools and techniques in cybersecurity.What you will learn Master ChatGPT prompt engineering for complex cybersecurity tasks Use the OpenAI API to enhance and automate penetration testing Implement artificial intelligence-driven vulnerability assessments and risk analyses Automate threat detection with the OpenAI API Develop custom AI-enhanced cybersecurity tools and scripts Perform AI-powered cybersecurity training and exercises Optimize cybersecurity workflows using generative AI-powered techniques Who this book is for This book is for cybersecurity professionals, IT experts, and enthusiasts looking to harness the power of ChatGPT and the OpenAI API in their cybersecurity operations. Whether you're a red teamer, blue teamer, or security researcher, this book will help you revolutionize your approach to cybersecurity with generative AI-powered techniques. A basic understanding of cybersecurity concepts along with familiarity in Python programming is expected. Experience with command-line tools and basic knowledge of networking concepts and web technologies is also required.
Machine Learning for Cybersecurity Cookbook
Author: Emmanuel Tsukerman
language: en
Publisher: Packt Publishing Ltd
Release Date: 2019-11-25
Learn how to apply modern AI to create powerful cybersecurity solutions for malware, pentesting, social engineering, data privacy, and intrusion detection Key FeaturesManage data of varying complexity to protect your system using the Python ecosystemApply ML to pentesting, malware, data privacy, intrusion detection system(IDS) and social engineeringAutomate your daily workflow by addressing various security challenges using the recipes covered in the bookBook Description Organizations today face a major threat in terms of cybersecurity, from malicious URLs to credential reuse, and having robust security systems can make all the difference. With this book, you'll learn how to use Python libraries such as TensorFlow and scikit-learn to implement the latest artificial intelligence (AI) techniques and handle challenges faced by cybersecurity researchers. You'll begin by exploring various machine learning (ML) techniques and tips for setting up a secure lab environment. Next, you'll implement key ML algorithms such as clustering, gradient boosting, random forest, and XGBoost. The book will guide you through constructing classifiers and features for malware, which you'll train and test on real samples. As you progress, you'll build self-learning, reliant systems to handle cybersecurity tasks such as identifying malicious URLs, spam email detection, intrusion detection, network protection, and tracking user and process behavior. Later, you'll apply generative adversarial networks (GANs) and autoencoders to advanced security tasks. Finally, you'll delve into secure and private AI to protect the privacy rights of consumers using your ML models. By the end of this book, you'll have the skills you need to tackle real-world problems faced in the cybersecurity domain using a recipe-based approach. What you will learnLearn how to build malware classifiers to detect suspicious activitiesApply ML to generate custom malware to pentest your securityUse ML algorithms with complex datasets to implement cybersecurity conceptsCreate neural networks to identify fake videos and imagesSecure your organization from one of the most popular threats – insider threatsDefend against zero-day threats by constructing an anomaly detection systemDetect web vulnerabilities effectively by combining Metasploit and MLUnderstand how to train a model without exposing the training dataWho this book is for This book is for cybersecurity professionals and security researchers who are looking to implement the latest machine learning techniques to boost computer security, and gain insights into securing an organization using red and blue team ML. This recipe-based book will also be useful for data scientists and machine learning developers who want to experiment with smart techniques in the cybersecurity domain. Working knowledge of Python programming and familiarity with cybersecurity fundamentals will help you get the most out of this book.