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Author: Clint Bodungen
Publisher: Packt Publishing Ltd
ISBN: 1805125117
Category : Computers
Languages : en
Pages : 372
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Book Description
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. 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 Purchase of the print or Kindle book includes a free PDF eBook 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.
Author: Clint Bodungen
Publisher: Packt Publishing Ltd
ISBN: 1805125117
Category : Computers
Languages : en
Pages : 372
Get Book
Book Description
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. 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 Purchase of the print or Kindle book includes a free PDF eBook 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.
Author: Emmanuel Tsukerman
Publisher: Packt Publishing Ltd
ISBN: 1838556346
Category : Computers
Languages : en
Pages : 338
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Book Description
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.
Author: Alessandro Parisi
Publisher: Packt Publishing Ltd
ISBN: 1789805171
Category : Computers
Languages : en
Pages : 331
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Book Description
Build smart cybersecurity systems with the power of machine learning and deep learning to protect your corporate assets Key FeaturesIdentify and predict security threats using artificial intelligenceDevelop intelligent systems that can detect unusual and suspicious patterns and attacksLearn how to test the effectiveness of your AI cybersecurity algorithms and toolsBook Description Today's organizations spend billions of dollars globally on cybersecurity. Artificial intelligence has emerged as a great solution for building smarter and safer security systems that allow you to predict and detect suspicious network activity, such as phishing or unauthorized intrusions. This cybersecurity book presents and demonstrates popular and successful AI approaches and models that you can adapt to detect potential attacks and protect your corporate systems. You'll learn about the role of machine learning and neural networks, as well as deep learning in cybersecurity, and you'll also learn how you can infuse AI capabilities into building smart defensive mechanisms. As you advance, you'll be able to apply these strategies across a variety of applications, including spam filters, network intrusion detection, botnet detection, and secure authentication. By the end of this book, you'll be ready to develop intelligent systems that can detect unusual and suspicious patterns and attacks, thereby developing strong network security defenses using AI. What you will learnDetect email threats such as spamming and phishing using AICategorize APT, zero-days, and polymorphic malware samplesOvercome antivirus limits in threat detectionPredict network intrusions and detect anomalies with machine learningVerify the strength of biometric authentication procedures with deep learningEvaluate cybersecurity strategies and learn how you can improve themWho this book is for If you’re a cybersecurity professional or ethical hacker who wants to build intelligent systems using the power of machine learning and AI, you’ll find this book useful. Familiarity with cybersecurity concepts and knowledge of Python programming is essential to get the most out of this book.
Author: Emmanuel Tsukerman
Publisher:
ISBN: 9781789614671
Category : Computers
Languages : en
Pages : 346
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Book Description
Learn how to apply modern AI to create powerful cybersecurity solutions for malware, pentesting, social engineering, data privacy, and intrusion detection Key Features Manage data of varying complexity to protect your system using the Python ecosystem Apply ML to pentesting, malware, data privacy, intrusion detection system(IDS) and social engineering Automate your daily workflow by addressing various security challenges using the recipes covered in the book Book 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 learn Learn how to build malware classifiers to detect suspicious activities Apply ML to generate custom malware to pentest your security Use ML algorithms with complex datasets to implement cybersecurity concepts Create neural networks to identify fake videos and images Secure your organization from one of the most popular threats - insider threats Defend against zero-day threats by constructing an anomaly detection system Detect web vulnerabilities effectively by combining Metasploit and ML Understand how to train a model without exposing the training data Who 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.
Author: Haibo He
Publisher: John Wiley & Sons
ISBN: 1118025598
Category : Computers
Languages : en
Pages : 189
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Book Description
This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide applications from military security systems to civilian daily life. In this book, different application problems, including pattern recognition, classification, image recovery, and sequence learning, will be presented to show the capability of the proposed systems in learning, memory, and prediction. Therefore, this book will also provide potential new solutions to many real-world applications.
Author: Charbel Nemnom
Publisher: Packt Publishing Ltd
ISBN: 1787284549
Category : Computers
Languages : en
Pages : 415
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Book Description
Over 60 recipes to achieve a robust and advanced backup and recovery solution leveraging SCDPM Key FeaturesAdapt to the modern data center design challenges and improve storage efficiencyEffective recipes to help you create your own robust architectural designs Solve data protection and recovery problems in your organizationBook Description System Center Data Protection Manager (SCDPM) is a robust enterprise backup and recovery system that contributes to your BCDR strategy by facilitating the backup and recovery of enterprise data. With an increase in data recovery and protection problems faced in organizations, it has become important to keep data safe and recoverable. This book contains recipes that will help you upgrade to SCDPM and it covers the advanced features and functionality of SCDPM. This book starts by helping you install SCDPM and then moves on to post-installation and management tasks. You will come across a lot of useful recipes that will help you recover your VMware and Hyper-V VMs. It will also walk you through tips for monitoring SCDPM in different scenarios. Next, the book will also offer insights into protecting windows workloads followed by best practices on SCDPM. You will also learn to back up your Azure Stack Infrastructure using Azure Backup. You will also learn about recovering data from backup and implementing disaster recovery. Finally, the book will show you how to configure the protection groups to enable online protection and troubleshoot Microsoft Azure Backup Agent. What you will learnInstall and prepare SQL Server for the SCDPM databaseReduce backup storage with SCDPM and data deduplicationLearn about the prerequisites for supported Hyper-V Server protectionIntegrate SCDPM with other System Center products to build optimal servicesProtect and restore the SCDPM databaseProtect your data center by integrating SCDPM with Azure BackupManually create online recovery points and recover production data from AzureProtect and learn about the requirements to recover Azure Stack with SCDPMWho this book is for If you are an SCDPM administrator, this book will help you verify your knowledge and provide you with everything you need to know about the new release of System Center Data Protection Manager.
Author: Lutz H. Hamel
Publisher: John Wiley & Sons
ISBN: 1118211030
Category : Computers
Languages : en
Pages : 211
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Book Description
An easy-to-follow introduction to support vector machines This book provides an in-depth, easy-to-follow introduction to support vector machines drawing only from minimal, carefully motivated technical and mathematical background material. It begins with a cohesive discussion of machine learning and goes on to cover: Knowledge discovery environments Describing data mathematically Linear decision surfaces and functions Perceptron learning Maximum margin classifiers Support vector machines Elements of statistical learning theory Multi-class classification Regression with support vector machines Novelty detection Complemented with hands-on exercises, algorithm descriptions, and data sets, Knowledge Discovery with Support Vector Machines is an invaluable textbook for advanced undergraduate and graduate courses. It is also an excellent tutorial on support vector machines for professionals who are pursuing research in machine learning and related areas.
Author: Niels Brügger
Publisher: MIT Press
ISBN: 0262549719
Category : Computers
Languages : en
Pages : 199
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Book Description
An original methodological framework for approaching the archived web, both as a source and as an object of study in its own right. As life continues to move online, the web becomes increasingly important as a source for understanding the past. But historians have yet to formulate a methodology for approaching the archived web as a source of study. How should the history of the present be written? In this book, Niels Brügger offers an original methodological framework for approaching the web of the past, both as a source and as an object of study in its own right. While many studies of the web focus solely on its use and users, Brügger approaches the archived web as a semiotic, textual system in order to offer the first book-length treatment of its scholarly use. While the various forms of the archived web can challenge researchers' interactions with it, they also present a range of possibilities for interpretation. The Archived Web identifies characteristics of the online web that are significant now for scholars, investigates how the online web became the archived web, and explores how the particular digitality of the archived web can affect a historian's research process. Brügger offers suggestions for how to translate traditional historiographic methods for the study of the archived web, focusing on provenance, creating an overview of the archived material, evaluating versions, and citing the material. The Archived Web lays the foundations for doing web history in the digital age, offering important and timely guidance for today's media scholars and tomorrow's historians.
Author: Clint Bodungen
Publisher: McGraw Hill Professional
ISBN: 1259589722
Category : Computers
Languages : en
Pages : 544
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Book Description
Learn to defend crucial ICS/SCADA infrastructure from devastating attacks the tried-and-true Hacking Exposed way This practical guide reveals the powerful weapons and devious methods cyber-terrorists use to compromise the devices, applications, and systems vital to oil and gas pipelines, electrical grids, and nuclear refineries. Written in the battle-tested Hacking Exposed style, the book arms you with the skills and tools necessary to defend against attacks that are debilitating—and potentially deadly. Hacking Exposed Industrial Control Systems: ICS and SCADA Security Secrets & Solutions explains vulnerabilities and attack vectors specific to ICS/SCADA protocols, applications, hardware, servers, and workstations. You will learn how hackers and malware, such as the infamous Stuxnet worm, can exploit them and disrupt critical processes, compromise safety, and bring production to a halt. The authors fully explain defense strategies and offer ready-to-deploy countermeasures. Each chapter features a real-world case study as well as notes, tips, and cautions. Features examples, code samples, and screenshots of ICS/SCADA-specific attacks Offers step-by-step vulnerability assessment and penetration test instruction Written by a team of ICS/SCADA security experts and edited by Hacking Exposed veteran Joel Scambray
Author: Soma Halder
Publisher: Packt Publishing Ltd
ISBN: 178899096X
Category : Computers
Languages : en
Pages : 306
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Book Description
Get into the world of smart data security using machine learning algorithms and Python libraries Key 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 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 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 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
