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Author: Dr Emmanuel Tsukerman
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 100
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Book Description
Everyone knows that AI and machine learning are the future of penetration testing. Large cybersecurity enterprises talk about hackers automating and smartening their tools; The newspapers report on cybercriminals utilizing voice transfer technology to impersonate CEOs; The media warns us about the implications of DeepFakes in politics and beyond...This book finally teaches you how to use Machine Learning for Penetration Testing.This book will be teaching you, in a hands-on and practical manner, how to use the Machine Learning to perform penetration testing attacks, and how to perform penetration testing attacks ON Machine Learning systems. It will teach you techniques that few hackers or security experts know about.You will learn- how to supercharge your vulnerability fuzzing using Machine Learning.- how to evade Machine Learning malware classifiers.- how to perform adversarial attacks on commercially-available Machine Learning as a Service models.- how to bypass CAPTCHAs using Machine Learning.- how to create Deepfakes.- how to poison, backdoor and steal Machine Learning models.And you will solidify your slick new skills in fun hands-on assignments.
Author: Dr Emmanuel Tsukerman
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 100
Get Book Here
Book Description
Everyone knows that AI and machine learning are the future of penetration testing. Large cybersecurity enterprises talk about hackers automating and smartening their tools; The newspapers report on cybercriminals utilizing voice transfer technology to impersonate CEOs; The media warns us about the implications of DeepFakes in politics and beyond...This book finally teaches you how to use Machine Learning for Penetration Testing.This book will be teaching you, in a hands-on and practical manner, how to use the Machine Learning to perform penetration testing attacks, and how to perform penetration testing attacks ON Machine Learning systems. It will teach you techniques that few hackers or security experts know about.You will learn- how to supercharge your vulnerability fuzzing using Machine Learning.- how to evade Machine Learning malware classifiers.- how to perform adversarial attacks on commercially-available Machine Learning as a Service models.- how to bypass CAPTCHAs using Machine Learning.- how to create Deepfakes.- how to poison, backdoor and steal Machine Learning models.And you will solidify your slick new skills in fun hands-on assignments.
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: Marcus J. Carey
Publisher: John Wiley & Sons
ISBN: 1119643333
Category : Computers
Languages : en
Pages : 339
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Book Description
Want Red Team offensive advice from the biggest cybersecurity names in the industry? Join our tribe. The Tribe of Hackers team is back with a new guide packed with insights from dozens of the world’s leading Red Team security specialists. With their deep knowledge of system vulnerabilities and innovative solutions for correcting security flaws, Red Team hackers are in high demand. Tribe of Hackers Red Team: Tribal Knowledge from the Best in Offensive Cybersecurity takes the valuable lessons and popular interview format from the original Tribe of Hackers and dives deeper into the world of Red Team security with expert perspectives on issues like penetration testing and ethical hacking. This unique guide includes inspiring interviews from influential security specialists, including David Kennedy, Rob Fuller, Jayson E. Street, and Georgia Weidman, who share their real-world learnings on everything from Red Team tools and tactics to careers and communication, presentation strategies, legal concerns, and more Learn what it takes to secure a Red Team job and to stand out from other candidates Discover how to hone your hacking skills while staying on the right side of the law Get tips for collaborating on documentation and reporting Explore ways to garner support from leadership on your security proposals Identify the most important control to prevent compromising your network Uncover the latest tools for Red Team offensive security Whether you’re new to Red Team security, an experienced practitioner, or ready to lead your own team, Tribe of Hackers Red Team has the real-world advice and practical guidance you need to advance your information security career and ready yourself for the Red Team offensive.
Author: Himanshu Sharma
Publisher: Packt Publishing Ltd
ISBN: 178899700X
Category : Computers
Languages : en
Pages : 469
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Book Description
Your one-stop guide to learning and implementing Red Team tactics effectively Key FeaturesTarget a complex enterprise environment in a Red Team activityDetect threats and respond to them with a real-world cyber-attack simulationExplore advanced penetration testing tools and techniquesBook Description Red Teaming is used to enhance security by performing simulated attacks on an organization in order to detect network and system vulnerabilities. Hands-On Red Team Tactics starts with an overview of pentesting and Red Teaming, before giving you an introduction to few of the latest pentesting tools. We will then move on to exploring Metasploit and getting to grips with Armitage. Once you have studied the fundamentals, you will learn how to use Cobalt Strike and how to set up its team server. The book introduces some common lesser known techniques for pivoting and how to pivot over SSH, before using Cobalt Strike to pivot. This comprehensive guide demonstrates advanced methods of post-exploitation using Cobalt Strike and introduces you to Command and Control (C2) servers and redirectors. All this will help you achieve persistence using beacons and data exfiltration, and will also give you the chance to run through the methodology to use Red Team activity tools such as Empire during a Red Team activity on Active Directory and Domain Controller. In addition to this, you will explore maintaining persistent access, staying untraceable, and getting reverse connections over different C2 covert channels. By the end of this book, you will have learned about advanced penetration testing tools, techniques to get reverse shells over encrypted channels, and processes for post-exploitation. What you will learnGet started with red team engagements using lesser-known methodsExplore intermediate and advanced levels of post-exploitation techniquesGet acquainted with all the tools and frameworks included in the Metasploit frameworkDiscover the art of getting stealthy access to systems via Red TeamingUnderstand the concept of redirectors to add further anonymity to your C2Get to grips with different uncommon techniques for data exfiltrationWho this book is for Hands-On Red Team Tactics is for you if you are an IT professional, pentester, security consultant, or ethical hacker interested in the IT security domain and wants to go beyond Penetration Testing. Prior knowledge of penetration testing is beneficial.
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
Author: Patrick Hall
Publisher: "O'Reilly Media, Inc."
ISBN: 1098102401
Category : Computers
Languages : en
Pages : 469
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Book Description
The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI—a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public. Learn technical approaches for responsible AI across explainability, model validation and debugging, bias management, data privacy, and ML security Learn how to create a successful and impactful AI risk management practice Get a basic guide to existing standards, laws, and assessments for adopting AI technologies, including the new NIST AI Risk Management Framework Engage with interactive resources on GitHub and Colab
Author: Abdul Rahman
Publisher: John Wiley & Sons
ISBN: 1394206453
Category : Computers
Languages : en
Pages : 293
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Book Description
A comprehensive and up-to-date application of reinforcement learning concepts to offensive and defensive cybersecurity In Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing, a team of distinguished researchers delivers an incisive and practical discussion of reinforcement learning (RL) in cybersecurity that combines intelligence preparation for battle (IPB) concepts with multi-agent techniques. The authors explain how to conduct path analyses within networks, how to use sensor placement to increase the visibility of adversarial tactics and increase cyber defender efficacy, and how to improve your organization's cyber posture with RL and illuminate the most probable adversarial attack paths in your networks. Containing entirely original research, this book outlines findings and real-world scenarios that have been modeled and tested against custom generated networks, simulated networks, and data. You'll also find: A thorough introduction to modeling actions within post-exploitation cybersecurity events, including Markov Decision Processes employing warm-up phases and penalty scaling Comprehensive explorations of penetration testing automation, including how RL is trained and tested over a standard attack graph construct Practical discussions of both red and blue team objectives in their efforts to exploit and defend networks, respectively Complete treatment of how reinforcement learning can be applied to real-world cybersecurity operational scenarios Perfect for practitioners working in cybersecurity, including cyber defenders and planners, network administrators, and information security professionals, Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing will also benefit computer science researchers.
Author: Cybellium
Publisher: Cybellium Ltd
ISBN: 1836797524
Category : Computers
Languages : en
Pages : 299
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Book Description
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Author: Johann Rehberger
Publisher: Packt Publishing Ltd
ISBN: 1838825509
Category : Computers
Languages : en
Pages : 525
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Book Description
Develop your red team skills by learning essential foundational tactics, techniques, and procedures, and boost the overall security posture of your organization by leveraging the homefield advantage Key FeaturesBuild, manage, and measure an offensive red team programLeverage the homefield advantage to stay ahead of your adversariesUnderstand core adversarial tactics and techniques, and protect pentesters and pentesting assetsBook Description It's now more important than ever for organizations to be ready to detect and respond to security events and breaches. Preventive measures alone are not enough for dealing with adversaries. A well-rounded prevention, detection, and response program is required. This book will guide you through the stages of building a red team program, including strategies and homefield advantage opportunities to boost security. The book starts by guiding you through establishing, managing, and measuring a red team program, including effective ways for sharing results and findings to raise awareness. Gradually, you'll learn about progressive operations such as cryptocurrency mining, focused privacy testing, targeting telemetry, and even blue team tooling. Later, you'll discover knowledge graphs and how to build them, then become well-versed with basic to advanced techniques related to hunting for credentials, and learn to automate Microsoft Office and browsers to your advantage. Finally, you'll get to grips with protecting assets using decoys, auditing, and alerting with examples for major operating systems. By the end of this book, you'll have learned how to build, manage, and measure a red team program effectively and be well-versed with the fundamental operational techniques required to enhance your existing skills. What you will learnUnderstand the risks associated with security breachesImplement strategies for building an effective penetration testing teamMap out the homefield using knowledge graphsHunt credentials using indexing and other practical techniquesGain blue team tooling insights to enhance your red team skillsCommunicate results and influence decision makers with appropriate dataWho this book is for This is one of the few detailed cybersecurity books for penetration testers, cybersecurity analysts, security leaders and strategists, as well as red team members and chief information security officers (CISOs) looking to secure their organizations from adversaries. The program management part of this book will also be useful for beginners in the cybersecurity domain. To get the most out of this book, some penetration testing experience, and software engineering and debugging skills are necessary.
Author: Paul Geertsema
Publisher: Taylor & Francis
ISBN: 100088600X
Category : Business & Economics
Languages : en
Pages : 181
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Book Description
Machine learning can help managers make better predictions, automate complex tasks and improve business operations. Managers who are familiar with machine learning are better placed to navigate the increasingly digital world we live in. There is a view that machine learning is a highly technical subject that can only be understood by specialists. However, many of the ideas that underpin machine learning are straightforward and accessible to anyone with a bit of curiosity. This book is for managers who want to understand what machine learning is about, but who lack a technical background in computer science, statistics or math. The book describes in plain language what machine learning is and how it works. In addition, it explains how to manage machine learning projects within an organization. This book should appeal to anyone that wants to learn more about using machine learning to drive value in real-world organizations.
