Machine Learning For Red Team Hackers

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Machine Learning For Red Team Hackers

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Author : Dr Emmanuel Tsukerman
language : en
Publisher: Independently Published
Release Date : 2020-08-15

Machine Learning For Red Team Hackers written by Dr Emmanuel Tsukerman and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-15 with categories.

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.

Proceedings Of The Congress On Evolutionary Computation

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Author :
language : en
Publisher:
Release Date : 2004

Proceedings Of The Congress On Evolutionary Computation written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Evolutionary computation categories.

Principles Of Computer Security Lab Manual Fourth Edition

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Author : Vincent J. Nestler
language : en
Publisher: McGraw Hill Professional
Release Date : 2014-10-31

Principles Of Computer Security Lab Manual Fourth Edition written by Vincent J. Nestler and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-31 with Computers categories.

Practice the Computer Security Skills You Need to Succeed! 40+ lab exercises challenge you to solve problems based on realistic case studies Step-by-step scenarios require you to think critically Lab analysis tests measure your understanding of lab results Key term quizzes help build your vocabulary Labs can be performed on a Windows, Linux, or Mac platform with the use of virtual machines In this Lab Manual, you'll practice Configuring workstation network connectivity Analyzing network communication Establishing secure network application communication using TCP/IP protocols Penetration testing with Nmap, metasploit, password cracking, Cobalt Strike, and other tools Defending against network application attacks, including SQL injection, web browser exploits, and email attacks Combatting Trojans, man-in-the-middle attacks, and steganography Hardening a host computer, using antivirus applications, and configuring firewalls Securing network communications with encryption, secure shell (SSH), secure copy (SCP), certificates, SSL, and IPsec Preparing for and detecting attacks Backing up and restoring data Handling digital forensics and incident response Instructor resources available: This lab manual supplements the textbook Principles of Computer Security, Fourth Edition, which is available separately Virtual machine files Solutions to the labs are not included in the book and are only available to adopting instructors

Red Teaming Large Language Models

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Author : Dan O. Sterling
language : en
Publisher: david abayomi olunloyo
Release Date : 2025-12-12

Red Teaming Large Language Models written by Dan O. Sterling and has been published by david abayomi olunloyo this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-12 with Computers categories.

Defend the Future of Artificial Intelligence; Before It Defends Itself Large Language Models (LLMs) are rewriting the rules of technology. From powering search engines and virtual assistants to generating code and content, these AI systems are transforming the digital landscape at lightning speed. But with great power comes hidden risks and the attackers are already watching. Red Teaming Large Language Models: Playbooks, Payloads, and Protections is the ultimate hands-on guide for cybersecurity professionals, AI developers, and ethical hackers who refuse to wait for disaster to strike. This isn’t just another theory-heavy book, it’s a tactical playbook for stress-testing, breaking, and fortifying the most advanced AI systems in the world. Inside, you’ll discover: The Red Team Mindset – Learn to think like an adversary to expose vulnerabilities others overlook. Battle-Tested Playbooks – Step-by-step strategies for reconnaissance, infiltration, exploitation, and reporting. Real-World Payloads – A catalog of prompt injections, PII extraction tricks, denial-of-service attacks, and malicious content bypasses. Defensive Blueprints – From input sanitization to guardrails, fine-tuning, and architectural defenses, build resilient systems that withstand tomorrow’s threats. The Road Ahead – How AI will be used to fight AI in the never-ending battle between attackers and defenders. Where other books skim the surface, this guide dives deep into practical red teaming techniques, providing actionable methods you can immediately apply in secure environments. Every chapter is designed to sharpen your skills, strengthen your systems, and prepare you for the escalating war over AI security. Whether you’re a security engineer, AI researcher, or ethical hacker, this book arms you with the tools, insights, and mindset needed to stay one step ahead of adversaries in the age of artificial intelligence.

Vanity Fair

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Author :
language : en
Publisher:
Release Date : 2016

Vanity Fair written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Dressmaking categories.

Ai Powered Iot Hacking

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Author : Zephyrion Stravos
language : en
Publisher: Independently Published
Release Date : 2025-05-11

Ai Powered Iot Hacking written by Zephyrion Stravos and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-11 with Computers categories.

Welcome to the future-where your smart fridge can betray you, your voice assistant might take secret orders from strangers, and your security camera can be fooled by a few well-placed pixels. In the ever-evolving world of AI-powered IoT, cyber threats are getting smarter, sneakier, and downright scary. But don't worry-that's why you're here! AI-Powered IoT Hacking: Machine Learning Attacks and Defenses is your ultimate guide to understanding how artificial intelligence is being weaponized in IoT security. Whether you're an ethical hacker, a cybersecurity pro, or just someone who really doesn't want their smart doorbell turned into a spy tool, this book will take you deep into the world of AI-driven cyberattacks-and how to stop them. We'll uncover: AI's role in hacking IoT-How cybercriminals use machine learning to break into smart devices. Adversarial machine learning-Tricking AI models into making terrible decisions (like unlocking doors for the bad guys). Data poisoning-Feeding AI false data so it learns all the wrong things (think of it as brainwashing, but for machines). Voice assistant exploits-How hackers hijack Siri, Alexa, and Google Assistant with hidden commands. AI-powered malware-Self-learning cyber threats that evolve mid-attack. Defensive strategies-Using AI against attackers to strengthen IoT security. But this isn't just a doom-and-gloom guide to all the ways AI can ruin your life. It's part of the IoT Red Teaming: Offensive and Defensive Strategies series, designed to empower you with hands-on knowledge and practical security solutions. If you love this book, be sure to check out others in the series like Firmware Hacking & Reverse Engineering, Wireless Hacking Unleashed, and The Car Hacker's Guide-because trust me, everything is hackable, including your car, your smartwatch, and even your coffee maker. So, are you ready to take on the AI-powered cyber threats of the future? Whether you're here to learn, test, defend, or just make sure your IoT devices aren't secretly plotting against you, this book has you covered. Let's hack (ethically) and secure the AI-driven world-before it secures us.

Linux Journal

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Author :
language : en
Publisher:
Release Date : 1996

Linux Journal written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Linux categories.

Hands On Machine Learning For Cybersecurity

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Author : Soma Halder
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-31

Hands On Machine Learning For Cybersecurity written by Soma Halder and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-31 with Computers categories.

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

Reinforcement Learning For Cyber Operations

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Author : Abdul Rahman
language : en
Publisher: John Wiley & Sons
Release Date : 2025-01-22

Reinforcement Learning For Cyber Operations written by Abdul Rahman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-22 with Computers categories.

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.

Hacker S Guide To Machine Learning Concepts

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Author : Trilokesh Khatri
language : en
Publisher: Educohack Press
Release Date : 2025-01-03

Hacker S Guide To Machine Learning Concepts written by Trilokesh Khatri and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.

Hacker’s Guide to Machine Learning Concepts is crafted for those eager to dive into the world of ethical hacking. This book demonstrates how ethical hacking can help companies identify and fix vulnerabilities efficiently. With the rise of data and the evolving IT industry, the scope of ethical hacking continues to expand. We cover various hacking techniques, identifying weak points in programs, and how to address them. The book is accessible even to beginners, offering chapters on machine learning and programming in Python. Written in an easy-to-understand manner, it allows learners to practice hacking steps independently on Linux or Windows systems using tools like Netsparker. This book equips you with fundamental and intermediate knowledge about hacking, making it an invaluable resource for learners.