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Mastering hacking with AI

Mastering hacking with AI
Author: Kris Hermans
Publisher: Cybellium Ltd
Total Pages: 95
Release:
Genre: Computers
ISBN:
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In the rapidly evolving world of cybersecurity, the intersection of hacking and artificial intelligence (AI) has become an arena of immense potential. "Mastering Hacking with AI" by Kris Hermans is your comprehensive guide to harnessing the power of AI for ethical hacking purposes. This groundbreaking book takes you on a transformative journey, equipping you with the knowledge and skills to master the fusion of hacking and AI. Inside this groundbreaking book, you will: Explore the core principles of hacking and AI, including machine learning techniques, natural language processing, anomaly detection, and adversarial attacks, enabling you to develop advanced hacking strategies. Gain hands-on experience through real-world examples, step-by-step tutorials, and AI-driven tools, allowing you to apply AI techniques to identify vulnerabilities, automate penetration testing, and enhance threat intelligence. Understand the ethical implications of AI-driven hacking and learn how to responsibly use AI for cybersecurity purposes, adhering to legal and ethical frameworks. Stay ahead of the curve with discussions on emerging trends in AI and their impact on cybersecurity, such as AI-powered defences, deepfake detection, and autonomous threat hunting.

Machine Learning for Red Team Hackers

Machine Learning for Red Team Hackers
Author: Dr Emmanuel Tsukerman
Publisher: Independently Published
Total Pages: 100
Release: 2020-08-15
Genre:
ISBN:
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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.

Hacking Artificial Intelligence

Hacking Artificial Intelligence
Author: Davey Gibian
Publisher: Rowman & Littlefield
Total Pages: 154
Release: 2022-05-05
Genre: Computers
ISBN: 1538155095
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Sheds light on the ability to hack AI and the technology industry’s lack of effort to secure vulnerabilities. We are accelerating towards the automated future. But this new future brings new risks. It is no surprise that after years of development and recent breakthroughs, artificial intelligence is rapidly transforming businesses, consumer electronics, and the national security landscape. But like all digital technologies, AI can fail and be left vulnerable to hacking. The ability to hack AI and the technology industry’s lack of effort to secure it is thought by experts to be the biggest unaddressed technology issue of our time. Hacking Artificial Intelligence sheds light on these hacking risks, explaining them to those who can make a difference. Today, very few people—including those in influential business and government positions—are aware of the new risks that accompany automated systems. While society hurdles ahead with AI, we are also rushing towards a security and safety nightmare. This book is the first-ever layman’s guide to the new world of hacking AI and introduces the field to thousands of readers who should be aware of these risks. From a security perspective, AI is today where the internet was 30 years ago. It is wide open and can be exploited. Readers from leaders to AI enthusiasts and practitioners alike are shown how AI hacking is a real risk to organizations and are provided with a framework to assess such risks, before problems arise.

Mastering Machine Learning for Penetration Testing

Mastering Machine Learning for Penetration Testing
Author: Chiheb Chebbi
Publisher: Packt Publishing Ltd
Total Pages: 264
Release: 2018-06-27
Genre: Language Arts & Disciplines
ISBN: 178899311X
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Become a master at penetration testing using machine learning with Python Key Features Identify ambiguities and breach intelligent security systems Perform unique cyber attacks to breach robust systems Learn to leverage machine learning algorithms Book Description Cyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it’s important for pentesters and security researchers to understand how these systems work, and to breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you’ve gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you’ll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you’ll focus on topics such as network intrusion detection and AV and IDS evasion. We’ll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system. By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system. What you will learn Take an in-depth look at machine learning Get to know natural language processing (NLP) Understand malware feature engineering Build generative adversarial networks using Python libraries Work on threat hunting with machine learning and the ELK stack Explore the best practices for machine learning Who this book is for This book is for pen testers and security professionals who are interested in learning techniques to break an intelligent security system. Basic knowledge of Python is needed, but no prior knowledge of machine learning is necessary.

Mastering Black and White Hat hacking

Mastering Black and White Hat hacking
Author: Cybellium Ltd
Publisher: Cybellium Ltd
Total Pages: 122
Release: 2023-09-05
Genre: Computers
ISBN:
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Master the Art of Ethical Hacking with "Black and White Hat Hacking" by Kris Hermans In today's digital landscape, cybersecurity has become paramount. Understanding both the offensive and defensive sides of hacking is crucial for safeguarding digital assets. "Black and White Hat Hacking" by Kris Hermans is your comprehensive guide to mastering the art of ethical hacking and enhancing your cybersecurity skills. Inside this transformative book, you will: Learn the techniques and tools used by both black hat hackers, who exploit vulnerabilities, and white hat hackers, who protect against them. Gain a deep understanding of the various attack vectors, such as network and web application vulnerabilities, social engineering, and wireless security. Develop practical skills through hands-on exercises, real-world scenarios, and step-by-step tutorials to simulate both offensive and defensive hacking techniques. Understand the legal and ethical implications of hacking, and learn how to conduct penetration testing and vulnerability assessments in an ethical and responsible manner. Authored by Kris Hermans, a highly respected cybersecurity expert, "Black and White Hat Hacking" combines extensive practical experience with a passion for educating others. Kris's expertise shines through as they guide readers through the intricacies of ethical hacking, empowering them to defend against cyber threats effectively. Whether you're an aspiring cybersecurity professional, an IT enthusiast, or an ethical hacker looking to expand your skill set, "Black and White Hat Hacking" is your essential resource. Business owners, IT managers, and professionals responsible for safeguarding digital assets will also find valuable insights within these pages. Master the art of ethical hacking. Order your copy of "Black and White Hat Hacking" today and equip yourself with the knowledge and tools to strengthen cybersecurity defences.

Mastering AI ethics

Mastering AI ethics
Author: Cybellium Ltd
Publisher: Cybellium Ltd
Total Pages: 149
Release: 2023-09-05
Genre: Computers
ISBN:
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In an era shaped by the rapid evolution of artificial intelligence, grappling with the ethical dimensions of AI technologies has become an imperative. "Mastering AI Ethics" is a groundbreaking guide that delves deep into the complexities of AI ethics, equipping readers with the insights required to navigate the ethical challenges posed by AI innovations. About the Book: In this thought-provoking book, readers are invited to explore the intricate web of ethical considerations surrounding AI development, deployment, and societal impact. With real-world examples, case studies, and actionable frameworks, "Mastering AI Ethics" empowers readers to make informed decisions and contribute to a future where AI serves the greater good. Key Features: Foundations of Ethical AI: The book lays a strong foundation by demystifying the core concepts that underpin AI ethics. Readers will develop a clear understanding of how ethical considerations intersect with AI technologies and why these intersections are crucial. Tackling Complex Ethical Dilemmas: Through a series of real-world scenarios, readers will grapple with intricate ethical dilemmas presented by AI. The book guides readers in analyzing and evaluating these scenarios, enabling them to cultivate the critical thinking skills needed to confront ethical challenges head-on. Frameworks for Ethical Decision-Making: "Mastering AI Ethics" introduces readers to practical frameworks and models designed to facilitate ethical decision-making in AI contexts. These frameworks empower readers to weigh conflicting interests, anticipate potential harms, and arrive at ethically sound solutions. Promoting Transparency and Accountability: The book delves into the concepts of transparency and accountability in AI development and deployment. Readers will discover how to foster transparency, hold AI systems accountable, and ensure responsible use of AI technologies. Societal Implications of AI: By examining broader societal implications, the book explores how AI influences areas such as privacy, bias, fairness, and social justice. Readers will gain insights into how AI technologies can amplify existing inequalities and how to design AI systems that mitigate these effects. Collaborative Ethical Practices: "Mastering AI Ethics" underscores the significance of collaborative efforts in shaping AI ethics. Readers will learn how interdisciplinary collaboration involving ethicists, technologists, policymakers, and stakeholders can drive more ethical AI development and deployment. Exploring Future Ethical Challenges: As AI continues to evolve, so do its ethical considerations. The book provides a forward-looking perspective on emerging trends in AI ethics, from the ethical implications of AI in healthcare to the challenges posed by autonomous systems and AI-driven decision-making. Who Should Read This Book: "Mastering AI Ethics" is an indispensable resource for AI practitioners, data scientists, ethicists, policymakers, and anyone concerned with the ethical implications of AI technologies. Whether you're an AI researcher aiming to integrate ethics into your work, a business leader exploring responsible AI implementation, or a curious citizen intrigued by AI's impact on society, this book equips you with the tools to engage in meaningful discussions and drive ethical change in the AI landscape.

Hacker Mindset: Psychological Tactics and Strategies for Mastering Social Engineering

Hacker Mindset: Psychological Tactics and Strategies for Mastering Social Engineering
Author: Josh Luberisse
Publisher: Fortis Novum Mundum
Total Pages: 140
Release:
Genre: Business & Economics
ISBN:
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"Hacker Mindset: Psychological Tactics and Strategies for Mastering Social Engineering" is an authoritative and comprehensive guide that delves deep into the psychology of cyber attackers and equips cybersecurity professionals with the knowledge and tools to defend against social engineering attacks. This essential resource offers a unique blend of psychological insights and practical cybersecurity strategies, making it an invaluable asset for red teamers, ethical hackers, and security professionals seeking to enhance their skills and protect critical systems and assets. With a focus on understanding the hacker mindset, this book provides a thorough exploration of the techniques and methodologies used by social engineers to exploit human vulnerabilities. Gain a deep understanding of the psychological principles behind social engineering, including authority, scarcity, social proof, reciprocity, consistency, and emotional manipulation. Learn how attackers leverage these principles to deceive and manipulate their targets. Discover the latest tools and techniques for conducting advanced reconnaissance, vulnerability scanning, and exploitation, covering essential frameworks and software, such as Metasploit, Cobalt Strike, and OSINT tools like Maltego and Shodan. Explore the unique social engineering threats faced by various sectors, including healthcare, finance, government, and military, and learn how to implement targeted defenses and countermeasures to mitigate these risks effectively. Understand how AI, machine learning, and other advanced technologies are transforming the field of cybersecurity and how to integrate these technologies into your defensive strategies to enhance threat detection, analysis, and response. Discover the importance of realistic training scenarios and continuous education in preparing cybersecurity professionals for real-world threats. Learn how to design and conduct effective red team/blue team exercises and capture-the-flag competitions. Navigate the complex legal and ethical landscape of offensive cybersecurity operations with guidance on adhering to international laws, military ethics, and best practices to ensure your actions are justified, lawful, and morally sound. Benefit from detailed case studies and real-world examples that illustrate the practical application of social engineering tactics and defensive strategies, providing valuable lessons and highlighting best practices for safeguarding against cyber threats. "Hacker Mindset: Psychological Tactics and Strategies for Mastering Social Engineering" is designed to not only enhance your technical skills but also to foster a deeper understanding of the human element in cybersecurity. Whether you are a seasoned cybersecurity professional or new to the field, this book provides the essential knowledge and strategies needed to effectively defend against the growing threat of social engineering attacks. Equip yourself with the insights and tools necessary to stay one step ahead of cyber adversaries and protect your organization's critical assets.

Learn Ethical Hacking from Scratch

Learn Ethical Hacking from Scratch
Author: Zaid Sabih
Publisher: Packt Publishing Ltd
Total Pages: 549
Release: 2018-07-31
Genre: Computers
ISBN: 1788624785
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Learn how to hack systems like black hat hackers and secure them like security experts Key Features Understand how computer systems work and their vulnerabilities Exploit weaknesses and hack into machines to test their security Learn how to secure systems from hackers Book Description This book starts with the basics of ethical hacking, how to practice hacking safely and legally, and how to install and interact with Kali Linux and the Linux terminal. You will explore network hacking, where you will see how to test the security of wired and wireless networks. You’ll also learn how to crack the password for any Wi-Fi network (whether it uses WEP, WPA, or WPA2) and spy on the connected devices. Moving on, you will discover how to gain access to remote computer systems using client-side and server-side attacks. You will also get the hang of post-exploitation techniques, including remotely controlling and interacting with the systems that you compromised. Towards the end of the book, you will be able to pick up web application hacking techniques. You'll see how to discover, exploit, and prevent a number of website vulnerabilities, such as XSS and SQL injections. The attacks covered are practical techniques that work against real systems and are purely for educational purposes. At the end of each section, you will learn how to detect, prevent, and secure systems from these attacks. What you will learn Understand ethical hacking and the different fields and types of hackers Set up a penetration testing lab to practice safe and legal hacking Explore Linux basics, commands, and how to interact with the terminal Access password-protected networks and spy on connected clients Use server and client-side attacks to hack and control remote computers Control a hacked system remotely and use it to hack other systems Discover, exploit, and prevent a number of web application vulnerabilities such as XSS and SQL injections Who this book is for Learning Ethical Hacking from Scratch is for anyone interested in learning how to hack and test the security of systems like professional hackers and security experts.

Mastering AI

Mastering AI
Author: Jeremy Kahn
Publisher: Simon and Schuster
Total Pages: 336
Release: 2024-07-09
Genre: Business & Economics
ISBN: 1668053322
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A Fortune magazine journalist draws on his expertise and extensive contacts among the companies and scientists at the forefront of artificial intelligence to offer dramatic predictions of AI’s impact over the next decade, from reshaping our economy and the way we work, learn, and create to unknitting our social fabric, jeopardizing our democracy, and fundamentally altering the way we think. Within the next five years, Jeremy Kahn predicts, AI will disrupt almost every industry and enterprise, with vastly increased efficiency and productivity. It will restructure the workforce, making AI copilots a must for every knowledge worker. It will revamp education, meaning children around the world can have personal, portable tutors. It will revolutionize health care, making individualized, targeted pharmaceuticals more affordable. It will compel us to reimagine how we make art, compose music, and write and publish books. The potential of generative AI to extend our skills, talents, and creativity as humans is undeniably exciting and promising. But while this new technology has a bright future, it also casts a dark and fearful shadow. AI will provoke pervasive, disruptive, potentially devastating knock-on effects. Leveraging his unrivaled access to the leaders, scientists, futurists, and others who are making AI a reality, Kahn will argue that if not carefully designed and vigilantly regulated AI will deepen income inequality, depressing wages while imposing winner-take-all markets across much of the economy. AI risks undermining democracy, as truth is overtaken by misinformation, racial bias, and harmful stereotypes. Continuing a process begun by the internet, AI will rewire our brains, likely inhibiting our ability to think critically, to remember, and even to get along with one another—unless we all take decisive action to prevent this from happening. Much as Michael Lewis’s classic The New New Thing offered a prescient, insightful, and eminently readable account of life inside the dot-com bubble, Mastering AI delivers much-needed guidance for anyone eager to understand the AI boom—and what comes next.

Bayesian Methods for Hackers

Bayesian Methods for Hackers
Author: Cameron Davidson-Pilon
Publisher: Addison-Wesley Professional
Total Pages: 551
Release: 2015-09-30
Genre: Computers
ISBN: 0133902927
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Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.