Large Language Models In Cybersecurity PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Large Language Models In Cybersecurity PDF full book. Access full book title Large Language Models In Cybersecurity.
| Author | : Andrei Kucharavy |
| Publisher | : Springer Nature |
| Total Pages | : 249 |
| Release | : 2024 |
| Genre | : Computer security |
| ISBN | : 3031548272 |
Download Large Language Models in Cybersecurity Book in PDF, ePub and Kindle
This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful large language models (LLMs) and how they can be mitigated. It attempts to outrun the malicious attackers by anticipating what they could do. It also alerts LLM developers to understand their work's risks for cybersecurity and provides them with tools to mitigate those risks. The book starts in Part I with a general introduction to LLMs and their main application areas. Part II collects a description of the most salient threats LLMs represent in cybersecurity, be they as tools for cybercriminals or as novel attack surfaces if integrated into existing software. Part III focuses on attempting to forecast the exposure and the development of technologies and science underpinning LLMs, as well as macro levers available to regulators to further cybersecurity in the age of LLMs. Eventually, in Part IV, mitigation techniques that should allowsafe and secure development and deployment of LLMs are presented. The book concludes with two final chapters in Part V, one speculating what a secure design and integration of LLMs from first principles would look like and the other presenting a summary of the duality of LLMs in cyber-security. This book represents the second in a series published by the Technology Monitoring (TM) team of the Cyber-Defence Campus. The first book entitled "Trends in Data Protection and Encryption Technologies" appeared in 2023. This book series provides technology and trend anticipation for government, industry, and academic decision-makers as well as technical experts.
| Author | : Andrei Kucharavy |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2024-08-26 |
| Genre | : Computers |
| ISBN | : 9783031548260 |
Download Large Language Models in Cybersecurity Book in PDF, ePub and Kindle
This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful large language models (LLMs) and how they can be mitigated. It attempts to outrun the malicious attackers by anticipating what they could do. It also alerts LLM developers to understand their work's risks for cybersecurity and provides them with tools to mitigate those risks. The book starts in Part I with a general introduction to LLMs and their main application areas. Part II collects a description of the most salient threats LLMs represent in cybersecurity, be they as tools for cybercriminals or as novel attack surfaces if integrated into existing software. Part III focuses on attempting to forecast the exposure and the development of technologies and science underpinning LLMs, as well as macro levers available to regulators to further cybersecurity in the age of LLMs. Eventually, in Part IV, mitigation techniques that should allow safe and secure development and deployment of LLMs are presented. The book concludes with two final chapters in Part V, one speculating what a secure design and integration of LLMs from first principles would look like and the other presenting a summary of the duality of LLMs in cyber-security. This book represents the second in a series published by the Technology Monitoring (TM) team of the Cyber-Defence Campus. The first book entitled "Trends in Data Protection and Encryption Technologies" appeared in 2023. This book series provides technology and trend anticipation for government, industry, and academic decision-makers as well as technical experts.
| Author | : National Academies of Sciences, Engineering, and Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 99 |
| Release | : 2020-01-27 |
| Genre | : Computers |
| ISBN | : 0309494508 |
Download Implications of Artificial Intelligence for Cybersecurity Book in PDF, ePub and Kindle
In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop.
| Author | : Omar, Marwan |
| Publisher | : IGI Global |
| Total Pages | : 287 |
| Release | : 2024-07-17 |
| Genre | : Computers |
| ISBN | : |
Download Redefining Security With Cyber AI Book in PDF, ePub and Kindle
In the rapidly evolving digital landscape, the importance of cybersecurity has never been more critical. With the increasing sophistication of cyber threats, traditional security measures often fall short in providing adequate protection. Cyber artificial intelligence (AI) offers advanced capabilities to detect, prevent, and respond to attacks in real time. As cyber threats continue to grow in complexity and frequency, the integration of AI into cybersecurity frameworks is not just advantageous but essential for maintaining robust and resilient defenses. Redefining Security With Cyber AI delves into the profound transformation of security paradigms brought about by the advent of AI. This book explores the intricate dance between the ever-expanding frontiers of digital technology and the AI-driven mechanisms that aim to safeguard them. Covering topics such as artificial neural networks, intrusion detection, and large language models, this book is an excellent resource for cybersecurity professionals, AI and machine learning researchers, IT executives and managers, policy makers and regulators, postgraduate students and educators, academicians, and more.
| Author | : Mark Stamp |
| Publisher | : Springer Nature |
| Total Pages | : 388 |
| Release | : 2022-07-15 |
| Genre | : Computers |
| ISBN | : 3030970876 |
Download Artificial Intelligence for Cybersecurity Book in PDF, ePub and Kindle
This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity. This book also provides insight into the difficult "how" and "why" questions that arise in AI within the security domain. For example, this book includes chapters covering "explainable AI", "adversarial learning", "resilient AI", and a wide variety of related topics. It’s not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.
| Author | : Iqbal H. Sarker |
| Publisher | : Springer Nature |
| Total Pages | : 207 |
| Release | : |
| Genre | : |
| ISBN | : 3031544978 |
Download AI-Driven Cybersecurity andThreat Intelligence Book in PDF, ePub and Kindle
| Author | : Xiaofeng Chen |
| Publisher | : Springer Nature |
| Total Pages | : 168 |
| Release | : 2021-07-02 |
| Genre | : Computers |
| ISBN | : 9813367261 |
Download Cyber Security Meets Machine Learning Book in PDF, ePub and Kindle
Machine learning boosts the capabilities of security solutions in the modern cyber environment. However, there are also security concerns associated with machine learning models and approaches: the vulnerability of machine learning models to adversarial attacks is a fatal flaw in the artificial intelligence technologies, and the privacy of the data used in the training and testing periods is also causing increasing concern among users. This book reviews the latest research in the area, including effective applications of machine learning methods in cybersecurity solutions and the urgent security risks related to the machine learning models. The book is divided into three parts: Cyber Security Based on Machine Learning; Security in Machine Learning Methods and Systems; and Security and Privacy in Outsourced Machine Learning. Addressing hot topics in cybersecurity and written by leading researchers in the field, the book features self-contained chapters to allow readers to select topics that are relevant to their needs. It is a valuable resource for all those interested in cybersecurity and robust machine learning, including graduate students and academic and industrial researchers, wanting to gain insights into cutting-edge research topics, as well as related tools and inspiring innovations.
| Author | : Maria Antonieta Flores |
| Publisher | : XML Press |
| Total Pages | : 188 |
| Release | : 2018-07-13 |
| Genre | : Business & Economics |
| ISBN | : 1492065226 |
Download The Language of Cybersecurity Book in PDF, ePub and Kindle
The Language of Cybersecurity defines 52 terms that every business professional should know about cybersecurity, even professionals who are not specialists. Anyone who uses any kind of computing device needs to understand the importance of cybersecurity, and every business professional also needs to be able to speak intelligently with cybersecurity professionals. The Language of Cybersecurity introduces the world of cybersecurity through the terminology that defines the field. Each of the 52 main terms contains a definition, a statement of why the term is important, and an essay that explains why a business professional should know about the term. Each term was authored by an expert practitioner in that area. The Language of Cybersecurity looks at vulnerabilities, exploits, defenses, planning, and compliance. In addition there is a glossary that defines more than 80 additional. For those who want to dig deeper, there are more than 150 references for further exploration. Expertly compiled and edited by Tonie Flores, this book is a useful reference for cybersecurity experts, managers, students, and anyone who uses a computer, tablet, smart phone, or other computing device.
| Author | : Soma Halder |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 306 |
| Release | : 2018-12-31 |
| Genre | : Computers |
| ISBN | : 178899096X |
Download Hands-On Machine Learning for Cybersecurity Book in PDF, ePub and Kindle
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 | : Prithviraj Dasgupta |
| Publisher | : Springer Nature |
| Total Pages | : 229 |
| Release | : 2021-01-22 |
| Genre | : Computers |
| ISBN | : 3030556921 |
Download Adversary-Aware Learning Techniques and Trends in Cybersecurity Book in PDF, ePub and Kindle
This book is intended to give researchers and practitioners in the cross-cutting fields of artificial intelligence, machine learning (AI/ML) and cyber security up-to-date and in-depth knowledge of recent techniques for improving the vulnerabilities of AI/ML systems against attacks from malicious adversaries. The ten chapters in this book, written by eminent researchers in AI/ML and cyber-security, span diverse, yet inter-related topics including game playing AI and game theory as defenses against attacks on AI/ML systems, methods for effectively addressing vulnerabilities of AI/ML operating in large, distributed environments like Internet of Things (IoT) with diverse data modalities, and, techniques to enable AI/ML systems to intelligently interact with humans that could be malicious adversaries and/or benign teammates. Readers of this book will be equipped with definitive information on recent developments suitable for countering adversarial threats in AI/ML systems towards making them operate in a safe, reliable and seamless manner.
