Large Language Models In Cybersecurity
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Large Language Models In Cybersecurity
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Author : Andrei Kucharavy
language : en
Publisher: Springer Nature
Release Date : 2024-05-31
Large Language Models In Cybersecurity written by Andrei Kucharavy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-31 with Computers categories.
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.
Revolutionizing Cybersecurity With Deep Learning And Large Language Models
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Author : Zangana, Hewa Majeed
language : en
Publisher: IGI Global
Release Date : 2025-04-08
Revolutionizing Cybersecurity With Deep Learning And Large Language Models written by Zangana, Hewa Majeed and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-08 with Computers categories.
As cyber threats grow, national security measures struggle to keep pace with sophisticated attacks. Deep learning and large language models (LLMs) revolutionize cybersecurity by enabling advanced threat detection automated response mechanisms and analytics. AI technologies can analyze vast amounts of data, recognize patterns, and identify threats to security systems. Using deep learning and LLMs to transform cybersecurity is essential for addressing both their potential and the challenges that come with their adoption. Revolutionizing Cybersecurity With Deep Learning and Large Language Models explores the intersection of AI, cybersecurity, deep learning, and LLMs, and the potential of these technologies in safeguarding the digital world. It examines real-world applications, ethical challenges, and new technological advancements. This book covers topics such as artificial intelligence, cybersecurity, and threat detection, and is a useful resource for academicians, researchers, security professionals, computer engineers, and data scientists.
Application Of Large Language Models Llms For Software Vulnerability Detection
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Author : Omar, Marwan
language : en
Publisher: IGI Global
Release Date : 2024-11-01
Application Of Large Language Models Llms For Software Vulnerability Detection written by Omar, Marwan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-01 with Computers categories.
Large Language Models (LLMs) are redefining the landscape of cybersecurity, offering innovative methods for detecting software vulnerabilities. By applying advanced AI techniques to identify and predict weaknesses in software code, including zero-day exploits and complex malware, LLMs provide a proactive approach to securing digital environments. This integration of AI and cybersecurity presents new possibilities for enhancing software security measures. Application of Large Language Models (LLMs) for Software Vulnerability Detection offers a comprehensive exploration of this groundbreaking field. These chapters are designed to bridge the gap between AI research and practical application in cybersecurity, in order to provide valuable insights for researchers, AI specialists, software developers, and industry professionals. Through real-world examples and actionable strategies, the publication will drive innovation in vulnerability detection and set new standards for leveraging AI in cybersecurity.
Leveraging Large Language Models For Quantum Aware Cybersecurity
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Author : Zangana, Hewa Majeed
language : en
Publisher: IGI Global
Release Date : 2024-12-26
Leveraging Large Language Models For Quantum Aware Cybersecurity written by Zangana, Hewa Majeed and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-26 with Computers categories.
As the digital landscape evolves, the growing threat of cyberattacks has prompted the need for more advanced security measures. One of the most promising developments in cybersecurity is the integration of large language models (LLMs) with quantum-aware systems. These AI-powered models, capable of processing data and recognizing complex patterns, play a pivotal role in identifying vulnerabilities, predicting threats, and enhancing the resilience of security infrastructures. In quantum computing, LLMs offer new opportunities to stay ahead of cyber threats by simulating attack strategies and developing adaptive defense mechanisms. By harnessing the power of these tools, cybersecurity professionals can address current challenges while preparing for an era of quantum-enabled cyber threats. Leveraging Large Language Models for Quantum-Aware Cybersecurity explores the convergence of LLMs, cybersecurity, and quantum computing, providing an in-depth analysis of how these fields are being integrated to tackle emerging challenges in the digital security landscape. It covers foundational concepts, cutting-edge research, and practical applications, demonstrating how LLMs can be leveraged alongside quantum technologies to enhance threat detection, automate incident response, and build quantum-resilient security frameworks. This book covers topics such as artificial intelligence, computer engineering, natural language processing, and is a useful resource for computer engineers, security professionals, scientists, academicians, and researchers.
Artificial Intelligence For Blockchain And Cybersecurity Powered Iot Applications
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Author : Mariya Ouaissa
language : en
Publisher: CRC Press
Release Date : 2025-01-16
Artificial Intelligence For Blockchain And Cybersecurity Powered Iot Applications written by Mariya Ouaissa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-16 with Computers categories.
The objective of this book is to showcase recent solutions and discuss the opportunities that AI, blockchain, and even their combinations can present to solve the issue of Internet of Things (IoT) security. It delves into cuttingedge technologies and methodologies, illustrating how these innovations can fortify IoT ecosystems against security threats. The discussion includes a comprehensive analysis of AI techniques such as machine learning and deep learning, which can detect and respond to security breaches in real time. The role of blockchain in ensuring data integrity, transparency, and tamper- proof transactions is also thoroughly examined. Furthermore, this book will present solutions that will help analyze complex patterns in user data and ultimately improve productivity.
Machine Learning For Cybersecurity Cookbook
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Author : Emmanuel Tsukerman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-11-25
Machine Learning For Cybersecurity Cookbook written by Emmanuel Tsukerman 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 2019-11-25 with Computers categories.
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.
Foundations And Practice Of Security
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Author : Kamel Adi
language : en
Publisher: Springer Nature
Release Date : 2025-04-30
Foundations And Practice Of Security written by Kamel Adi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-30 with Computers categories.
This two-volume set constitutes the refereed proceedings of the 17th International Symposium on Foundations and Practice of Security, FPS 2024, held in Montréal, QC, Canada, during December 09–11, 2024. The 28 full and 11 short papers presented in this book were carefully reviewed and selected from 75 submissions. The papers were organized in the following topical sections: Part I: Critical issues of protecting systems against digital threats,considering financial, technological, and operational implications; Automating and enhancing security mechanisms in software systems and data management; Cybersecurity and AI when applied to emerging technologies; Cybersecurity and Ethics; Cybersecurity and privacy in connected and autonomous systems for IoT, smart environments, and critical infrastructure; New trends in advanced cryptographic protocols. Part II: Preserving privacy and maintaining trust for end users in a complex and numeric cyberspace; Intersecting security, privacy, and machine learning techniques to detect, mitigate, and prevent threats; New trends of machine leaning and AI applied to cybersecurity.
Secure It Systems
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Author : Leonardo Horn Iwaya
language : en
Publisher: Springer Nature
Release Date : 2025-01-28
Secure It Systems written by Leonardo Horn Iwaya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-28 with Computers categories.
This book constitutes the refereed proceedings of the 29th International Conference on Secure IT Systems, NordSec 2024, held in Karlstad, Sweden, during November 6–7, 2024. The 25 full papers presented in this book were carefully reviewed and selected from 59 submissions. They focus on topics such as: Authentication; Cryptography; Cyber-Physical Systems; Cybersecurity and Policy; LLMs for Security; Formal Verification; Mobile and IoT; Network Security; and Privacy.
Computer Security Esorics 2024 International Workshops
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Author : Joaquin Garcia-Alfaro
language : en
Publisher: Springer Nature
Release Date : 2025-03-31
Computer Security Esorics 2024 International Workshops written by Joaquin Garcia-Alfaro and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Computers categories.
This two-volume set LNCS 15263 and LNCS 15264 constitutes the refereed proceedings of eleven International Workshops which were held in conjunction with the 29th European Symposium on Research in Computer Security, ESORICS 2024, held in Bydgoszcz, Poland, during September 16–20, 2024. The papers included in these proceedings stem from the following workshops: 19th International Workshop on Data Privacy Management, DPM 2024, which accepted 7 full papers and 6 short papers out of 24 submissions; 8th International Workshop on Cryptocurrencies and Blockchain Technology, CBT 2024, which accepted 9 full papers out of 17 submissions; 10th Workshop on the Security of Industrial Control Systems and of Cyber-Physical Systems, CyberICPS 2024, which accepted 9 full papers out of 17 submissions; International Workshop on Security and Artificial Intelligence, SECAI 2024, which accepted 10 full papers and 5 short papers out of 42 submissions; Workshop on Computational Methods for Emerging Problems in Disinformation Analysis, DisA 2024, which accepted 4 full papers out of 8 submissions; 5th International Workshop on Cyber-Physical Security for Critical Infrastructures Protection, CPS4CIP 2024, which accepted 4 full papers out of 9 submissions; 3rd International Workshop on System Security Assurance, SecAssure 2024, which accepted 8 full papers out of 14 submissions.
Ai Driven Cybersecurity And Threat Intelligence
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Author : Iqbal H. Sarker
language : en
Publisher: Springer Nature
Release Date : 2024-04-28
Ai Driven Cybersecurity And Threat Intelligence written by Iqbal H. Sarker and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-28 with Computers categories.
This book explores the dynamics of how AI (Artificial Intelligence) technology intersects with cybersecurity challenges and threat intelligence as they evolve. Integrating AI into cybersecurity not only offers enhanced defense mechanisms, but this book introduces a paradigm shift illustrating how one conceptualize, detect and mitigate cyber threats. An in-depth exploration of AI-driven solutions is presented, including machine learning algorithms, data science modeling, generative AI modeling, threat intelligence frameworks and Explainable AI (XAI) models. As a roadmap or comprehensive guide to leveraging AI/XAI to defend digital ecosystems against evolving cyber threats, this book provides insights, modeling, real-world applications and research issues. Throughout this journey, the authors discover innovation, challenges, and opportunities. It provides a holistic perspective on the transformative role of AI in securing the digital world. Overall, the useof AI can transform the way one detects, responds and defends against threats, by enabling proactive threat detection, rapid response and adaptive defense mechanisms. AI-driven cybersecurity systems excel at analyzing vast datasets rapidly, identifying patterns that indicate malicious activities, detecting threats in real time as well as conducting predictive analytics for proactive solution. Moreover, AI enhances the ability to detect anomalies, predict potential threats, and respond swiftly, preventing risks from escalated. As cyber threats become increasingly diverse and relentless, incorporating AI/XAI into cybersecurity is not just a choice, but a necessity for improving resilience and staying ahead of ever-changing threats. This book targets advanced-level students in computer science as a secondary textbook. Researchers and industry professionals working in various areas, such as Cyber AI, Explainable and Responsible AI, Human-AI Collaboration, Automation and Intelligent Systems, Adaptive and Robust Security Systems, Cybersecurity Data Science and Data-Driven Decision Making will also find this book useful as reference book.