Large Language Models In Cyberattacks Pdf
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Combating Threats and Attacks Targeting The AI Ecosystem
Author: Aditya Sood
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2024-12-04
This book explores in detail the AI-driven cyber threat landscape, including inherent AI threats and risks that exist in Large Language Models (LLMs), Generative AI applications, and the AI infrastructure. The book highlights hands-on technical approaches to detect security flaws in AI systems and applications utilizing the intelligence gathered from real-world case studies. Lastly, the book presents a very detailed discussion of the defense mechanisms and practical solutions to secure LLMs, GenAI applications, and the AI infrastructure. The chapters are structured with a granular framework, starting with AI concepts, followed by practical assessment techniques based on real-world intelligence, and concluding with required security defenses. Artificial Intelligence (AI) and cybersecurity are deeply intertwined and increasingly essential to modern digital defense strategies. The book is a comprehensive resource for IT professionals, business leaders, and cybersecurity experts for understanding and defending against AI-driven cyberattacks.
Regulatory Challenges of AI Governance in the Era of ChatGPT
Author: Toriqul Islam
language: en
Publisher: Kluwer Law International B.V.
Release Date: 2024-12-06
The increasing integration of artificial intelligence (AI), and particularly of large language models (LLMs) like ChatGPT, into human interactions raises significant ethical and social concerns across a broad spectrum of human activity. Therefore, it is important to use AI responsibly and ethically and to be critical of the information it generates. This book – the first comprehensive work to provide a structured framework for AI governance – focuses specifically on the regulatory challenges of LLMs like ChatGPT. It presents an extensive framework for understanding AI regulation, addressing its societal and ethical impacts, and exploring potential policy directions. Through 11 meticulously researched chapters, the book examines AI’s historical development, industry applications, socio-ethical concerns, and legal challenges. Advocating for a human-centric, risk-based regulatory approach, emphasising transparency, public participation, and ongoing monitoring, the book covers such aspects of AI and its governance as the following: a comprehensive overview of the history and mechanics of AI; widespread public misconceptions surrounding ChatGPT; ethical considerations (e.g., misinformation, accountability, and transparency); societal implications (e.g., job displacement, critical thinking, and malicious use); privacy concerns; intellectual property challenges; healthcare application dilemmas; interplay between LLMs and finance, and cross-border regulatory challenges. Throughout, the author identifies significant gaps in existing legal frameworks and explores potential policy directions to bridge these gaps. The book offers invaluable insights and recommendations for policymakers, legal experts, academics, students, technologists, and anyone interested in AI governance. It underscores the need for a collaborative effort and meaningful dialogue among industry leaders, academia, and civil society worldwide to promote responsible and ethical development and use of AI for the benefit of humanity.
Leveraging Large Language Models for Quantum-Aware Cybersecurity
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.