Large Language Models in Cybersecurity

Large Language Models in Cybersecurity
Author :
Publisher : Springer Nature
Total Pages : 249
Release :
ISBN-10 : 9783031548277
ISBN-13 : 3031548272
Rating : 4/5 (77 Downloads)

Book Synopsis Large Language Models in Cybersecurity by : Andrei Kucharavy

Download or read book Large Language Models in Cybersecurity written by Andrei Kucharavy and published by Springer Nature. This book was released on 2024 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Large Language Models in Cybersecurity Related Books

Large Language Models in Cybersecurity
Language: en
Pages: 249
Authors: Andrei Kucharavy
Categories: Computer security
Type: BOOK - Published: 2024 - Publisher: Springer Nature

DOWNLOAD EBOOK

This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful large lan
Implications of Artificial Intelligence for Cybersecurity
Language: en
Pages: 99
Authors: National Academies of Sciences, Engineering, and Medicine
Categories: Computers
Type: BOOK - Published: 2020-01-27 - Publisher: National Academies Press

DOWNLOAD EBOOK

In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursu
Application of Large Language Models (LLMs) for Software Vulnerability Detection
Language: en
Pages: 534
Authors: Omar, Marwan
Categories: Computers
Type: BOOK - Published: 2024-11-01 - Publisher: IGI Global

DOWNLOAD EBOOK

Large Language Models (LLMs) are redefining the landscape of cybersecurity, offering innovative methods for detecting software vulnerabilities. By applying adva
Hands-On Machine Learning for Cybersecurity
Language: en
Pages: 306
Authors: Soma Halder
Categories: Computers
Type: BOOK - Published: 2018-12-31 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Get into the world of smart data security using machine learning algorithms and Python libraries Key FeaturesLearn machine learning algorithms and cybersecurity
Machine Learning and Cognitive Science Applications in Cyber Security
Language: en
Pages: 338
Authors: Khan, Muhammad Salman
Categories: Computers
Type: BOOK - Published: 2019-05-15 - Publisher: IGI Global

DOWNLOAD EBOOK

In the past few years, with the evolution of advanced persistent threats and mutation techniques, sensitive and damaging information from a variety of sources h