Author: Mauro BarniPublisher:
ISBN: 9781680837643
Category : Technology & Engineering
Languages : en
Pages : 190
Book Description
Theoretical Foundations of Adversarial Binary Detection
Author: Mauro Barni (Ph. D.)Publisher:
ISBN: 9781680837650
Category : Electronic books
Languages : en
Pages : 172
Book Description
This monograph, aimed at students, researchers and practitioners working in the application areas who want an accessible introduction to the theory behind Adversarial Binary Detection and the possible solutions to their particular problem.
Theoretical Foundations of Adversarial Binary Detection
Author: Mauro BarniPublisher:
ISBN: 9781680837643
Category : Technology & Engineering
Languages : en
Pages : 190
Book Description
Generative Adversarial Networks and Deep Learning
Author: Roshani RautPublisher: CRC Press
ISBN: 1000840565
Category : Computers
Languages : en
Pages : 286
Book Description
This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features: Presents a comprehensive guide on how to use GAN for images and videos. Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GAN Highlights the inclusion of gaming effects using deep learning methods Examines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutions The book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum
Game Theory and Machine Learning for Cyber Security
Author: Charles A. KamhouaPublisher: John Wiley & Sons
ISBN: 1119723949
Category : Technology & Engineering
Languages : en
Pages : 546
Book Description
GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.
Information Theory, Mathematical Optimization, and Their Crossroads in 6G System Design
Author: Shih-Chun LinPublisher: Springer Nature
ISBN: 9811920168
Category : Technology & Engineering
Languages : en
Pages : 403
Book Description
This book provides a broad understanding of the fundamental tools and methods from information theory and mathematical programming, as well as specific applications in 6G and beyond system designs. The contents focus on not only both theories but also their intersection in 6G. Motivations are from the multitude of new developments which will arise once 6G systems integrate new communication networks with AIoT (Artificial Intelligence plus Internet of Things). Design issues such as the intermittent connectivity, low latency, federated learning, IoT security, etc., are covered. This monograph provides a thorough picture of new results from information and optimization theories, as well as how their dialogues work to solve aforementioned 6G design issues.
Fundamentals of Computation Theory
Author: Maciej LiskiewiczPublisher: Springer
ISBN: 3540318739
Category : Computers
Languages : en
Pages : 580
Book Description
This volume is dedicated to the 15th Symposium on Fundamentals of Computation Theory FCT 2005, held in Lubeck, Germany, on August 17–20, 2005.
Adversarial Machine Learning
Author: Aneesh Sreevallabh ChivukulaPublisher: Springer Nature
ISBN: 3030997723
Category : Computers
Languages : en
Pages : 316
Book Description
A critical challenge in deep learning is the vulnerability of deep learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in unintended ways. In this book, we review the latest developments in adversarial attack technologies in computer vision; natural language processing; and cybersecurity with regard to multidimensional, textual and image data, sequence data, and temporal data. In turn, we assess the robustness properties of deep learning networks to produce a taxonomy of adversarial examples that characterises the security of learning systems using game theoretical adversarial deep learning algorithms. The state-of-the-art in adversarial perturbation-based privacy protection mechanisms is also reviewed. We propose new adversary types for game theoretical objectives in non-stationary computational learning environments. Proper quantification of the hypothesis set in the decision problems of our research leads to various functional problems, oracular problems, sampling tasks, and optimization problems. We also address the defence mechanisms currently available for deep learning models deployed in real-world environments. The learning theories used in these defence mechanisms concern data representations, feature manipulations, misclassifications costs, sensitivity landscapes, distributional robustness, and complexity classes of the adversarial deep learning algorithms and their applications. In closing, we propose future research directions in adversarial deep learning applications for resilient learning system design and review formalized learning assumptions concerning the attack surfaces and robustness characteristics of artificial intelligence applications so as to deconstruct the contemporary adversarial deep learning designs. Given its scope, the book will be of interest to Adversarial Machine Learning practitioners and Adversarial Artificial Intelligence researchers whose work involves the design and application of Adversarial Deep Learning.
Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies
Author: National Academies of Sciences, Engineering, and MedicinePublisher: National Academies Press
ISBN: 0309496128
Category : Computers
Languages : en
Pages : 83
Book Description
The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11â€"12, 2018, in Berkeley, California, to discuss robust machine learning algorithms and systems for the detection and mitigation of adversarial attacks and anomalies. This publication summarizes the presentations and discussions from the workshop.
Deep Learning Theory and Applications
Author: Donatello ContePublisher: Springer Nature
ISBN: 3031390598
Category : Computers
Languages : en
Pages : 496
Book Description
This book consitiutes the refereed proceedings of the 4th International Conference on Deep Learning Theory and Applications, DeLTA 2023, held in Rome, Italy from 13 to 14 July 2023. The 9 full papers and 22 short papers presented were thoroughly reviewed and selected from the 42 qualified submissions. The scope of the conference includes such topics as models and algorithms; machine learning; big data analytics; computer vision applications; and natural language understanding.
Decision and Game Theory for Security
Author: Jens GrossklagsPublisher: Springer
ISBN: 3642342663
Category : Computers
Languages : en
Pages : 309
Book Description
This book constitutes the refereed proceedings of the Third International Conference on Decision and Game Theory for Security, GameSec 2012, held in Budapest, Hungary, in November 2012. The 18 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on secret communications, identification of attackers, multi-step attacks, network security, system defense, and applications security.