Challenges And Solutions For Cybersecurity And Adversarial Machine Learning

DOWNLOAD

Download Challenges And Solutions For Cybersecurity And Adversarial Machine Learning PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Challenges And Solutions For Cybersecurity And Adversarial Machine Learning book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Challenges And Solutions For Cybersecurity And Adversarial Machine Learning

DOWNLOAD
Author : Ul Rehman, Shafiq
language : en
Publisher: IGI Global
Release Date : 2025-06-06

Challenges And Solutions For Cybersecurity And Adversarial Machine Learning written by Ul Rehman, Shafiq and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.

Adversarial machine learning poses a threat to cybersecurity by exploiting vulnerabilities in AI models through manipulated inputs. These attacks can cause systems in healthcare, finance, and autonomous vehicles to make dangerous or misleading decisions. A major challenge lies in detecting these small issues and defending learning models and organizational data without sacrificing performance. Ongoing research and cross-sector collaboration are essential to develop robust, ethical, and secure machine learning systems. Further research may reveal better solutions to converge cyber technology, security, and machine learning tools. Challenges and Solutions for Cybersecurity and Adversarial Machine Learning explores adversarial machine learning and deep learning within cybersecurity. It examines foundational knowledge, highlights vulnerabilities and threats, and proposes cutting-edge solutions to counteract adversarial attacks on AI systems. This book covers topics such as data privacy, federated learning, and threat detection, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and data scientists.

Machine Learning And Security

DOWNLOAD
Author : Clarence Chio
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-01-26

Machine Learning And Security written by Clarence Chio and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-26 with Computers categories.

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions

Adversarial Machine Learning

DOWNLOAD
Author : Aneesh Sreevallabh Chivukula
language : en
Publisher: Springer Nature
Release Date : 2023-03-06

Adversarial Machine Learning written by Aneesh Sreevallabh Chivukula and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-06 with Computers categories.

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.

Game Theory And Machine Learning For Cyber Security

DOWNLOAD
Author : Charles A. Kamhoua
language : en
Publisher: John Wiley & Sons
Release Date : 2021-09-15

Game Theory And Machine Learning For Cyber Security written by Charles A. Kamhoua and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-15 with Technology & Engineering categories.

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.

Ai Enhanced Cybersecurity For Industrial Automation

DOWNLOAD
Author : Pandey, Hari Mohan
language : en
Publisher: IGI Global
Release Date : 2025-05-09

Ai Enhanced Cybersecurity For Industrial Automation written by Pandey, Hari Mohan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-09 with Computers categories.

As industrial automation systems become reliant on digital technologies, they face growing threats from sophisticated cyberattacks. Traditional cybersecurity measures often struggle to keep up with the evolving threat landscape, leaving critical infrastructure vulnerable. AI-enhanced cybersecurity offers a promising solution by leveraging machine learning and intelligent algorithms to detect, respond to, and even predict cyber threats in real time. By integrating AI into industrial cybersecurity frameworks, organizations can strengthen their defenses, ensure operational continuity, and protect valuable assets from malicious threats. AI-Enhanced Cybersecurity for Industrial Automation explores the integration of AI and cybersecurity in industry 5.0, emphasizing sustainability, resilience, and ethical considerations. It examines how industry 5.0 extends beyond automation and efficiency by incorporating human-centric, sustainable, and intelligent technologies into industrial ecosystems. This book covers topics such as blockchain, industrial engineering, and machine learning, and is a useful resource for computer engineers, business owners, security professionals, academicians, researchers, and scientists.

Malware Detection

DOWNLOAD
Author : Mihai Christodorescu
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-03-06

Malware Detection written by Mihai Christodorescu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-06 with Computers categories.

This book captures the state of the art research in the area of malicious code detection, prevention and mitigation. It contains cutting-edge behavior-based techniques to analyze and detect obfuscated malware. The book analyzes current trends in malware activity online, including botnets and malicious code for profit, and it proposes effective models for detection and prevention of attacks using. Furthermore, the book introduces novel techniques for creating services that protect their own integrity and safety, plus the data they manage.

Machine Intelligence Applications In Cyber Risk Management

DOWNLOAD
Author : Almaiah, Mohammed Amin
language : en
Publisher: IGI Global
Release Date : 2024-11-29

Machine Intelligence Applications In Cyber Risk Management written by Almaiah, Mohammed Amin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-29 with Computers categories.

In an era where cyber threats are increasingly sophisticated and persistent, the intersection of machine intelligence and cyber-risk management represents a pivotal frontier in the defense against malicious actors. The rapid advancements of artificial intelligence (AI) and machine learning (ML) technologies offer unprecedented capabilities for identifying, analyzing, and mitigating cyber risks. These technologies not only improve the speed and accuracy of identifying potential threats but also enable proactive and adaptive security measures. Machine Intelligence Applications in Cyber-Risk Management explores the diverse applications of machine intelligence in cyber-risk management, providing a comprehensive overview of how AI and ML algorithms are utilized for automated incident response, threat intelligence gathering, and dynamic security postures. It addresses the pressing need for innovative solutions to combat cyber threats and offer insights into the future of cybersecurity, where machine intelligence plays a crucial role in creating resilient and adaptive defense mechanisms. Covering topics such as anomy detection algorithms, malware detection, and wireless sensor networks (WSNs), this book is an excellent resource for cybersecurity professionals, researchers, academicians, security analysts, threat intelligence experts, IT managers, and more.

Cyber Security And Digital Forensics

DOWNLOAD
Author : Mangesh M. Ghonge
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-12

Cyber Security And Digital Forensics written by Mangesh M. Ghonge and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-12 with Computers categories.

CYBER SECURITY AND DIGITAL FORENSICS Cyber security is an incredibly important issue that is constantly changing, with new methods, processes, and technologies coming online all the time. Books like this are invaluable to professionals working in this area, to stay abreast of all of these changes. Current cyber threats are getting more complicated and advanced with the rapid evolution of adversarial techniques. Networked computing and portable electronic devices have broadened the role of digital forensics beyond traditional investigations into computer crime. The overall increase in the use of computers as a way of storing and retrieving high-security information requires appropriate security measures to protect the entire computing and communication scenario worldwide. Further, with the introduction of the internet and its underlying technology, facets of information security are becoming a primary concern to protect networks and cyber infrastructures from various threats. This groundbreaking new volume, written and edited by a wide range of professionals in this area, covers broad technical and socio-economic perspectives for the utilization of information and communication technologies and the development of practical solutions in cyber security and digital forensics. Not just for the professional working in the field, but also for the student or academic on the university level, this is a must-have for any library. Audience: Practitioners, consultants, engineers, academics, and other professionals working in the areas of cyber analysis, cyber security, homeland security, national defense, the protection of national critical infrastructures, cyber-crime, cyber vulnerabilities, cyber-attacks related to network systems, cyber threat reduction planning, and those who provide leadership in cyber security management both in public and private sectors

Cyber Threat Intelligence

DOWNLOAD
Author : Ali Dehghantanha
language : en
Publisher: Springer
Release Date : 2018-04-27

Cyber Threat Intelligence written by Ali Dehghantanha and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-27 with Computers categories.

This book provides readers with up-to-date research of emerging cyber threats and defensive mechanisms, which are timely and essential. It covers cyber threat intelligence concepts against a range of threat actors and threat tools (i.e. ransomware) in cutting-edge technologies, i.e., Internet of Things (IoT), Cloud computing and mobile devices. This book also provides the technical information on cyber-threat detection methods required for the researcher and digital forensics experts, in order to build intelligent automated systems to fight against advanced cybercrimes. The ever increasing number of cyber-attacks requires the cyber security and forensic specialists to detect, analyze and defend against the cyber threats in almost real-time, and with such a large number of attacks is not possible without deeply perusing the attack features and taking corresponding intelligent defensive actions – this in essence defines cyber threat intelligence notion. However, such intelligence would not be possible without the aid of artificial intelligence, machine learning and advanced data mining techniques to collect, analyze, and interpret cyber-attack campaigns which is covered in this book. This book will focus on cutting-edge research from both academia and industry, with a particular emphasis on providing wider knowledge of the field, novelty of approaches, combination of tools and so forth to perceive reason, learn and act on a wide range of data collected from different cyber security and forensics solutions. This book introduces the notion of cyber threat intelligence and analytics and presents different attempts in utilizing machine learning and data mining techniques to create threat feeds for a range of consumers. Moreover, this book sheds light on existing and emerging trends in the field which could pave the way for future works. The inter-disciplinary nature of this book, makes it suitable for a wide range of audiences with backgrounds in artificial intelligence, cyber security, forensics, big data and data mining, distributed systems and computer networks. This would include industry professionals, advanced-level students and researchers that work within these related fields.

Exploiting Machine Learning For Robust Security

DOWNLOAD
Author : Minakshi
language : en
Publisher: IGI Global
Release Date : 2025-04-16

Exploiting Machine Learning For Robust Security written by Minakshi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-16 with Computers categories.

In the digital world, ensuring robust security is critical as cyber threats become more sophisticated and pervasive. Machine learning can be used to strengthen cybersecurity and offer dynamic solutions that can identify, predict, and mitigate potential risks with unprecedented accuracy. By analyzing vast amounts of data, detecting patterns, and adapting to evolving threats, machine learning enables security systems to autonomously respond to anomalies and protect sensitive information in real-time. As technology advances, the integration of machine learning into security systems represents a critical step towards creating adaptive protection against the complex challenges of modern cybersecurity. Further research into the potential of machine learning in enhancing security protocols may highlight its ability to prevent cyberattacks, detect vulnerabilities, and ensure resilient defenses. Exploiting Machine Learning for Robust Security explores the world of machine learning, discussing the darknet of threat detection and vulnerability assessment, malware analysis, and predictive security analysis. Using case studies, it explores machine learning for threat detection and bolstered online defenses. This book covers topics such as anomaly detection, threat intelligence, and machine learning, and is a useful resource for engineers, security professionals, computer scientists, academicians, and researchers.