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Malware Data Science
Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization. Security has become a "big data" problem. The growth rate of malware has accelerated to tens of millions of new files per year while our networks generate an ever-larger flood of security-relevant data each day. In order to defend against these advanced attacks, you'll need to know how to think like a data scientist. In Malware Data Science, security data scientist Joshua Saxe introduces machine learning, statistics, social network analysis, and data visualization, and shows you how to apply these methods to malware detection and analysis. You'll learn how t...
Malware Data Science
Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization. Security has become a "big data" problem. The growth rate of malware has accelerated to tens of millions of new files per year while our networks generate an ever-larger flood of security-relevant data each day. In order to defend against these advanced attacks, you'll need to know how to think like a data scientist. In Malware Data Science, security data scientist Joshua Saxe introduces machine learning, statistics, social network analysis, and data visualization, and shows you how to apply these methods to malware detection and analysis. You'll learn how t...
Deep Learning Applications for Cyber Security
Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.
Safety and Security of Cyber-Physical Systems
Cyber-physical systems (CPSs) consist of software-controlled computing devices communicating with each other and interacting with the physical world through sensors and actuators. Because most of the functionality of a CPS is implemented in software, the software is of crucial importance for the safety and security of the CPS. This book presents principle-based engineering for the development and operation of dependable software. The knowledge in this book addresses organizations that want to strengthen their methodologies to build safe and secure software for mission-critical cyber-physical systems. The book: • Presents a successful strategy for the management of vulnerabilities, threats, and failures in mission-critical cyber-physical systems; • Offers deep practical insight into principle-based software development (62 principles are introduced and cataloged into five categories: Business & organization, general principles, safety, security, and risk management principles); • Provides direct guidance on architecting and operating dependable cyber-physical systems for software managers and architects.
Black Hat Go
Like the best-selling Black Hat Python, Black Hat Go explores the darker side of the popular Go programming language. This collection of short scripts will help you test your systems, build and automate tools to fit your needs, and improve your offensive security skillset. Black Hat Go explores the darker side of Go, the popular programming language revered by hackers for its simplicity, efficiency, and reliability. It provides an arsenal of practical tactics from the perspective of security practitioners and hackers to help you test your systems, build and automate tools to fit your needs, and improve your offensive security skillset, all using the power of Go. You'll begin your journey wit...
Explainable AI for Cybersecurity
This book provides a comprehensive overview of security vulnerabilities and state-of-the-art countermeasures using explainable artificial intelligence (AI). Specifically, it describes how explainable AI can be effectively used for detection and mitigation of hardware vulnerabilities (e.g., hardware Trojans) as well as software attacks (e.g., malware and ransomware). It provides insights into the security threats towards machine learning models and presents effective countermeasures. It also explores hardware acceleration of explainable AI algorithms. The reader will be able to comprehend a complete picture of cybersecurity challenges and how to detect them using explainable AI. This book serves as a single source of reference for students, researchers, engineers, and practitioners for designing secure and trustworthy systems.
Machine Learning and Security
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 securit...
Artificial Neural Networks and Machine Learning – ICANN 2022
The 4-volumes set of LNCS 13529, 13530, 13531, and 13532 constitutes the proceedings of the 31st International Conference on Artificial Neural Networks, ICANN 2022, held in Bristol, UK, in September 2022. The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications. Chapter “Sim-to-Real Neural Learning with Domain Randomisation for Humanoid Robot Grasping ” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Pentesting Azure Applications
A comprehensive guide to penetration testing cloud services deployed with Microsoft Azure, the popular cloud computing service provider used by companies like Warner Brothers and Apple. Pentesting Azure Applications is a comprehensive guide to penetration testing cloud services deployed in Microsoft Azure, the popular cloud computing service provider used by numerous companies. You'll start by learning how to approach a cloud-focused penetration test and how to obtain the proper permissions to execute it; then, you'll learn to perform reconnaissance on an Azure subscription, gain access to Azure Storage accounts, and dig into Azure's Infrastructure as a Service (IaaS). You'll also learn how ...
Rootkits and Bootkits
Rootkits and Bootkits will teach you how to understand and counter sophisticated, advanced threats buried deep in a machine’s boot process or UEFI firmware. With the aid of numerous case studies and professional research from three of the world’s leading security experts, you’ll trace malware development over time from rootkits like TDL3 to present-day UEFI implants and examine how they infect a system, persist through reboot, and evade security software. As you inspect and dissect real malware, you’ll learn: • How Windows boots—including 32-bit, 64-bit, and UEFI mode—and where to find vulnerabilities • The details of boot process security mechanisms like Secure Boot, includi...
