Arash Habibi Lashkari – författare

This book discusses understand cybersecurity management in decentralized finance (DeFi). It commences with introducing fundamentals of DeFi and cybersecurity to readers. It emphasizes on the importance of cybersecurity for decentralized finance by illustrating recent cyber breaches, attacks, and financial losses. The book delves into understanding cyber threats and adversaries who can exploit those threats. It advances with cybersecurity threat, vulnerability, and risk management in DeFi. The book helps readers understand cyber threat landscape comprising different threat categories for that can exploit different types of vulnerabilities identified in DeFi. It puts forward prominent threat modelling strategies by focusing on attackers, assets, and software.

The book includes the popular blockchains that support DeFi include Ethereum, Binance Smart Chain, Solana, Cardano, Avalanche, Polygon, among others. With so much monetary value associated with all these technologies, theperpetrators are always lured to breach security by exploiting the vulnerabilities that exist in these technologies. For simplicity and clarity, all vulnerabilities are classified into different categories: arithmetic bugs, re-Entrancy attack, race conditions, exception handling, using a weak random generator, timestamp dependency, transaction-ordering dependence and front running, vulnerable libraries, wrong initial assumptions, denial of service, flash loan attacks, and vampire

Since decentralized finance infrastructures are the worst affected by cyber-attacks, it is imperative to understand various security issues in different components of DeFi infrastructures and proposes measures to secure all components of DeFi infrastructures. It brings the detailed cybersecurity policies and strategies that can be used to secure financial institutions. Finally, the book provides recommendations to secure DeFi infrastructures from cyber-attacks.

This book offers a comprehensive overview of smartphone security, focusing on various operating systems and their associated challenges. It covers the smartphone industry''s evolution, emphasizing security and privacy concerns. It explores Android, iOS, and Windows OS security vulnerabilities and mitigation measures. Additionally, it discusses alternative OSs like Symbian, Tizen, Sailfish, Ubuntu Touch, KaiOS, Sirin, and HarmonyOS.

The book also addresses mobile application security, best practices for users and developers, Mobile Device Management (MDM) in enterprise settings, mobile network security, and the significance of mobile cloud security and emerging technologies such as IoT, AI, ML, and blockchain. It discusses the importance of balancing innovation with solid security practices in the ever-evolving mobile technology landscape.

Digital technology is increasingly used in the healthcare sector, and healthcare organizations handle sensitive and confidential information that needs to be kept secure and protected. Therefore, the importance of cybersecurity in healthcare cannot be overstated. Cyber threats can compromise patient data, disrupt healthcare services, and put personal safety at risk. This book provides an understanding of cybersecurity in healthcare, which is crucial for protecting personal information, ensuring compliance with regulations, maintaining patient trust, and preventing cyber-attacks. Before defining cybersecurity in healthcare, the authors introduce the healthcare environment and cybersecurity basics to readers. They then emphasize the importance of data protection and privacy, software, and personal cybersecurity. Also, they highlight the importance of educating staff about cybersecurity. The discussion continues with data and information security in healthcare, including data threats and vulnerabilities, the difference between data protection and privacy, and how to protect data. Afterward, they focus on the software system frameworks and types of infra-security and app security in healthcare. A key goal of this book is to provide readers with an understanding of how to detect and prevent cyber-attacks in the healthcare sector and how to respond to and recover from them. Moreover, it gives them an insight into cybersecurity vulnerabilities in healthcare and how they are mitigated. A chapter on cybersecurity ethics and healthcare data governance frameworks is also included in the book. The last chapter explores the challenges healthcare organizations face in maintaining security compliance and security practice guidelines that exist. By understanding the risks and challenges of cybersecurity in healthcare, healthcare providers and organizations can better protect sensitive and confidential data and ensure the safety and privacy of those they serve.

This book presents an overview of the emerging topics in Artificial Intelligence (AI) and cybersecurity and addresses the latest AI models that could be potentially applied to a range of cybersecurity areas. Furthermore, it provides different techniques of how to make the AI algorithms secure from adversarial attacks. The book presents the cyber threat landscape and explains the various spectrums of AI and the applications and limitations of AI in cybersecurity. Moreover, it explores the applications and limitations of secure AI. The authors discuss the three categories of machine learning (ML) models and reviews cutting-edge recent Deep Learning (DL) models. Furthermore, the book provides a general AI framework in security as well as different modules of the framework; similarly, chapter four proposes a general framework for secure AI. It explains different aspects of network security including malware and attacks.

The book also includes a comprehensive study of various scopes of application security; categorised into three groups of smartphone, web application, and desktop application and delves into the concepts of cloud security. The authors discuss state-of-the-art Internet of Things (IoT) security and describe various challenges of AI for cybersecurity, such as data diversity, model customising, explainability, and time complexity and includes some future work. They provide a comprehensive understanding of adversarial machine learning including the up-to-date adversarial attacks and defences. The book finishes off with a discussion of the challenges and future work in secure AI.