Guide to Vulnerability Analysis for Computer Networks and Systems


Book Description

This professional guide and reference examines the challenges of assessing security vulnerabilities in computing infrastructure. Various aspects of vulnerability assessment are covered in detail, including recent advancements in reducing the requirement for expert knowledge through novel applications of artificial intelligence. The work also offers a series of case studies on how to develop and perform vulnerability assessment techniques using start-of-the-art intelligent mechanisms. Topics and features: provides tutorial activities and thought-provoking questions in each chapter, together with numerous case studies; introduces the fundamentals of vulnerability assessment, and reviews the state of the art of research in this area; discusses vulnerability assessment frameworks, including frameworks for industrial control and cloud systems; examines a range of applications that make use of artificial intelligence to enhance the vulnerability assessment processes; presents visualisation techniques that can be used to assist the vulnerability assessment process. In addition to serving the needs of security practitioners and researchers, this accessible volume is also ideal for students and instructors seeking a primer on artificial intelligence for vulnerability assessment, or a supplementary text for courses on computer security, networking, and artificial intelligence.




Guide to Computer Network Security


Book Description

This timely textbook presents a comprehensive guide to the core topics in cybersecurity, covering issues of security that extend beyond traditional computer networks to the ubiquitous mobile communications and online social networks that have become part of our daily lives. In the context of our growing dependence on an ever-changing digital ecosystem, this book stresses the importance of security awareness, whether in our homes, our businesses, or our public spaces. This fully updated new edition features new material on the security issues raised by blockchain technology, and its use in logistics, digital ledgers, payments systems, and digital contracts. Topics and features: Explores the full range of security risks and vulnerabilities in all connected digital systems Inspires debate over future developments and improvements necessary to enhance the security of personal, public, and private enterprise systems Raises thought-provoking questions regarding legislative, legal, social, technical, and ethical challenges, such as the tension between privacy and security Describes the fundamentals of traditional computer network security, and common threats to security Reviews the current landscape of tools, algorithms, and professional best practices in use to maintain security of digital systems Discusses the security issues introduced by the latest generation of network technologies, including mobile systems, cloud computing, and blockchain Presents exercises of varying levels of difficulty at the end of each chapter, and concludes with a diverse selection of practical projects Offers supplementary material for students and instructors at an associated website, including slides, additional projects, and syllabus suggestions This important textbook/reference is an invaluable resource for students of computer science, engineering, and information management, as well as for practitioners working in data- and information-intensive industries.




Network Vulnerability Assessment


Book Description

Build a network security threat model with this comprehensive learning guide Key Features Develop a network security threat model for your organization Gain hands-on experience in working with network scanning and analyzing tools Learn to secure your network infrastructure Book Description The tech world has been taken over by digitization to a very large extent, and so it’s become extremely important for an organization to actively design security mechanisms for their network infrastructures. Analyzing vulnerabilities can be one of the best ways to secure your network infrastructure. Network Vulnerability Assessment starts with network security assessment concepts, workflows, and architectures. Then, you will use open source tools to perform both active and passive network scanning. As you make your way through the chapters, you will use these scanning results to analyze and design a threat model for network security. In the concluding chapters, you will dig deeper into concepts such as IP network analysis, Microsoft Services, and mail services. You will also get to grips with various security best practices, which will help you build your network security mechanism. By the end of this book, you will be in a position to build a security framework fit for an organization. What you will learn Develop a cost-effective end-to-end vulnerability management program Implement a vulnerability management program from a governance perspective Learn about various standards and frameworks for vulnerability assessments and penetration testing Understand penetration testing with practical learning on various supporting tools and techniques Gain insight into vulnerability scoring and reporting Explore the importance of patching and security hardening Develop metrics to measure the success of the vulnerability management program Who this book is for Network Vulnerability Assessment is for security analysts, threat analysts, and any security professionals responsible for developing a network threat model for an organization. This book is also for any individual who is or wants to be part of a vulnerability management team and implement an end-to-end robust vulnerability management program.




Finding and Fixing Vulnerabilities in Information Systems


Book Description

Understanding an organization's reliance on information systems and how to mitigate the vulnerabilities of these systems can be an intimidating challenge--especially when considering less well-known weaknesses or even unknown vulnerabilities that have not yet been exploited. The authors introduce the Vulnerability Assessment and Mitigation methodology, a six-step process that uses a top-down approach to protect against future threats and system failures while mitigating current and past threats and weaknesses.




Guide to Computer Network Security


Book Description

This timely textbook presents a comprehensive guide to the core topics in computing and information security and assurance realms, going beyond the security of networks to the ubiquitous mobile communications and online social networks that have become part of daily life. In the context of growing human dependence on a digital ecosystem, this book stresses the importance of security awareness—whether in homes, businesses, or public spaces. It also embraces the new and more agile and artificial-intelligence-boosted computing systems models, online social networks, and virtual platforms that are interweaving and fueling growth of an ecosystem of intelligent digital and associated social networks. This fully updated edition features new material on new and developing artificial intelligence models across all computing security systems spheres, blockchain technology, and the metaverse, leading toward security systems virtualizations. Topics and features: Explores the range of risks and vulnerabilities in all connected digital systems Presents exercises of varying levels of difficulty at the end of each chapter, and concludes with a diverse selection of practical projects Describes the fundamentals of traditional computer network security, and common threats to security Discusses the role and challenges of artificial intelligence in advancing the security of computing systems’ algorithms, protocols, and best practices Raises thought-provoking questions regarding legislative, legal, social, technical, and ethical challenges, such as the tension between privacy and security Offers supplementary material for students and instructors at an associated website, including slides, additional projects, and syllabus suggestions This important textbook/reference is an invaluable resource for students of computer science, engineering, and information management, as well as for practitioners working in data- and information-intensive industries. Professor Joseph Migga Kizza is a professor, former Head of the Department of Computer Science and Engineering, and a former Director of the UTC InfoSec Center, at the University of Tennessee at Chattanooga, USA. He also authored the successful Springer textbooks Ethical and Social Issues in the Information Age and Ethical and Secure Computing: A Concise Module.




Information Security Technologies for Controlling Pandemics


Book Description

The year 2020 and the COVID-19 pandemic marked a huge change globally, both in working and home environments. They posed major challenges for organisations around the world, which were forced to use technological tools to help employees work remotely, while in self-isolation and/or total lockdown. Though the positive outcomes of using these technologies are clear, doing so also comes with its fair share of potential issues, including risks regarding data and its use, such as privacy, transparency, exploitation and ownership. COVID-19 also led to a certain amount of paranoia, and the widespread uncertainty and fear of change represented a golden opportunity for threat actors. This book discusses and explains innovative technologies such as blockchain and methods to defend from Advanced Persistent Threats (APTs), some of the key legal and ethical data challenges to data privacy and security presented by the COVID-19 pandemic, and their potential consequences. It then turns to improved decision making in cyber security, also known as cyber situational awareness, by analysing security events and comparing data mining techniques, specifically classification techniques, when applied to cyber security data. In addition, the book illustrates the importance of cyber security, particularly information integrity and surveillance, in dealing with an on-going, infectious crisis. Aspects addressed range from the spread of misinformation, which can lead people to actively work against measures designed to ensure public safety and minimise the spread of the virus, to concerns over the approaches taken to monitor, track, trace and isolate infectious cases through the use of technology. In closing, the book considers the legal, social and ethical cyber and information security implications of the pandemic and responses to it from the perspectives of confidentiality, integrity and availability.




Cyber Security of Industrial Control Systems in the Future Internet Environment


Book Description

In today’s modernized market, many fields are utilizing internet technologies in their everyday methods of operation. The industrial sector is no different as these technological solutions have provided several benefits including reduction of costs, scalability, and efficiency improvements. Despite this, cyber security remains a crucial risk factor in industrial control systems. The same public and corporate solutions do not apply to this specific district because these security issues are more complex and intensive. Research is needed that explores new risk assessment methods and security mechanisms that professionals can apply to their modern technological procedures. Cyber Security of Industrial Control Systems in the Future Internet Environment is a pivotal reference source that provides vital research on current security risks in critical infrastructure schemes with the implementation of information and communication technologies. While highlighting topics such as intrusion detection systems, forensic challenges, and smart grids, this publication explores specific security solutions within industrial sectors that have begun applying internet technologies to their current methods of operation. This book is ideally designed for researchers, system engineers, managers, networkers, IT professionals, analysts, academicians, and students seeking a better understanding of the key issues within securing industrial control systems that utilize internet technologies.




The Internet of Things in the Industrial Sector


Book Description

This book has a focus on the development and deployment of the Industrial Internet of Things (IIoT) paradigm, discussing frameworks, methodologies, benefits and limitations, as well as providing case studies of employing the IoT vision in the industrial domain. IIoT is becoming an attractive business reality for many organisations such as manufacturing, logistics, oil and gas, energy and other utilities, mining, aviation, and many more. The opportunities for this paradigm are huge, and according to one report, the IIoT market is predicted to reach $125 billion by 2021. The driving philosophy behind the IIoT is that smart machines are better than humans at accurately capturing, analysing and communicating real-time data. The underlying technologies include distributed computing, machine learning, artificial intelligence, and machine-to-machine communication, with a typical IIoT system consisting of intelligent systems (applications, controllers, sensors, and security mechanisms), data communication infrastructure (cloud computing, edge computing, etc.), data analytics (to support business intelligence and corporate decision making), and most importantly the human element. The promised benefits of the IIoT include enhanced safety, better reliability, smart metering, inventory management, equipment tracking, and facilities management. There are, however, numerous issues that are also becoming the focus of active research, such as concerns regarding service availability, data security, and device communication. Lack of ubiquitous interoperability between heterogeneous devices is also a major concern. This book intends to fill a gap in the IIoT literature by providing the scientific contributions and latest developments from researchers and practitioners of international repute, focusing on frameworks, methodologies, benefits, and inherent issues/barriers to connected environments, especially in industrial settings. The intended audience includes network specialists, hardware engineers, and security experts who wish to adopt newer approaches for device connectivity, IoT security, and sensor-based devices design. University level students, researchers and practitioners will also find the latest innovation in technology and newer approaches relevant to the IIoT from a distributed computing perspective.







AI, Machine Learning and Deep Learning


Book Description

Today, Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society, many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices, they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, among many other attacks and threats. Such attacks can make AI products dangerous to use. While this discussion focuses on security issues in AI/ML/DL-based systems (i.e., securing the intelligent systems themselves), AI/ML/DL models and algorithms can actually also be used for cyber security (i.e., the use of AI to achieve security). Since AI/ML/DL security is a newly emergent field, many researchers and industry professionals cannot yet obtain a detailed, comprehensive understanding of this area. This book aims to provide a complete picture of the challenges and solutions to related security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then, the book describes many sets of promising solutions to achieve AI security and privacy. The features of this book have seven aspects: This is the first book to explain various practical attacks and countermeasures to AI systems Both quantitative math models and practical security implementations are provided It covers both "securing the AI system itself" and "using AI to achieve security" It covers all the advanced AI attacks and threats with detailed attack models It provides multiple solution spaces to the security and privacy issues in AI tools The differences among ML and DL security and privacy issues are explained Many practical security applications are covered