Threat intelligence is a surprisingly complex topic that goes far beyond the obvious technical challenges of collecting, modelling and sharing technical indicators. Most books in this area focus mainly on technical measures to harden a system based on threat intel data and limit their scope to single organizations only. This book provides a unique angle on the topic of national cyber threat intelligence and security information sharing. It also provides a clear view on ongoing works in research laboratories world-wide in order to address current security concerns at national level. It allows practitioners to learn about upcoming trends, researchers to share current results, and decision makers to prepare for future developments.

Threat intelligence is a surprisingly complex topic that goes far beyond the obvious technical challenges of collecting, modelling and sharing technical indicators. Most books in this area focus mainly on technical measures to harden a system based on threat intel data and limit their scope to single organizations only. This book provides a unique angle on the topic of national cyber threat intelligence and security information sharing. It also provides a clear view on ongoing works in research laboratories world-wide in order to address current security concerns at national level. It allows practitioners to learn about upcoming trends, researchers to share current results, and decision makers to prepare for future developments.

Cyber threats are ever increasing. Adversaries are getting more sophisticated and cyber criminals are infiltrating companies in a variety of sectors. In today’s landscape, organizations need to acquire and develop effective security tools and mechanisms – not only to keep up with cyber criminals, but also to stay one step ahead. Cyber-Vigilance and Digital Trust develops cyber security disciplines that serve this double objective, dealing with cyber security threats in a unique way. Specifically, the book reviews recent advances in cyber threat intelligence, trust management and risk analysis, and gives a formal and technical approach based on a data tainting mechanism to avoid data leakage in Android systems

Get to grips with cyber threat intelligence and data-driven threat hunting while exploring expert tips and techniques Key Features Set up an environment to centralize all data in an Elasticsearch, Logstash, and Kibana (ELK) server that enables threat hunting Carry out atomic hunts to start the threat hunting process and understand the environment Perform advanced hunting using MITRE ATT&CK Evals emulations and Mordor datasets Book DescriptionThreat hunting (TH) provides cybersecurity analysts and enterprises with the opportunity to proactively defend themselves by getting ahead of threats before they can cause major damage to their business. This book is not only an introduction for those who don’t know much about the cyber threat intelligence (CTI) and TH world, but also a guide for those with more advanced knowledge of other cybersecurity fields who are looking to implement a TH program from scratch. You will start by exploring what threat intelligence is and how it can be used to detect and prevent cyber threats. As you progress, you’ll learn how to collect data, along with understanding it by developing data models. The book will also show you how to set up an environment for TH using open source tools. Later, you will focus on how to plan a hunt with practical examples, before going on to explore the MITRE ATT&CK framework. By the end of this book, you’ll have the skills you need to be able to carry out effective hunts in your own environment.What you will learn Understand what CTI is, its key concepts, and how it is useful for preventing threats and protecting your organization Explore the different stages of the TH process Model the data collected and understand how to document the findings Simulate threat actor activity in a lab environment Use the information collected to detect breaches and validate the results of your queries Use documentation and strategies to communicate processes to senior management and the wider business Who this book is for If you are looking to start out in the cyber intelligence and threat hunting domains and want to know more about how to implement a threat hunting division with open-source tools, then this cyber threat intelligence book is for you.

Drawing upon years of practical experience and using numerous examples and illustrative case studies, Threat Forecasting: Leveraging Big Data for Predictive Analysis discusses important topics, including the danger of using historic data as the basis for predicting future breaches, how to use security intelligence as a tool to develop threat forecasting techniques, and how to use threat data visualization techniques and threat simulation tools. Readers will gain valuable security insights into unstructured big data, along with tactics on how to use the data to their advantage to reduce risk. - Presents case studies and actual data to demonstrate threat data visualization techniques and threat simulation tools - Explores the usage of kill chain modelling to inform actionable security intelligence - Demonstrates a methodology that can be used to create a full threat forecast analysis for enterprise networks of any size

In recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromised data and sufficient losses. Massive losses and frequent attacks dictate the need for accurate and timely detection methods. Current static and dynamic methods do not provide efficient detection, especially when dealing with zero-day attacks. For this reason, big data analytics and machine intelligencebased techniques can be used. This book brings together researchers in the field of big data analytics and intelligent systems for cyber threat intelligence CTI and key data to advance the mission of anticipating, prohibiting, preventing, preparing, and responding to internal security. The wide variety of topics it presents offers readers multiple perspectives on various disciplines related to big data analytics and intelligent systems for cyber threat intelligence applications. Technical topics discussed in the book include: • Big data analytics for cyber threat intelligence and detection • Artificial intelligence analytics techniques • Real-time situational awareness • Machine learning techniques for CTI • Deep learning techniques for CTI • Malware detection and prevention techniques • Intrusion and cybersecurity threat detection and analysis • Blockchain and machine learning techniques for CTI

This book introduces the Process for Attack Simulation & Threat Analysis (PASTA) threat modeling methodology. It provides an introduction to various types of application threat modeling and introduces a risk-centric methodology aimed at applying security countermeasures that are commensurate to the possible impact that could be sustained from defined threat models, vulnerabilities, weaknesses, and attack patterns. This book describes how to apply application threat modeling as an advanced preventive form of security. The authors discuss the methodologies, tools, and case studies of successful application threat modeling techniques. Chapter 1 provides an overview of threat modeling, while Chapter 2 describes the objectives and benefits of threat modeling. Chapter 3 focuses on existing threat modeling approaches, and Chapter 4 discusses integrating threat modeling within the different types of Software Development Lifecycles (SDLCs). Threat modeling and risk management is the focus of Chapter 5. Chapter 6 and Chapter 7 examine Process for Attack Simulation and Threat Analysis (PASTA). Finally, Chapter 8 shows how to use the PASTA risk-centric threat modeling process to analyze the risks of specific threat agents targeting web applications. This chapter focuses specifically on the web application assets that include customer’s confidential data and business critical functionality that the web application provides. • Provides a detailed walkthrough of the PASTA methodology alongside software development activities, normally conducted via a standard SDLC process • Offers precise steps to take when combating threats to businesses • Examines real-life data breach incidents and lessons for risk management Risk Centric Threat Modeling: Process for Attack Simulation and Threat Analysis is a resource for software developers, architects, technical risk managers, and seasoned security professionals.