A comprehensive guide that will give you hands-on experience to study and overcome financial cyber threats Key FeaturesProtect your financial environment with cybersecurity practices and methodologiesIdentify vulnerabilities such as data manipulation and fraudulent transactionsProvide end-to-end protection within organizationsBook Description Organizations have always been a target of cybercrime. Hands-On Cybersecurity for Finance teaches you how to successfully defend your system against common cyber threats, making sure your financial services are a step ahead in terms of security. The book begins by providing an overall description of cybersecurity, guiding you through some of the most important services and technologies currently at risk from cyber threats. Once you have familiarized yourself with the topic, you will explore specific technologies and threats based on case studies and real-life scenarios. As you progress through the chapters, you will discover vulnerabilities and bugs (including the human risk factor), gaining an expert-level view of the most recent threats. You'll then explore information on how you can achieve data and infrastructure protection. In the concluding chapters, you will cover recent and significant updates to procedures and configurations, accompanied by important details related to cybersecurity research and development in IT-based financial services. By the end of the book, you will have gained a basic understanding of the future of information security and will be able to protect financial services and their related infrastructures. What you will learnUnderstand the cyber threats faced by organizationsDiscover how to identify attackersPerform vulnerability assessment, software testing, and pentestingDefend your financial cyberspace using mitigation techniques and remediation plansImplement encryption and decryptionUnderstand how Artificial Intelligence (AI) affects cybersecurityWho this book is for Hands-On Cybersecurity for Finance is for you if you are a security architect, cyber risk manager, or pentester looking to secure your organization. Basic understanding of cybersecurity tools and practices will help you get the most out of this book.

Build smart cybersecurity systems with the power of machine learning and deep learning to protect your corporate assets Key FeaturesIdentify and predict security threats using artificial intelligenceDevelop intelligent systems that can detect unusual and suspicious patterns and attacksLearn how to test the effectiveness of your AI cybersecurity algorithms and toolsBook Description Today's organizations spend billions of dollars globally on cybersecurity. Artificial intelligence has emerged as a great solution for building smarter and safer security systems that allow you to predict and detect suspicious network activity, such as phishing or unauthorized intrusions. This cybersecurity book presents and demonstrates popular and successful AI approaches and models that you can adapt to detect potential attacks and protect your corporate systems. You'll learn about the role of machine learning and neural networks, as well as deep learning in cybersecurity, and you'll also learn how you can infuse AI capabilities into building smart defensive mechanisms. As you advance, you'll be able to apply these strategies across a variety of applications, including spam filters, network intrusion detection, botnet detection, and secure authentication. By the end of this book, you'll be ready to develop intelligent systems that can detect unusual and suspicious patterns and attacks, thereby developing strong network security defenses using AI. What you will learnDetect email threats such as spamming and phishing using AICategorize APT, zero-days, and polymorphic malware samplesOvercome antivirus limits in threat detectionPredict network intrusions and detect anomalies with machine learningVerify the strength of biometric authentication procedures with deep learningEvaluate cybersecurity strategies and learn how you can improve themWho this book is for If you’re a cybersecurity professional or ethical hacker who wants to build intelligent systems using the power of machine learning and AI, you’ll find this book useful. Familiarity with cybersecurity concepts and knowledge of Python programming is essential to get the most out of this book.

Exploring the negative social impact of cyber-attacks, this book takes a closer look at the challenges faced by both the public and private sectors of the financial industry. It is widely known amongst senior executives in both sectors that cybercrime poses a real threat, however effective collaboration between individual financial institutions and the public sector into detecting, monitoring and responding to cyber-attacks remains limited. Addressing this problem, the authors present the results from a series of interviews with cybersecurity professionals based in Canada in order to better understand the potential risks and threats that financial institutions are facing in the digital age. Offering policy recommendations for improving cybersecurity protection measures within financial institutions, and enhancing the sharing of information between the public and private sector, this book is a timely and invaluable read for those researching financial services, cybercrime and risk management, as well as finance professionals interested in cybersecurity.

Understand critical cybersecurity and risk perspectives, insights, and tools for the leaders of complex financial systems and markets. This book offers guidance for decision makers and helps establish a framework for communication between cyber leaders and front-line professionals. Information is provided to help in the analysis of cyber challenges and choosing between risk treatment options. Financial cybersecurity is a complex, systemic risk challenge that includes technological and operational elements. The interconnectedness of financial systems and markets creates dynamic, high-risk environments where organizational security is greatly impacted by the level of security effectiveness of partners, counterparties, and other external organizations. The result is a high-risk environment with a growing need for cooperation between enterprises that are otherwise direct competitors. There is a new normal of continuous attack pressures that produce unprecedented enterprise threats that must be met with an array of countermeasures. Financial Cybersecurity Risk Management explores a range of cybersecurity topics impacting financial enterprises. This includes the threat and vulnerability landscape confronting the financial sector, risk assessment practices and methodologies, and cybersecurity data analytics. Governance perspectives, including executive and board considerations, are analyzed as are the appropriate control measures and executive risk reporting. What You’ll Learn Analyze the threat and vulnerability landscape confronting the financial sector Implement effective technology risk assessment practices and methodologies Craft strategies to treat observed risks in financial systemsImprove the effectiveness of enterprise cybersecurity capabilities Evaluate critical aspects of cybersecurity governance, including executive and board oversight Identify significant cybersecurity operational challenges Consider the impact of the cybersecurity mission across the enterpriseLeverage cybersecurity regulatory and industry standards to help manage financial services risksUse cybersecurity scenarios to measure systemic risks in financial systems environmentsApply key experiences from actual cybersecurity events to develop more robust cybersecurity architectures Who This Book Is For Decision makers, cyber leaders, and front-line professionals, including: chief risk officers, operational risk officers, chief information security officers, chief security officers, chief information officers, enterprise risk managers, cybersecurity operations directors, technology and cybersecurity risk analysts, cybersecurity architects and engineers, and compliance officers

Get into the world of smart data security using machine learning algorithms and Python libraries Key FeaturesLearn machine learning algorithms and cybersecurity fundamentalsAutomate your daily workflow by applying use cases to many facets of securityImplement smart machine learning solutions to detect various cybersecurity problemsBook Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learnUse machine learning algorithms with complex datasets to implement cybersecurity conceptsImplement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problemsLearn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDAUnderstand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimesUse TensorFlow in the cybersecurity domain and implement real-world examplesLearn how machine learning and Python can be used in complex cyber issuesWho this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book

This practical textbook offers a hands-on introduction to big data analytics, helping you to develop the skills required to hit the ground running as a data professional. It complements theoretical foundations with an emphasis on the application of big data analytics, illustrated by real-life examples and datasets. Containing comprehensive coverage of all the key topics in this area, this book uses open-source technologies and examples in Python and Apache Spark. Learning features include: - Ethics by Design encourages you to consider data ethics at every stage. - Industry Insights facilitate a deeper understanding of the link between what you are studying and how it is applied in industry. - Datasets, questions, and exercises give you the opportunity to apply your learning. Dr Funmi Obembe is the Head of Technology at the Faculty of Arts, Science and Technology, University of Northampton. Dr Ofer Engel is a Data Scientist at the University of Groningen.

In the midst of several large cyberattacks in 2017, the European Commission adopted its multi-sector cybersecurity package in September of that same year. Whereas this initiative can be expected to contribute to strengthening the cyber-resilience and response of EU financial firms, several policy issues and unanswered questions remain. In order to analyse the issues that are considered to be relevant to financial fields (retail banking, corporate banking, capital markets, financial infrastructure and insurance), CEPS-ECRI organised a Task Force between September 2017 and May 2018 with a group of experts from the financial industry, tech industry, national supervisors and European institutions, as well from a consumer association and a law firm. In this book, based on the Final Report, the Task Force members identify nine policy issues that need to be further addressed in order to bolster the financial industry’s cyber-resilience against current and future threats.