The Economics of Financial and Medical Identity Theft discusses how the digital networked environment is critically different from the world of paper, eyeballs and pens. Many of the effective identity protections are embedded behind the eyeballs, where the presumably passive observer is actually a fairly keen student of human behavior. The emergence of medical identity theft and the implications of medical data privacy are described in the second section of this book.
The Economics of Financial and Medical Identity Theft also presents an overview of the current technology for identity management. The book closes with a series of vignettes in the last chapter, looking at the risks we may see in the future and how these risks can be mitigated or avoided.
Developed from the author's successful Springer guide to Foundations of Computer Security, this accessible textbook/reference is fully updated and enhanced with resources for students and tutors.
Topics and features: examines the physical security of computer hardware, networks, and digital data; introduces the different forms of rogue software (or malware), discusses methods for preventing and defending against malware, and describes a selection of viruses, worms and Trojans in detail; investigates the important threats to network security, and explores the subjects of authentication, spyware, and identity theft; discusses issues of privacy and trust in the online world, including children's privacy and safety; includes appendices which discuss the definition, meaning, and history of the term hacker, introduce the language of "l33t Speak", and provide a detailed virus timeline; provides numerous exercises and examples throughout the text, in addition to a Glossary of terms used in the book; supplies additional resources at the associated website, http://www.DavidSalomon.name/, including an introduction to cryptography, and answers to the exercises.
Clearly and engagingly written, this concise textbook is an ideal resource for undergraduate classes on computer security. The book is mostly non-mathematical, and is suitable for anyone familiar with the basic concepts of computers and computations.
The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently.
Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.
By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse Scikit-Learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural nets
Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started.