Today, everyone recognizes the importance of safeguarding computer systems and networks from vulnerability, attack, and compromise. But computer security is neither an easy art nor a simple science: its methodologies and technologies require rigorous study, and a deep grounding in principles that can be applied even as technologies change. Moreover, practitioners must understand how to align concepts with real policies, and then actually implement those policies -- managing inevitable tradeoffs such as ´´How secure do our devices really need to be, and how much inconvenience can we accept?´´ In his extensively updated Computer Security: Art and Science, 2nd Edition, University of California at Davis Computer Security Laboratory co-director Matt Bishop offers a clear, rigorous, and thorough introduction to the entire modern field of computer security. Bishop covers access control; security, confidentiality, integrity, availability, and hybrid policies; policy composition; cryptography; authentication; identity management; information flow; assurance; formal methods; system evaluation; vulnerability analysis; auditing; intrusion detection, and many other topics. This edition adds four new chapters, including a brand-new chapter-length case study on the high-profile issue of electronic voting. Through this case study, Bishop demonstrates how principles, policies, procedures, and technology come together in a crucial real-world application.
Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of ´´recipes,´´ this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
Today, learning to program and understanding the basics of computation isn´t just indispensable for every science and engineering student: it´s crucial for everyone who wants to understand the world they live in. In Computer Science: An Interdisciplinary Approach, pioneering Princeton computer science professors Robert Sedgewick and Kevin Wayne introduce core Java programming techniques in a scientific context, while also demystifying computation and illuminating its intellectual underpinnings.
Computer Architecture: A Quantitative Approach, Sixth Edition has been considered essential reading by instructors, students and practitioners of computer design for over 20 years. The sixth edition of this classic textbook from Hennessy and Patterson, winners of the 2017 ACM A.M. Turing Award recognizing contributions of lasting and major technical importance to the computing field, is fully revised with the latest developments in processor and system architecture. The text now features examples from the RISC-V (RISC Five) instruction set architecture, a modern RISC instruction set developed and designed to be a free and openly adoptable standard. It also includes a new chapter on domain-specific architectures and an updated chapter on warehouse-scale computing that features the first public information on Google´s newest WSC. True to its original mission of demystifying computer architecture, this edition continues the longstanding tradition of focusing on areas where the most exciting computing innovation is happening, while always keeping an emphasis on good engineering design. Winner of a 2019 Textbook Excellence Award (Texty) from the Textbook and Academic Authors Association Includes a new chapter on domain-specific architectures, explaining how they are the only path forward for improved performance and energy efficiency given the end of Moore´s Law and Dennard scaling Features the first publication of several DSAs from industry Features extensive updates to the chapter on warehouse-scale computing, with the first public information on the newest Google WSC Offers updates to other chapters including new material dealing with the use of stacked DRAM; data on the performance of new NVIDIA Pascal GPU vs. new AVX-512 Intel Skylake CPU; and extensive additions to content covering multicore architecture and organization Includes ´´Putting It All Together´´ sections near the end of every chapter, providing real-world technology examples that demonstrate the principles covered in each chapter Includes review appendices in the printed text and additional reference appendices available online Includes updated and improved case studies and exercises ACM named John L. Hennessy and David A. Patterson, recipients of the 2017 ACM A.M. Turing Award for pioneering a systematic, quantitative approach to the design and evaluation of computer architectures with enduring impact on the microprocessor industry
This textbook provides an accessible general introduction to the essential topics in computer vision. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter. Features: provides an introduction to the basic notation and mathematical concepts for describing an image and the key concepts for mapping an image into an ℑ explains the topologic and geometric basics for analysing image regions and distributions of image values and discusses identifying patterns in an ℑ introduces optic flow for representing dense motion and various topics in sparse motion analysis; describes special approaches for image binarization and segmentation of still images or video frames; examines the basic components of a computer vision system; reviews different techniques for vision-based 3D shape reconstruction; includes a discussion of stereo matchers and the phase-congruency model for image features; presents an introduction into classification and learning.
Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples. The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you´ll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision. After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work. What You Will Learn Understand what computer vision is, and its overall application in intelligent automation systems Discover the deep learning techniques required to build computer vision applications Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis Who This Book Is For Those who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.
Computer-Forensik Hacks ? 100 Forensik-Hacks ist eine Sammlung von 100 thematisch sortierten Tricks und Tools, die dabei helfen, herausfordernde Probleme der Computer-Forensik zu lösen. Die im Buch vorgestellten Werkzeuge sind durchgängig Open-Source-Tools. Die detailliert beschriebenen Hacks zeigen die State-of-the-Art-Ansätze der modernen Computerforsensik. Die Hacks zeigen, wie Daten juristisch korrekt gesichert, wie gelöschte Daten und Verzeichnisse wieder hergestellt und wie digitale Spuren gesichert werden. Welche Spuren in Browsern hinterlassen werden und wie sie aufgefunden werden können, wird in weiteren Hacks dargestellt, ebenso wie Erläuterung von üblichen Angriffstechniken. Die Autoren Lorenz Kuhlee und Victor Völzow sind bei der hessischen Polizei für die Aus- und Fortbildung von Computer-Forensikern zuständig. Computer-Forensik Hacks ist eine Sammlung von Methoden, Tipps und Tricks - kurz: Hacks - aus allen Bereichen der Computer-Forensik. Die Autoren, die bei der Polizei Forensiker ausbilden, haben praktische Lösungen für echte Problemstellungen aus dem Computer-Forensik-Alltag in kleine, bekömmliche Portionen gepackt, die direkt angewendet werden können. Zu jeder praktischen Lösung gibt es auch das notwendige Hintergrundwissen mit auf den Weg, das benötigt wird, um sowohl das Problem wie auch den Lösungsansatz nachvollziehen zu können. Nicht nur für Forensiker Nicht nur Forensiker müssen heutzutage wissen, wie sie den Zustand eines Computersystems sichern können, damit dies bei späteren Gerichtsverhandlungen juristisch wasserdicht ist. Auch für Systemadministratoren aus der freien Wirtschaft gehört mittlerweile ein computer-forsensisches Grundwissen zum Arbeitsalltag. Und auch Rechtsanwälte benötigen immer wieder Wissen darüber, was bei einer Datensicherung beachtet werden muss.
Jeder kennt das: Webseiten, auf denen man die Schrift nicht lesen kann - Informationsterminals, bei denen man nicht erkennt, wo man drücken soll - Programme, die unverständliche Meldungen hervorbringen - kurz: Software, die nicht zu gebrauchen ist. Das Lehrbuch ´´Mensch-Computer-Interaktion´´ enthält das Basiswissen, das alle Programmentwickler benötigen, die wirklich benutzerfreundliche Software erstellen wollen. Ausgehend von der menschlichen Informationsverarbeitung wird dargestellt, wie Benutzeroberflächen beschaffen sein müssen, damit Menschen Software sinnvoll nutzen können. Praktische Aufgaben und Beispiele vertiefen die Lehrinhalte unter Beachtung der gesetzlich vorgeschriebenen Normen.
Structure and Interpretation of Computer Programs has had a dramatic impact on computer science curricula over the past decade. This long-awaited revision contains changes throughout the text.