But how do you interpret those packets once you've captured them? And how can those packets help you to better understand what's going on under the hood of your network? Practical Packet Analysis shows how to use Wireshark to capture and then analyze packets as you take an indepth look at real-world packet analysis and network troubleshooting. The way the pros do it.Wireshark (derived from the Ethereal project), has become the world's most popular network sniffing application. But while Wireshark comes with documentation, there's not a whole lot of information to show you how to use it in real-world scenarios. Practical Packet Analysis shows you how to:Use packet analysis to tackle common network problems, such as loss of connectivity, slow networks, malware infections, and more Build customized capture and display filters Tap into live network communication Graph traffic patterns to visualize the data flowing across your network Use advanced Wireshark features to understand confusing packets Build statistics and reports to help you better explain technical network information to non-technical usersBecause net-centric computing requires a deep understanding of network communication at the packet level, Practical Packet Analysis is a must have for any network technician, administrator, or engineer troubleshooting network problems of any kind.

    In this revision, the author takes a structured approach to explaining how networks function.

    Wolfram lets the world see his work in A New Kind of Science, a gorgeous, 1,280-page tome more than a decade in the making. With patience, insight, and self-confidence to spare, Wolfram outlines a fundamental new way of modeling complex systems. On the frontier of complexity science since he was a boy, Wolfram is a champion of cellular automata--256 "programs" governed by simple nonmathematical rules. He points out that even the most complex equations fail to accurately model biological systems, but the simplest cellular automata can produce results straight out of nature--tree branches, stream eddies, and leopard spots, for instance. The graphics in A New Kind of Science show striking resemblance to the patterns we see in nature every day. Wolfram wrote the book in a distinct style meant to make it easy to read, even for nontechies; a basic familiarity with logic is helpful but not essential. Readers will find themselves swept away by the elegant simplicity of Wolfram's ideas and the accidental artistry of the cellular automaton models. Whether or not Wolfram's revolution ultimately gives us the keys to the universe, his new science is absolutely awe-inspiring. --Therese Littleton

    Reverse engineering is not about reading assembly code, but actually understanding how different pieces/components in a system work. To reverse engineer a system is to understand how it is constructed and how it works. The book provides: Coverage of x86, x64, and ARM. In the past x86 was the most common architecture on the PC; however, times have changed and x64 is becoming the dominant architecture. It brings new complexity and constructs previously not present in x86. ARM ("Advanced RISC Machine) "is very common in embedded / consumer electronic devices; for example, most if not all cell phones run on ARM. All of apple's i-devices run on ARM. This book will be the first book to cover all three.Discussion of Windows kernel-mode code (rootkits/drivers). This topic has a steep learning curve so most practitioners stay away from this area because it is highly complex. However, this book will provide a concise treatment of this topic and explain how to analyze drivers step-by-step.The book uses real world examples from the public domain. The best way to learn is through a combination of concept discussions, examples, and exercises. This book uses real-world trojans / rootkits as examples congruent with real-life scenariosHands-on exercises. End-of-chapter exercises in the form of conceptual questions and hands-on analysis so so readers can solidify their understanding of the concepts and build confidence. The exercises are also meant to teach readers about topics not covered in the book.

    Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.

    The RTFM contains the basic syntax for commonly used Linux and Windows command line tools, but it also encapsulates unique use cases for powerful tools such as Python and Windows PowerShell. The RTFM will repeatedly save you time looking up the hard to remember Windows nuances such as Windows wmic and dsquery command line tools, key registry values, scheduled tasks syntax, startup locations and Windows scripting. More importantly, it should teach you some new red team techniques.

    With the unwitting help of its users, the generative Internet is on a path to a lockdown, ending its cycle of innovation—and facilitating unsettling new kinds of control.IPods, iPhones, Xboxes, and TiVos represent the first wave of Internet-centered products that can’t be easily modified by anyone except their vendors or selected partners. These “tethered appliances” have already been used in remarkable but little-known ways: car GPS systems have been reconfigured at the demand of law enforcement to eavesdrop on the occupants at all times, and digital video recorders have been ordered to self-destruct thanks to a lawsuit against the manufacturer thousands of miles away. New Web 2.0 platforms like Google mash-ups and Facebook are rightly touted—but their applications can be similarly monitored and eliminated from a central source. As tethered appliances and applications eclipse the PC, the very nature of the Internet—its “generativity,” or innovative character—is at risk.The Internet’s current trajectory is one of lost opportunity. Its salvation, Zittrain argues, lies in the hands of its millions of users. Drawing on generative technologies like Wikipedia that have so far survived their own successes, this book shows how to develop new technologies and social structures that allow users to work creatively and collaboratively, participate in solutions, and become true “netizens.”The book is available to download under a Creative Commons Attribution Non-Commercial Share-Alike 3.0 license: Download PDF. http://futureoftheinternet.org/download

    The first edition of this book, Programming Perl, hit the shelves in 1990, and was quickly adopted as the undisputed bible of the language. Since then, Perl has grown with the times, and so has this book.Programming Perl is not just a book about Perl. It is also a unique introduction to the language and its culture, as one might expect only from its authors. Larry Wall is the inventor of Perl, and provides a unique perspective on the evolution of Perl and its future direction. Tom Christiansen was one of the first champions of the language, and lives and breathes the complexities of Perl internals as few other mortals do. Jon Orwant is the editor of The Perl Journal, which has brought together the Perl community as a common forum for new developments in Perl.Any Perl book can show the syntax of Perl's functions, but only this one is a comprehensive guide to all the nooks and crannies of the language. Any Perl book can explain typeglobs, pseudohashes, and closures, but only this one shows how they really work. Any Perl book can say that my is faster than local, but only this one explains why. Any Perl book can have a title, but only this book is affectionately known by all Perl programmers as "The Camel."This third edition of Programming Perl has been expanded to cover version 5.6 of this maturing language. New topics include threading, the compiler, Unicode, and other new features that have been added since the previous edition.

    Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

    His breaking of the German U-boat Enigma cipher in World War II ensured Allied-American control of the Atlantic. But Turing's vision went far beyond the desperate wartime struggle. Already in the 1930s he had defined the concept of the universal machine, which underpins the computer revolution. In 1945 he was a pioneer of electronic computer design. But Turing's true goal was the scientific understanding of the mind, brought out in the drama and wit of the famous "Turing test" for machine intelligence and in his prophecy for the twenty-first century.Drawn in to the cockpit of world events and the forefront of technological innovation, Alan Turing was also an innocent and unpretentious gay man trying to live in a society that criminalized him. In 1952 he revealed his homosexuality and was forced to participate in a humiliating treatment program, and was ever after regarded as a security risk. His suicide in 1954 remains one of the many enigmas in an astonishing life story.

    

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.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 how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    Jill Lepore, best-selling author of These Truths, came across the company’s papers in MIT’s archives and set out to tell this forgotten history, the long-lost backstory to the methods, and the arrogance, of Silicon Valley.Founded in 1959 by some of the nation’s leading social scientists—“the best and the brightest, fatally brilliant, Icaruses with wings of feathers and wax, flying to the sun”—Simulmatics proposed to predict and manipulate the future by way of the computer simulation of human behavior. In summers, with their wives and children in tow, the company’s scientists met on the beach in Long Island under a geodesic, honeycombed dome, where they built a “People Machine” that aimed to model everything from buying a dishwasher to counterinsurgency to casting a vote. Deploying their “People Machine” from New York, Washington, Cambridge, and even Saigon, Simulmatics’ clients included the John F. Kennedy presidential campaign, the New York Times, the Department of Defense, and dozens of major manufacturers: Simulmatics had a hand in everything from political races to the Vietnam War to the Johnson administration’s ill-fated attempt to predict race riots. The company’s collapse was almost as rapid as its ascent, a collapse that involved failed marriages, a suspicious death, and bankruptcy. Exposed for false claims, and even accused of war crimes, it closed its doors in 1970 and all but vanished. Until Lepore came across the records of its remains.The scientists of Simulmatics believed they had invented “the A-bomb of the social sciences.” They did not predict that it would take decades to detonate, like a long-buried grenade. But, in the early years of the twenty-first century, that bomb did detonate, creating a world in which corporations collect data and model behavior and target messages about the most ordinary of decisions, leaving people all over the world, long before the global pandemic, crushed by feelings of helplessness. This history has a past; If Then is its cautionary tale.

    While there will be the inevitable criticism that the material contained in the book could be used maliciously, the fact is that this knowledge is already in the hands of our enemies. This book is truly designed to inform while entertaining (and scaring) the reader, and it will instantly be in demand by readers of "Stealing the Network: How to Own the Box" * A meticulously detailed and technically accurate work of fiction that exposes the very real possibilities of such an event occurring* An informative and scary insight into the boundries of hacking and cyber-terrorism* Written by a team of the most accomplished cyber-security specialists in the world

      Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.