Adopting an approach that favors full disclosure, The Rootkit Arsenal presents the most accessible, timely, and complete coverage of rootkit technology. This book covers more topics, in greater depth, than any other currently available. In doing so the author forges through the murky back alleys of the Internet, shedding light on material that has traditionally been poorly documented, partially documented, or intentionally undocumented.The spectrum of topics covered includes how to:* Hook kernel structures on multi-processor systems* Use a kernel debugger to reverse system internals* Inject call gates to create a back door into Ring-0* Use detour patches to sidestep group policy* Modify privilege levels on Vista by altering kernel objects* Utilize bootkit technology* Defeat live incident response and post-mortem forensics* Implement code armoring to protect your deliverables* Establish covert channels using the WSK and NDIS 6.0

    Beginning with an introduction to array formulas, this manual examines topics such as how they differ from ordinary formulas, the benefits and drawbacks of their use, functions that can and cannot handle array calculations, and array constants and functions. Among the practical applications surveyed include how to extract data from tables and unique lists, how to get results that match any criteria, and how to utilize various methods for unique counts. This book contains 529 screen shots.

    Siracusa's overview, wrap-up, and critique of everything new in OS X 10.10 Yosemite.

    The classic and popular text is back with refreshed pedagogy and programming problems helps the students to have an upper hand on the practical understanding of the subject. Salient Features: Expanded discussion on Recursion (Backtracking, Simulating Recursion), Spanning Trees. Covers all important topics like Strings, Arrays, Linked Lists, Trees Highly illustrative with over 300 figures and 400 solved and unsolved exercises Content 1.Introduction and Overview 2.Preliminaries 3.String Processing 4.Arrays, Records and Pointers 5.Linked Lists 6.S tacks, Queues, Recursion 7.Trees 8.Graphs and Their Applications 9.Sorting and Searching About the Author: Seymour Lipschutz Seymour Lipschutz, Professor of Mathematics, Temple University

    It aims to present these concepts and algorithms in a general setting that is not tied to one particular database system.

    From Stephen Levy—the author who made "hackers" a household word—comes this account of a revolution that is already affecting every citizen in the twenty-first century. Crypto tells the inside story of how a group of "crypto rebels"—nerds and visionaries turned freedom fighters—teamed up with corporate interests to beat Big Brother and ensure our privacy on the Internet. Levy's history of one of the most controversial and important topics of the digital age reads like the best futuristic fiction.

    

    Aiming to tell the dark secrets of computer arithmetic, this title is suitable for library developers, compiler writers, and lovers of elegant hacks.

    It's aimed at developers who might not be quite comfortable with the idea of pointers and static typing.http://openmymind.net/The-Little-Go-B...

    The most effective computer security strategies integrate network security monitoring (NSM): the collection and analysis of data to help you detect and respond to intrusions.In The Practice of Network Security Monitoring, Mandiant CSO Richard Bejtlich shows you how to use NSM to add a robust layer of protection around your networks — no prior experience required. To help you avoid costly and inflexible solutions, he teaches you how to deploy, build, and run an NSM operation using open source software and vendor-neutral tools.You'll learn how to:Determine where to deploy NSM platforms, and size them for the monitored networks Deploy stand-alone or distributed NSM installations Use command line and graphical packet analysis tools, and NSM consoles Interpret network evidence from server-side and client-side intrusions Integrate threat intelligence into NSM software to identify sophisticated adversaries There's no foolproof way to keep attackers out of your network. But when they get in, you'll be prepared. The Practice of Network Security Monitoring will show you how to build a security net to detect, contain, and control them. Attacks are inevitable, but losing sensitive data shouldn't be.

    Following a cookbook-style Problem/Solution/Discussion format, this practical handbook builds on the foundational concepts of the Go language and introduces specific strategies you can use in your day-to-day applications. You'll learn techniques for building web services, using Go in the cloud, testing and debugging, routing, network applications, and much more.

    Intended for developers who are already familiar with the Apex language, and experienced Java and C# developers who are moving to Apex, this book starts where the Force.com documentation leaves off. Instead of trying to cover all of the features of the platform, Advanced Apex programming focuses entirely on the Apex language and core design patterns. You’ll learn how to truly think in Apex – to embrace limits and bulk patterns. You’ll see how to develop architectures for efficient and reliable trigger handling, and for asynchronous operations. You’ll discover that best practices differ radically depending on whether you are building software for a specific organization or for a managed package. And you’ll find approaches for incorporating testing and diagnostic code that can dramatically improve the reliability and deployment of Apex software, and reduce your lifecycle and support costs. Based on his experience both as a consultant and as architect of a major AppExchange package, Dan Appleman focuses on the real-world problems and issues that are faced by Apex developers every day, along with the obscure problems and surprises that can sneak up on you if you are unprepared.

    The book comprises chapters on elementary data structures, dynamic programming, backtracking, algebraic problems, lower bound theory, pram algorithms, mesh algorithms, and hypercube algorithms. In addition, the book consists of several real-world examples to understand the concepts better. This book is indispensable for computer engineers preparing for competitive examinations like GATE and IES.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    This text provides a basic treatment of discrete-event simulation, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. It offers an up-to-date treatment of simulation of manufacturing and material handling systems, computer systems, and computer networks. Students and instructors will find a variety of resources at the associated website, www.bcnn.net, including simulation source code for download, additional exercises and solutions, web links and errata.