This book provides an in-depth look at return-oriented programming attacks. It explores several conventional return-oriented programming attacks and analyzes the effectiveness of defense techniques including address space layout randomization (ASLR) and the control-flow restrictions implemented in security watchdogs such as Microsoft EMET. Chapters also explain the principle of control-flow integrity (CFI), highlight the benefits of CFI and discuss its current weaknesses. Several improved and sophisticated return-oriented programming attack techniques such as just-in-time return-oriented programming are presented. Building Secure Defenses against Code-Reuse Attacks is an excellent reference tool for researchers, programmers and professionals working in the security field. It provides advanced-level students studying computer science with a comprehensive overview and clear understanding of important runtime attacks.

Die 15. GI/ITG-Fachtagung "Kommunikation in Verteilten Systemen (KiVS 2007)" befasst sich mit einer großen Vielfalt innovativer und zukunftsorientierter Fragen: Overlay- und Peer to Peer-Netze, Sensornetze, mobile Ad Hoc-Netze, Web Services. Die KiVS 2007 dient der Standortbestimmung aktueller Entwicklungen, der Präsentation laufender Forschungsarbeiten und der Diskussion zukunftsträchtiger Ansätze für die Kommunikation in verteilten Systemen.

Proceedings of the 30th Annual International Conference on Very Large Data Bases held in Toronto, Canada on August 31 - September 3 2004. Organized by the VLDB Endowment, VLDB is the premier international conference on database technology.

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.

For more than the last three decades, the security of software systems has been an important area of computer science, yet it is a rather recent general recognition that technologies for software security are highly needed. This book assesses the state of the art in software and systems security by presenting a carefully arranged selection of revised invited and reviewed papers. It covers basic aspects and recently developed topics such as security of pervasive computing, peer-to-peer systems and autonomous distributed agents, secure software circulation, compilers for fail-safe C language, construction of secure mail systems, type systems and multiset rewriting systems for security protocols, and privacy issues as well.

Mastering Cloud Computing is designed for undergraduate students learning to develop cloud computing applications. Tomorrow's applications won't live on a single computer but will be deployed from and reside on a virtual server, accessible anywhere, any time. Tomorrow's application developers need to understand the requirements of building apps for these virtual systems, including concurrent programming, high-performance computing, and data-intensive systems. The book introduces the principles of distributed and parallel computing underlying cloud architectures and specifically focuses on virtualization, thread programming, task programming, and map-reduce programming. There are examples demonstrating all of these and more, with exercises and labs throughout. - Explains how to make design choices and tradeoffs to consider when building applications to run in a virtual cloud environment - Real-world case studies include scientific, business, and energy-efficiency considerations