22,076 research outputs found

    A Framework for Rapid Development and Portable Execution of Packet-Handling Applications

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    This paper presents a framework that enables the execution of packet-handling applications (such as sniffers, firewalls, intrusion detectors, etc.) on different hardware platforms. This framework is centered on the NetVM - a novel, portable, and efficient virtual processor targeted for packet-based processing - and the NetPDL - a language dissociating applications from protocol specifications. In addition, a high-level programming language that enables rapid development of packet-based applications is presented

    On the Feasibility of Malware Authorship Attribution

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    There are many occasions in which the security community is interested to discover the authorship of malware binaries, either for digital forensics analysis of malware corpora or for thwarting live threats of malware invasion. Such a discovery of authorship might be possible due to stylistic features inherent to software codes written by human programmers. Existing studies of authorship attribution of general purpose software mainly focus on source code, which is typically based on the style of programs and environment. However, those features critically depend on the availability of the program source code, which is usually not the case when dealing with malware binaries. Such program binaries often do not retain many semantic or stylistic features due to the compilation process. Therefore, authorship attribution in the domain of malware binaries based on features and styles that will survive the compilation process is challenging. This paper provides the state of the art in this literature. Further, we analyze the features involved in those techniques. By using a case study, we identify features that can survive the compilation process. Finally, we analyze existing works on binary authorship attribution and study their applicability to real malware binaries.Comment: FPS 201

    Proceedings of the 3rd Workshop on Domain-Specific Language Design and Implementation (DSLDI 2015)

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    The goal of the DSLDI workshop is to bring together researchers and practitioners interested in sharing ideas on how DSLs should be designed, implemented, supported by tools, and applied in realistic application contexts. We are both interested in discovering how already known domains such as graph processing or machine learning can be best supported by DSLs, but also in exploring new domains that could be targeted by DSLs. More generally, we are interested in building a community that can drive forward the development of modern DSLs. These informal post-proceedings contain the submitted talk abstracts to the 3rd DSLDI workshop (DSLDI'15), and a summary of the panel discussion on Language Composition

    Reify Your Collection Queries for Modularity and Speed!

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    Modularity and efficiency are often contradicting requirements, such that programers have to trade one for the other. We analyze this dilemma in the context of programs operating on collections. Performance-critical code using collections need often to be hand-optimized, leading to non-modular, brittle, and redundant code. In principle, this dilemma could be avoided by automatic collection-specific optimizations, such as fusion of collection traversals, usage of indexing, or reordering of filters. Unfortunately, it is not obvious how to encode such optimizations in terms of ordinary collection APIs, because the program operating on the collections is not reified and hence cannot be analyzed. We propose SQuOpt, the Scala Query Optimizer--a deep embedding of the Scala collections API that allows such analyses and optimizations to be defined and executed within Scala, without relying on external tools or compiler extensions. SQuOpt provides the same "look and feel" (syntax and static typing guarantees) as the standard collections API. We evaluate SQuOpt by re-implementing several code analyses of the Findbugs tool using SQuOpt, show average speedups of 12x with a maximum of 12800x and hence demonstrate that SQuOpt can reconcile modularity and efficiency in real-world applications.Comment: 20 page

    Building Efficient Query Engines in a High-Level Language

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    Abstraction without regret refers to the vision of using high-level programming languages for systems development without experiencing a negative impact on performance. A database system designed according to this vision offers both increased productivity and high performance, instead of sacrificing the former for the latter as is the case with existing, monolithic implementations that are hard to maintain and extend. In this article, we realize this vision in the domain of analytical query processing. We present LegoBase, a query engine written in the high-level language Scala. The key technique to regain efficiency is to apply generative programming: LegoBase performs source-to-source compilation and optimizes the entire query engine by converting the high-level Scala code to specialized, low-level C code. We show how generative programming allows to easily implement a wide spectrum of optimizations, such as introducing data partitioning or switching from a row to a column data layout, which are difficult to achieve with existing low-level query compilers that handle only queries. We demonstrate that sufficiently powerful abstractions are essential for dealing with the complexity of the optimization effort, shielding developers from compiler internals and decoupling individual optimizations from each other. We evaluate our approach with the TPC-H benchmark and show that: (a) With all optimizations enabled, LegoBase significantly outperforms a commercial database and an existing query compiler. (b) Programmers need to provide just a few hundred lines of high-level code for implementing the optimizations, instead of complicated low-level code that is required by existing query compilation approaches. (c) The compilation overhead is low compared to the overall execution time, thus making our approach usable in practice for compiling query engines

    A gentle transition from Java programming to Web Services using XML-RPC

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    Exposing students to leading edge vocational areas of relevance such as Web Services can be difficult. We show a lightweight approach by embedding a key component of Web Services within a Level 3 BSc module in Distributed Computing. We present a ready to use collection of lecture slides and student activities based on XML-RPC. In addition we show that this material addresses the central topics in the context of web services as identified by Draganova (2003)
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