9,050 research outputs found

    Simulation of Mixed Critical In-vehicular Networks

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    Future automotive applications ranging from advanced driver assistance to autonomous driving will largely increase demands on in-vehicular networks. Data flows of high bandwidth or low latency requirements, but in particular many additional communication relations will introduce a new level of complexity to the in-car communication system. It is expected that future communication backbones which interconnect sensors and actuators with ECU in cars will be built on Ethernet technologies. However, signalling from different application domains demands for network services of tailored attributes, including real-time transmission protocols as defined in the TSN Ethernet extensions. These QoS constraints will increase network complexity even further. Event-based simulation is a key technology to master the challenges of an in-car network design. This chapter introduces the domain-specific aspects and simulation models for in-vehicular networks and presents an overview of the car-centric network design process. Starting from a domain specific description language, we cover the corresponding simulation models with their workflows and apply our approach to a related case study for an in-car network of a premium car

    Harvey: A Greybox Fuzzer for Smart Contracts

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    We present Harvey, an industrial greybox fuzzer for smart contracts, which are programs managing accounts on a blockchain. Greybox fuzzing is a lightweight test-generation approach that effectively detects bugs and security vulnerabilities. However, greybox fuzzers randomly mutate program inputs to exercise new paths; this makes it challenging to cover code that is guarded by narrow checks, which are satisfied by no more than a few input values. Moreover, most real-world smart contracts transition through many different states during their lifetime, e.g., for every bid in an auction. To explore these states and thereby detect deep vulnerabilities, a greybox fuzzer would need to generate sequences of contract transactions, e.g., by creating bids from multiple users, while at the same time keeping the search space and test suite tractable. In this experience paper, we explain how Harvey alleviates both challenges with two key fuzzing techniques and distill the main lessons learned. First, Harvey extends standard greybox fuzzing with a method for predicting new inputs that are more likely to cover new paths or reveal vulnerabilities in smart contracts. Second, it fuzzes transaction sequences in a targeted and demand-driven way. We have evaluated our approach on 27 real-world contracts. Our experiments show that the underlying techniques significantly increase Harvey's effectiveness in achieving high coverage and detecting vulnerabilities, in most cases orders-of-magnitude faster; they also reveal new insights about contract code.Comment: arXiv admin note: substantial text overlap with arXiv:1807.0787

    Volume serving and media management in a networked, distributed client/server environment

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    The E-Systems Modular Automated Storage System (EMASS) is a family of hierarchical mass storage systems providing complete storage/'file space' management. The EMASS volume server provides the flexibility to work with different clients (file servers), different platforms, and different archives with a 'mix and match' capability. The EMASS design considers all file management programs as clients of the volume server system. System storage capacities are tailored to customer needs ranging from small data centers to large central libraries serving multiple users simultaneously. All EMASS hardware is commercial off the shelf (COTS), selected to provide the performance and reliability needed in current and future mass storage solutions. All interfaces use standard commercial protocols and networks suitable to service multiple hosts. EMASS is designed to efficiently store and retrieve in excess of 10,000 terabytes of data. Current clients include CRAY's YMP Model E based Data Migration Facility (DMF), IBM's RS/6000 based Unitree, and CONVEX based EMASS File Server software. The VolSer software provides the capability to accept client or graphical user interface (GUI) commands from the operator's console and translate them to the commands needed to control any configured archive. The VolSer system offers advanced features to enhance media handling and particularly media mounting such as: automated media migration, preferred media placement, drive load leveling, registered MediaClass groupings, and drive pooling

    The bacterial antitoxin HipB establishes a ternary complex with operator DNA and phosphorylated toxin HipA to regulate bacterial persistence

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    Nearly all bacteria exhibit a type of phenotypic growth described as persistence that is thought to underlie antibiotic tolerance and recalcitrant chronic infections. The chromosomally encoded high-persistence (Hip) toxin-antitoxin proteins HipA(SO) and HipB(SO) from Shewanella oneidensis, a proteobacterium with unusual respiratory capacities, constitute a type II toxin-antitoxin protein module. Here we show that phosphorylated HipA(SO) can engage in an unexpected ternary complex with HipB(SO) and double-stranded operator DNA that is distinct from the prototypical counterpart complex from Escherichia coli. The structure of HipB(SO) in complex with operator DNA reveals a flexible C-terminus that is sequestered by HipA(SO) in the ternary complex, indicative of its role in binding HipA(SO) to abolish its function in persistence. The structure of HipA(SO) in complex with a non-hydrolyzable ATP analogue shows that HipA(SO) autophosphorylation is coupled to an unusual conformational change of its phosphorylation loop. However, HipA(SO) is unable to phosphorylate the translation factor Elongation factor Tu, contrary to previous reports, but in agreement with more recent findings. Our studies suggest that the phosphorylation state of HipA is an important factor in persistence and that the structural and mechanistic diversity of HipAB modules as regulatory factors in bacterial persistence is broader than previously thought
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