267 research outputs found

    Verifying parameterized timed security protocols

    Get PDF
    Quantitative timing is often explicitly used in systems for better security, e.g., the credentials for automatic website logon often has limited lifetime. Verifying timing relevant security protocols in these systems is very challenging as timing adds another dimension of complexity compared with the untimed protocol verification. In our previous work, we proposed an approach to check the correctness of the timed authentication in security protocols with fixed timing constraints. However, a more difficult question persists, i.e., given a particular protocol design, whether the protocol has security flaws in its design or it can be configured secure with proper parameter values? In this work, we answer this question by proposing a parameterized verification framework, where the quantitative parameters in the protocols can be intuitively specified as well as automatically analyzed. Given a security protocol, our verification algorithm either produces the secure constraints of the parameters, or constructs an attack that works for any parameter values. The correctness of our algorithm is formally proved. We implement our method into a tool called PTAuth and evaluate it with several security protocols. Using PTAuth, we have successfully found a timing attack in Kerberos V which is unreported before.No Full Tex

    Dynamics of Gaseous Disks in a Non-axisymmetric Dark Halo

    Full text link
    The dynamics of a galactic disk in a non-axisymmetric (triaxial) dark halo is studied in detail using high-resolution, numerical, hydrodynamical models. A long-lived, two-armed spiral pattern is generated for a wide range of parameters. The spiral structure is global, and the number of turns can be two or three, depending on the model parameters. The morphology and kinematics of the spiral pattern are studied as functions of the halo and disk parameters. The spiral structure rotates slowly, and its angular velocity varies quasi-periodically. Models with differing relative halo masses, halo semi-axis ratios, distributions of matter in the disk, Mach numbers in the gaseous component, and angular rotational velocities of their halos are considered.Comment: 22 pages, 11 figure

    Blind topological measurement-based quantum computation

    Full text link
    Blind quantum computation is a novel secure quantum-computing protocol that enables Alice, who does not have sufficient quantum technology at her disposal, to delegate her quantum computation to Bob, who has a fully fledged quantum computer, in such a way that Bob cannot learn anything about Alice's input, output and algorithm. A recent proof-of-principle experiment demonstrating blind quantum computation in an optical system has raised new challenges regarding the scalability of blind quantum computation in realistic noisy conditions. Here we show that fault-tolerant blind quantum computation is possible in a topologically protected manner using the Raussendorf-Harrington-Goyal scheme. The error threshold of our scheme is 0.0043, which is comparable to that (0.0075) of non-blind topological quantum computation. As the error per gate of the order 0.001 was already achieved in some experimental systems, our result implies that secure cloud quantum computation is within reach.Comment: 17 pages, 5 figure

    Asymmetric Hsp90 N domain SUMOylation recruits Aha1 and ATP-competitive inhibitors

    Get PDF
    The stability and activity of numerous signaling proteins in both normal and cancer cells depends on the dimeric molecular chaperone heat shock protein 90 (Hsp90). Hsp90's function is coupled to ATP binding and hydrolysis and requires a series of conformational changes that are regulated by cochaperones and numerous posttranslational modifications (PTMs). SUMOylation is one of the least-understood Hsp90 PTMs. Here, we show that asymmetric SUMOylation of a conserved lysine residue in the N domain of both yeast (K178) and human (K191) Hsp90 facilitates both recruitment of the adenosine triphosphatase (ATPase)-activating cochaperone Aha1 and, unexpectedly, the binding of Hsp90 inhibitors, suggesting that these drugs associate preferentially with Hsp90 proteins that are actively engaged in the chaperone cycle. Importantly, cellular transformation is accompanied by elevated steady-state N domain SUMOylation, and increased Hsp90 SUMOylation sensitizes yeast and mammalian cells to Hsp90 inhibitors, providing a mechanism to explain the sensitivity of cancer cells to these drugs. © 2014 Elsevier Inc

    Applying advanced data analytics and machine learning to enhance the safety control of dams

    Get PDF
    The protection of critical engineering infrastructures is vital to today’s so- ciety, not only to ensure the maintenance of their services (e.g., water supply, energy production, transport), but also to avoid large-scale disasters. Therefore, technical and financial efforts are being continuously made to improve the safety control of large civil engineering structures like dams, bridges and nuclear facilities. This con- trol is based on the measurement of physical quantities that characterize the struc- tural behavior, such as displacements, strains and stresses. The analysis of monitor- ing data and its evaluation against physical and mathematical models is the strongest tool to assess the safety of the structural behavior. Commonly, dam specialists use multiple linear regression models to analyze the dam response, which is a well- known approach among dam engineers since the 1950s decade. Nowadays, the data acquisition paradigm is changing from a manual process, where measurements were taken with low frequency (e.g., on a weekly basis), to a fully automated process that allows much higher frequencies. This new paradigm escalates the potential of data analytics on top of monitoring data, but, on the other hand, increases data quality issues related to anomalies in the acquisition process. This chapter presents the full data lifecycle in the safety control of large-scale civil engineering infrastructures (focused on dams), from the data acquisition process, data processing and storage, data quality and outlier detection, and data analysis. A strong focus is made on the use of machine learning techniques for data analysis, where the common multiple linear regression analysis is compared with deep learning strategies, namely recur- rent neural networks. Demonstration scenarios are presented based on data obtained from monitoring systems of concrete dams under operation in Portugal.info:eu-repo/semantics/acceptedVersio

    BigDL: A Distributed Deep Learning Framework for Big Data

    Full text link
    This paper presents BigDL (a distributed deep learning framework for Apache Spark), which has been used by a variety of users in the industry for building deep learning applications on production big data platforms. It allows deep learning applications to run on the Apache Hadoop/Spark cluster so as to directly process the production data, and as a part of the end-to-end data analysis pipeline for deployment and management. Unlike existing deep learning frameworks, BigDL implements distributed, data parallel training directly on top of the functional compute model (with copy-on-write and coarse-grained operations) of Spark. We also share real-world experience and "war stories" of users that have adopted BigDL to address their challenges(i.e., how to easily build end-to-end data analysis and deep learning pipelines for their production data).Comment: In ACM Symposium of Cloud Computing conference (SoCC) 201

    The stellar halo of the Galaxy

    Get PDF
    Stellar halos may hold some of the best preserved fossils of the formation history of galaxies. They are a natural product of the merging processes that probably take place during the assembly of a galaxy, and hence may well be the most ubiquitous component of galaxies, independently of their Hubble type. This review focuses on our current understanding of the spatial structure, the kinematics and chemistry of halo stars in the Milky Way. In recent years, we have experienced a change in paradigm thanks to the discovery of large amounts of substructure, especially in the outer halo. I discuss the implications of the currently available observational constraints and fold them into several possible formation scenarios. Unraveling the formation of the Galactic halo will be possible in the near future through a combination of large wide field photometric and spectroscopic surveys, and especially in the era of Gaia.Comment: 46 pages, 16 figures. References updated and some minor changes. Full-resolution version available at http://www.astro.rug.nl/~ahelmi/stellar-halo-review.pd

    Discreet element modeling of under sleeper pads using a box test

    Get PDF
    It has recently been reported that under sleeper pads (USPs) could improve ballasted rail track by decreasing the sleeper settlement and reducing particle breakage. In order to find out what happens at the particle-pad interface, discrete element modelling (DEM) is used to provide micro mechanical insight. The same positive effects of USP are found in the DEM simulations. The evidence provided by DEM shows that application of a USP allows more particles to be in contact with the pad, and causes these particles to transfer a larger lateral load to the adjacent ballast but a smaller vertical load beneath the sleeper. This could be used to explain why the USP helps to reduce the track settlement. In terms of particle breakage, it is found that most breakage occurs at the particle-sleeper interface and along the main contact force chains between particles under the sleeper. The use of USPs could effectively reduce particle abrasion that occurs in both of these regions

    Delayed Recovery of Skeletal Muscle Mass following Hindlimb Immobilization in mTOR Heterozygous Mice

    Get PDF
    The present study addressed the hypothesis that reducing mTOR, as seen in mTOR heterozygous (+/−) mice, would exaggerate the changes in protein synthesis and degradation observed during hindlimb immobilization as well as impair normal muscle regrowth during the recovery period. Atrophy was produced by unilateral hindlimb immobilization and data compared to the contralateral gastrocnemius. In wild-type (WT) mice, the gradual loss of muscle mass plateaued by day 7. This response was associated with a reduction in basal protein synthesis and development of leucine resistance. Proteasome activity was consistently elevated, but atrogin-1 and MuRF1 mRNAs were only transiently increased returning to basal values by day 7. When assessed 7 days after immobilization, the decreased muscle mass and protein synthesis and increased proteasome activity did not differ between WT and mTOR+/− mice. Moreover, the muscle inflammatory cytokine response did not differ between groups. After 10 days of recovery, WT mice showed no decrement in muscle mass, and this accretion resulted from a sustained increase in protein synthesis and a normalization of proteasome activity. In contrast, mTOR+/− mice failed to fully replete muscle mass at this time, a defect caused by the lack of a compensatory increase in protein synthesis. The delayed muscle regrowth of the previously immobilized muscle in the mTOR+/− mice was associated with a decreased raptor•4EBP1 and increased raptor•Deptor binding. Slowed regrowth was also associated with a sustained inflammatory response (e.g., increased TNFα and CD45 mRNA) during the recovery period and a failure of IGF-I to increase as in WT mice. These data suggest mTOR is relatively more important in regulating the accretion of muscle mass during recovery than the loss of muscle during the atrophy phase, and that protein synthesis is more sensitive than degradation to the reduction in mTOR during muscle regrowth
    corecore