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Sökning: hsv:(TEKNIK OCH TEKNOLOGIER) hsv:(Elektroteknik och elektronik) hsv:(Datorsystem) > Annan publikation

  • Resultat 1-10 av 103
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1.
  • Zhang, Kewei, et al. (författare)
  • Protecting GNSS Open Service-Navigation Message Authentication against Distance-Decreasing Attacks
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • As the security of global navigation satellite systems (GNSS) for civilian usage is increasingly important, navigation message authentication (NMA) significantly improves resilience to spoofing attacks. However, not all attacks can be effectively countered: a strong variant of replay/relay attacks, distance-decreasing (DD) attacks, can shorten pseudorange measurements, without manipulating the cryptographically protected navigation message, thus manipulating the position, velocity, and time solution undetected. First, we discuss how DD attacks can tamper with GNSS signals, demonstrating the attack effectiveness on a recorded Galileo signal. DD attacks might introduce bit errors to the forged signals, but the adversary can keep this error rate very low with proper attack parameter settings. Then, based on our mathematical model of the prompt correlator output of the tracking phase at the victim receiver, we find that the correlator output distribution changes in the presence of DD attacks. This leads us to apply hypothesis testing to detect DD attacks, notably a Goodness of Fit (GoF) test and a generalized likelihood ratio test (GLRT), depending on the victim’s knowledge on the DD attacks. Monte Carlo simulations are used to evaluate the detection probability and the receiver operating characteristic (ROC) curves for two tests, for different adversary configuration and noise settings. Then, we evaluate the effectiveness of the GoF and GLRT tests with a synthesized DD signal. Both tests can detect DD attacks with similar performance in high signal-to-noise ratio (SNR) environments. The GLRT detection probability is approximately 20% higher than that of the GoF test in low SNR environments.
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2.
  • Yin, Hang, et al. (författare)
  • Policy Learning with Embedded Koopman Optimal Control
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • Embedding an optimization process has been explored for imposing efficient and flexible policy structures. Existing work often build upon nonlinear optimization with explicitly unrolling of iteration steps, making policy inference prohibitively expensive for online learning and real-time control. Our approach embeds a linear-quadratic-regulator (LQR) formulation with a Koopman representation, thus exhibiting the tractability from a closed-form solution and richness from a non-convex neural network. We use a few auxiliary objectives and reparameterization to enforce optimality conditions of the policy that can be easily integrated to standard gradient-based learning. Our approach is shown to be effective for learning policies rendering an optimality structure and efficient reinforcement learning, including simulated pendulum control, 2D and 3D walking, and manipulation for both rigid and deformable objects. We also demonstrate real world application in a robot pivoting task.
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3.
  • Yanggratoke, Rerngvit, 1983-, et al. (författare)
  • A service-agnostic method for predicting service metrics in real-time
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • We predict performance metrics of cloud services using statistical learning, whereby the behavior of a system is learned from observations. Specifically, we collect device and network statistics from a cloud testbed and apply regression methods to predict, in real-time, client-side service metrics for video streaming and key-value store services. Our method is service agnostic in the sense that it takes as input operating-systems and network statistics instead of service-specific metrics. We show that feature set reduction significantly improves the prediction accuracy in our case, while simultaneously reducing model computation time. We find that the prediction accuracy decreases when, instead of a single service, both services run on the same testbed simultaneously or when the network quality on the path between the server cluster and the client deteriorates. Finally, we discuss the design and implementation of a real-time analytics engine, which processes streams of device statistics and service metrics from testbed sensors and produces model predictions through online learning.
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  • Farshin, Alireza, 1992-, et al. (författare)
  • Scheduling - A Secret Sauce For Resource Disaggregation
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • This technical report describes the design & implementation of a constraint-based framework for scheduling & resource allocation in a disaggregated data center (DDC) where we build logical servers from disaggregated resources. We show that an Service LevelObjective (SLO)-aware constraint-based solver could improve a data center’s resource utilization by finding better solutions based on provided workload characteristics.
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  • Resultat 1-10 av 103
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