47 research outputs found
Tiresias: Predicting Security Events Through Deep Learning
With the increased complexity of modern computer attacks, there is a need for
defenders not only to detect malicious activity as it happens, but also to
predict the specific steps that will be taken by an adversary when performing
an attack. However this is still an open research problem, and previous
research in predicting malicious events only looked at binary outcomes (e.g.,
whether an attack would happen or not), but not at the specific steps that an
attacker would undertake. To fill this gap we present Tiresias, a system that
leverages Recurrent Neural Networks (RNNs) to predict future events on a
machine, based on previous observations. We test Tiresias on a dataset of 3.4
billion security events collected from a commercial intrusion prevention
system, and show that our approach is effective in predicting the next event
that will occur on a machine with a precision of up to 0.93. We also show that
the models learned by Tiresias are reasonably stable over time, and provide a
mechanism that can identify sudden drops in precision and trigger a retraining
of the system. Finally, we show that the long-term memory typical of RNNs is
key in performing event prediction, rendering simpler methods not up to the
task
Tiresias: Predicting Security Events Through Deep Learning
With the increased complexity of modern computer attacks, there is a need for defenders not only to detect malicious activity as it happens, but also to predict the specific steps that will be taken by an adversary when performing an attack. However this is still an open research problem, and previous research in predicting malicious events only looked at binary outcomes (eg. whether an attack would happen or not), but not at the specific steps that an attacker would undertake. To fill this gap we present Tiresias xspace, a system that leverages Recurrent Neural Networks (RNNs) to predict future events on a machine, based on previous observations. We test Tiresias xspace on a dataset of 3.4 billion security events collected from a commercial intrusion prevention system, and show that our approach is effective in predicting the next event that will occur on a machine with a precision of up to 0.93. We also show that the models learned by Tiresias xspace are reasonably stable over time, and provide a mechanism that can identify sudden drops in precision and trigger a retraining of the system. Finally, we show that the long-term memory typical of RNNs is key in performing event prediction, rendering simpler methods not up to the task
Implementation and testing of the first prompt search for gravitational wave transients with electromagnetic counterparts
Aims. A transient astrophysical event observed in both gravitational wave
(GW) and electromagnetic (EM) channels would yield rich scientific rewards. A
first program initiating EM follow-ups to possible transient GW events has been
developed and exercised by the LIGO and Virgo community in association with
several partners. In this paper, we describe and evaluate the methods used to
promptly identify and localize GW event candidates and to request images of
targeted sky locations.
Methods. During two observing periods (Dec 17 2009 to Jan 8 2010 and Sep 2 to
Oct 20 2010), a low-latency analysis pipeline was used to identify GW event
candidates and to reconstruct maps of possible sky locations. A catalog of
nearby galaxies and Milky Way globular clusters was used to select the most
promising sky positions to be imaged, and this directional information was
delivered to EM observatories with time lags of about thirty minutes. A Monte
Carlo simulation has been used to evaluate the low-latency GW pipeline's
ability to reconstruct source positions correctly.
Results. For signals near the detection threshold, our low-latency algorithms
often localized simulated GW burst signals to tens of square degrees, while
neutron star/neutron star inspirals and neutron star/black hole inspirals were
localized to a few hundred square degrees. Localization precision improves for
moderately stronger signals. The correct sky location of signals well above
threshold and originating from nearby galaxies may be observed with ~50% or
better probability with a few pointings of wide-field telescopes.Comment: 17 pages. This version (v2) includes two tables and 1 section not
included in v1. Accepted for publication in Astronomy & Astrophysic
Hydrogen Storage Materials for Mobile and Stationary Applications: Current State of the Art
One of the limitations to the widespread use of hydrogen as an energy carrier is its storage in a safe and compact form. Herein, recent developments in effective high-capacity hydrogen storage materials are reviewed, with a special emphasis on light compounds, including those based on organic porous structures, boron, nitrogen, and aluminum. These elements and their related compounds hold the promise of high, reversible, and practical hydrogen storage capacity for mobile applications, including vehicles and portable power equipment, but also for the large scale and distributed storage of energy for stationary applications. Current understanding of the fundamental principles that govern the interaction of hydrogen with these light compounds is summarized, as well as basic strategies to meet practical targets of hydrogen uptake and release. The limitation of these strategies and current understanding is also discussed and new directions proposed
First searches for optical counterparts to gravitational-wave candidate events
During the Laser Interferometer Gravitational-wave Observatory and Virgo joint science runs in 2009-2010, gravitational wave (GW) data from three interferometer detectors were analyzed within minutes to select GW candidate events and infer their apparent sky positions. Target coordinates were transmitted to several telescopes for follow-up observations aimed at the detection of an associated optical transient. Images were obtained for eight such GW candidates. We present the methods used to analyze the image data as well as the transient search results. No optical transient was identified with a convincing association with any of these candidates, and none of the GW triggers showed strong evidence for being astrophysical in nature. We compare the sensitivities of these observations to several model light curves from possible sources of interest, and discuss prospects for future joint GW-optical observations of this type