ATTACK2VEC: Leveraging Temporal Word Embeddings to Understand the Evolution of Cyberattacks

Despite the fact that cyberattacks are constantly growing in complexity, the research community still lacks effective tools to easily monitor and understand them. In particular, there is a need for techniques that are able to not only track how prominently certain malicious actions, such as the exploitation of specific vulnerabilities, are exploited in the wild, but also (and more importantly) how these malicious actions factor in as attack steps in more complex cyberattacks. In this paper we present ATTACK2VEC, a system that uses temporal word embeddings to model how attack steps are exploited in the wild, and track how they evolve. We test ATTACK2VEC on a dataset of billions of security events collected from the customers of a commercial Intrusion Prevention System over a period of two years, and show that our approach is effective in monitoring the emergence of new attack strategies in the wild and in flagging which attack steps are often used together by attackers (e.g., vulnerabilities that are frequently exploited together). ATTACK2VEC provides a useful tool for researchers and practitioners to better understand cyberattacks and their evolution, and use this knowledge to improve situational awareness and develop proactive defenses

Cascade and anti-Cascade Polarization Measurements at 800 GeV/c

The polarization of neutral Cascade and anti-Cascade hyperons produced by 800 GeV/c protons on a BeO target at a fixed targeting angle of 4.8 mrad is measured by the KTeV experiment at Fermilab. Our result of 9.7% for the neutral Cascade polarization shows no significant energy dependence when compared to a result obtained at 400 GeV/c production energy and at twice our targeting angle. The polarization of the neutral anti-Cascade is measured for the first time and found to be consistent with zero. We also examine the dependence of polarization on transverse production momentum.Comment: 4 page PR

Self-normalizing phase measurement in multimode terahertz spectroscopy based on photomixing of three lasers

Photomixing of two near-infrared lasers is well established for continuous-wave terahertz spectroscopy. Photomixing of three lasers allows us to measure at three terahertz frequencies simultaneously. Similar to Fourier spectroscopy, the spectral information is contained in an nterferogram, which is equivalent to the waveform in time-domain spectroscopy. We use one fixed terahertz frequency \nu_ref to monitor temporal drifts of the setup, i.e., of the optical path-length difference. The other two frequencies are scanned for broadband high-resolution spectroscopy. The frequency dependence of the phase is obtained with high accuracy by normalizing it to the data obtained at \nu_ref, which eliminates drifts of the optical path-length difference. We achieve an accuracy of about 1-2 microns or 10^{-8} of the optical path length. This method is particularly suitable for applications in nonideal environmental conditions outside of an air-conditioned laboratory.Comment: 5 pages, 5 figure

Investigation of radiometric properties of the LANDSAT-4 multispectral scanner

The radiometric data quality of the LANDSAT 4 multispectral scanner (MSS) was examined using several LANDSAT 4 frames. It was found that LANDSAT 4 MSS produces high-quality data of the caliber experienced with previous LANDSATS. For example, the detector equalization procedure worked well, leaving a residual banding effect of about 0.3 digital counts RMS, close to the theoretical minimum value of quantization error. Nevertheless, artifacts of the data were found, two of which were not experienced in previous MSS data. A low-level coherent noise effect was observed in all bands, with a magnitude of about 0.5 digital counts and a frequency of approximately 28 KHz (representing a wavelength of about 3.6 pixels); a substantial increase in processing complexity would be required to reduce this artifact in the data. Also, a substantial scan-length variation (of up to six pixels) was noted in MSS data when the TM sensor was operating; the LANDSAT 4 correction algorithms being applied routinely by the EROS Data Center to produce a p-type data should remove most of this variation. Between-satellite calibrations were examined in paired LANDSAT 3 and LANDSAT 4 MSS data sets, which were closely matched in acquisition time and place. Radiometric comparisons showed that all bands were highly linear in digital counts, and a well-determined linear transformation between the MSS's was established

A machine learning route between band mapping and band structure

The electronic band structure (BS) of solid state materials imprints the multidimensional and multi-valued functional relations between energy and momenta of periodically confined electrons. Photoemission spectroscopy is a powerful tool for its comprehensive characterization. A common task in photoemission band mapping is to recover the underlying quasiparticle dispersion, which we call band structure reconstruction. Traditional methods often focus on specific regions of interests yet require extensive human oversight. To cope with the growing size and scale of photoemission data, we develop a generic machine-learning approach leveraging the information within electronic structure calculations for this task. We demonstrate its capability by reconstructing all fourteen valence bands of tungsten diselenide and validate the accuracy on various synthetic data. The reconstruction uncovers previously inaccessible momentum-space structural information on both global and local scales in conjunction with theory, while realizing a path towards integrating band mapping data into materials science databases

Measurement of B(/\c->pKpi)

The /\c->pKpi yield has been measured in a sample of two-jet continuum events containing a both an anticharm tag (Dbar) as well as an antiproton (e+e- -> Dbar pbar X), with the antiproton in the hemisphere opposite the Dbar. Under the hypothesis that such selection criteria tag e+e- -> Dbar pbar (/\c) X events, the /\c->pkpi branching fraction can be determined by measuring the pkpi yield in the same hemisphere as the antiprotons in our Dbar pbar X sample. Combining our results from three independent types of anticharm tags, we obtain B(/\c->pKpi)=(5.0+/-0.5+/-1.2)