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Creators/Authors contains: "Yang, S."

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  1. ; ; ; ; ; ; ; ; ; ; et al ( , The Astrophysical Journal)
    Abstract We present a comprehensive analysis of 653 optical candidate counterparts reported during the third gravitational-wave (GW) observing run. Our sample concentrates on candidates from the 15 events (published in GWTC-2, GWTC-3, or not retracted on GraceDB) that had a >1% chance of including a neutron star in order to assess their viability as true kilonovae. In particular, we leverage tools available in real time, including pre-merger detections and cross-matching with catalogs (i.e., point-source, variable-star, quasar and host-galaxy redshift data sets), to eliminate 65% of candidates in our sample. We further employ spectroscopic classifications, late-time detections, and light-curve behavior analysesmore »and conclude that 66 candidates remain viable kilonovae. These candidates lack sufficient information to determine their classifications, and the majority would require luminosities greater than that of AT 2017gfo. Pre-merger detections in public photometric survey data and comparison of cataloged host-galaxy redshifts with the GW event distances are critical to incorporate into vetting procedures, as these tools eliminated >20% and >30% of candidates, respectively. We expect that such tools that leverage archival information will significantly reduce the strain on spectroscopic and photometric follow-up resources in future observing runs. Finally, we discuss the critical role prompt updates from GW astronomers to the EM community play in reducing the number of candidates requiring vetting.« less
    Free, publicly-accessible full text available March 1, 2023
  2. ; ; ( , SIGKDD explorations)
    Free, publicly-accessible full text available June 30, 2022
  3. ; ; ( , ACM Knowledge Discovery and Data Mining (KDD))
    Accepted Manuscript Full Text Available
  4. ; ; ; ; ; ; ; ; ( , Physical Review X)
    null (Ed.)
    Full Text Available 
  5. ; ; ; ( , Proceedings of IEEE/ACM DS-RT 2020)
    Recognizing the need for proactive analysis of cyber adversary behavior, this paper presents a new event-driven simulation model and implementation to reveal the efforts needed by attackers who have various entry points into a network. Unlike previous models which focus on the impact of attackers’ actions on the defender’s infrastructure, this work focuses on the attackers’ strategies and actions. By operating on a request-response session level, our model provides an abstraction of how the network infrastructure reacts to access credentials the adversary might have obtained through a variety of strategies. We present the current capabilities of the simulator by showingmore »three variants of Bronze Butler APT on a network with different user access levels.« less
    Accepted Manuscript Full Text Available
  6. ; ; ( , Proceedings of 2020 International Conference on Availability, Reliability and Security (ARES))
    Cyber situational awareness is an essential part of cyber defense that allows the cybersecurity operators to cope with the complexity of today’s networks and threat landscape. Perceiving and comprehending the situation allow the operator to project upcoming events and make strategic decisions. In this paper, we recapitulate the fundamentals of cyber situational awareness and highlight its unique characteristics in comparison to generic situational awareness known from other fields. Subsequently, we provide an overview of existing research and trends in publishing on the topic, introduce front research groups, and highlight the impact of cyber situational awareness research. Further, we propose anmore »updated taxonomy and enumeration of the components used for achieving cyber situational awareness. The updated taxonomy conforms to the widely-accepted three-level definition of cyber situational awareness and newly includes the projection level. Finally, we identify and discuss contemporary research and operational challenges, such as the need to cope with rising volume, velocity, and variety of cybersecurity data and the need to provide cybersecurity operators with the right data at the right time and increase their value through visualization.« less
    Accepted Manuscript Full Text Available
  7. ; ; ; ; ( , Eleventh International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures (AMDS'20))
    RDMA has been an important building block for many high-performance distributed key-value stores in recent prior work. To sustain millions of operations per second per node, many of these works use hashing schemes, such as cuckoo hashing, that guarantee that an existing key can be found in a small, constant number of RDMA operations. In this paper, we explore whether linear probing is a compelling design alternative to cuckoo-based hashing schemes. Instead of reading a fixed number of bytes per RDMA request, this paper introduces a mathematical model that picks the optimal read size by balancing the cost of performingmore »an RDMA operation with the probability of encountering a probe sequence of a certain length. The model can further leverage optimization hints about the location of clusters of keys, which commonly occur in skewed key distributions. We extensively evaluate the performance of linear probing with a variable read size in a modern cluster to understand the trade-offs between cuckoo hashing and linear probing. We find that cuckoo hashing outperforms linear probing only in very highly loaded hash tables (load factors at 90% or higher) that would be prohibitively expensive to maintain in practice. Overall, linear probing with variable-sized reads using our model has up to 2.8× higher throughput than cuckoo hashing, with throughput as high as 50M lookup operations per second per node.« less
    Accepted Manuscript Full Text Available
  8. ; ; ; ; ; ( , Proceedings of The 6th ACM International Workshop on Security and Privacy Analytics, co-located with ACM Codaspy)
    Advanced Persistent Threats (APTs) are professional, sophisticated threats that pose a serious concern to our technologically-dependent society. As these threats become more common, conventional response-driven cyberattack management needs to be substituted with anticipatory defense measures. Understanding adversarial behavior and movement is critical to improve our ability to proactively defend. This paper focuses on understanding adversarial movement and adaptation using a case study from a real-time cybersecurity exercise. Through multidisciplinary methodologies from social and hard sciences, this paper presents a mechanism to dissect cyberadversarial intrusion chains to unpack movement, and adaptations.
    Accepted Manuscript Full Text Available
  9. ; ; ; ; ; ; ; ; ; ; et al ( , Astronomy & Astrophysics)
    Context. We present observations of ZTF20aatqesi (SN 2020faa). This Type II supernova (SN) displays a luminous light curve (LC) that started to rebrighten from an initial decline. We investigate this in relation to the famous SN iPTF14hls, which received a great deal of attention and multiple interpretations in the literature, but whose nature and source of energy still remain unknown. Aims. We demonstrate the great similarity between SN 2020faa and iPTF14hls during the first 6 months, and use this comparison to forecast the evolution of SN 2020faa and to reflect on the less well observed early evolution of iPTF14hls. Methods.more »We present and analyse our observational data, consisting mainly of optical LCs from the Zwicky Transient Facility in the gri bands and of a sequence of optical spectra. We construct colour curves and a bolometric lc, and we compare ejecta-velocity and black-body radius evolutions for the two supernovae (SNe) and for more typical Type II SNe. Results. The LCs show a great similarity with those of iPTF14hls over the first 6 months in luminosity, timescale, and colour. In addition, the spectral evolution of SN 2020faa is that of a Type II SN, although it probes earlier epochs than those available for iPTF14hls. Conclusions. The similar LC behaviour is suggestive of SN 2020faa being a new iPTF14hls. We present these observations now to advocate follow-up observations, since most of the more striking evolution of SN iPTF14hls came later, with LC undulations and a spectacular longevity. On the other hand, for SN 2020faa we have better constraints on the explosion epoch than we had for iPTF14hls, and we have been able to spectroscopically monitor it from earlier phases than was done for the more famous sibling.« less
    Full Text Available 
  10. ; ; ; ; ; ; ; ; ; ; et al ( , Computing and Software for Big Science)
    Abstract The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hardmore »scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.« less
    Free, publicly-accessible full text available December 1, 2023