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Free, publicly-accessible full text available October 1, 2023
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Black hat hackers use malicious exploits to circumvent security controls and take advantage of system vulnerabilities worldwide, costing the global economy over $450 billion annually. While many organizations are increasingly turning to cyber threat intelligence (CTI) to help prioritize their vulnerabilities, extant CTI processes are often criticized as being reactive to known exploits. One promising data source that can help develop proactive CTI is the vast and ever-evolving Dark Web. In this study, we adopted the computational design science paradigm to design a novel deep learning (DL)-based exploit-vulnerability attention deep structured semantic model (EVA-DSSM) that includes bidirectional processing and attentionmore »Free, publicly-accessible full text available June 1, 2023
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Marc Peter Deisenroth (Ed.)Free, publicly-accessible full text available January 1, 2023
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Semiconductors with O(meV) band gaps have been shown to be promising targets to search for sub-MeV mass dark matter (DM). In this paper we focus on a class of materials where such narrow band gaps arise naturally as a consequence of spin-orbit coupling (SOC). Specifically, we are interested in computing DM-electron scattering and absorption rates in these materials using state- of-the-art density functional theory (DFT) techniques. To do this, we extend the DM interaction rate calculation to include SOC effects which necessitates a generalization to spin-dependent wave functions. We apply our new formalism to calculate limits for several DM benchmarkmore »Free, publicly-accessible full text available February 1, 2023
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Free, publicly-accessible full text available December 1, 2022
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Free, publicly-accessible full text available January 1, 2023
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Cybercrime was estimated to cost the global economy $945 billion in 2020. Increasingly, law enforcement agencies are using social network analysis (SNA) to identify key hackers from Dark Web hacker forums for targeted investigations. However, past approaches have primarily focused on analyzing key hackers at a single point in time and use a hacker’s structural features only. In this study, we propose a novel Hacker Evolution Identification Framework to identify how hackers evolve within hacker forums. The proposed framework has two novelties in its design. First, the framework captures features such as user statistics, node-level metrics, lexical measures, and postmore »Free, publicly-accessible full text available November 1, 2022
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Free, publicly-accessible full text available November 1, 2022
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Despite significant contributions to various aspects of cybersecurity, cyber-attacks remain on the unfortunate rise. Increasingly, internationally recognized entities such as the National Science Foundation and National Science & Technology Council have noted Artificial Intelligence can help analyze billions of log files, Dark Web data, malware, and other data sources to help execute fundamental cybersecurity tasks. Our objective for the 1st Workshop on Artificial Intelligence-enabled Cybersecurity Analytics (half-day; co-located with ACM KDD) was to gather academic and practitioners to contribute recent work pertaining to AI-enabled cybersecurity analytics. We composed an outstanding, inter-disciplinary Program Committee with significant expertise in various aspects ofmore »