31 research outputs found
Securing the Human: Broadening Diversity in Cybersecurity
Get PDFRecent global demand for cybersecurity professionals is promising, with the U.S. job growth rate at 28%, three times the national average [1]. Lacking qualified applicants, many organizations struggle to fill open positions [2]. In a global survey, 2,300 security managers reported that 59% of their security positions were unfilled, although 82% anticipated cyberattacks to their systems [3]. At the same time, the cybersecurity field is broadening, not only in technical concepts but also in human factors, business processes, and international law. The field has not become culturally diversified, however. Professionals hired in 2018 included only 24.9% women, 12.3% African Americans, and 6.8% Latinos [4]. These facts create an opportunity for higher education: diversify the profession while increasing the numbers of skilled computer scientists. New and integrated methods of attracting student populations in the field of cybersecurity are needed. The working group goal is to evaluate the effectiveness of approaches used in higher education to diversify the cybersecurity field through literature review, analysis of the findings, and a surve
Processing of Ice Cloud In-Situ Data Collected by Bulk Water, Scattering, and Imaging Probes: Fundamentals, Uncertainties and Efforts towards Consistency
Get PDFIn-situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in-situ data collected during different field projects processed by different groups must be used. However, due to the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in-situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single particle light scattering spectrometers and cloud imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in-situ data include the following: establishment of a common reference library of individual processing algorithms; better documentation of assumptions used in these algorithms; development and maintenance of sustainable community software for processing in-situ observations; and more studies that compare different algorithms with the same benchmark data sets
