2021 Systems and Information Engineering Design Symposium (SIEDS)最新文献_第9页

Scoring Cyber Vulnerabilities based on Their Impact on Organizational Goals* 基于对组织目标影响的网络漏洞评分*

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483741

O. Keskin, Nick Gannon, B. Lopez, Unal Tatar

{"title":"Scoring Cyber Vulnerabilities based on Their Impact on Organizational Goals*","authors":"O. Keskin, Nick Gannon, B. Lopez, Unal Tatar","doi":"10.1109/SIEDS52267.2021.9483741","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483741","url":null,"abstract":"Vulnerability Management, which is a vital part of risk and resiliency management efforts, is a continuous process of identifying, classifying, prioritizing, and removing vulnerabilities on devices that are likely to be used by attackers to compromise a network component. For effective and efficient vulnerability management, which requires extensive resources– such as time and personnel, vulnerabilities should be prioritized based on their criticality. One of the most common methods to prioritize vulnerabilities is the Common Vulnerability Scoring System (CVSS). However, in its severity score, the National Institute of Standards and Technology (NIST) only provides the base metric values that include exploitability and impact information for the known vulnerabilities and acknowledges the importance of temporal and environmental characteristics to have a more accurate vulnerability assessment. There is no established method to conduct the integration of these metrics. In this study, we created a testbed to assess the vulnerabilities by considering the functional dependencies between vulnerable assets, other assets, and business processes. The experiment results revealed that a vulnerability’s severity significantly changes from its CVSS base score when the vulnerable asset’s characteristics and role inside the organization are considered.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"72 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114314937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Data Mining of Rare Alleles to Assess Biogeographic Ancestry 稀有等位基因数据挖掘在生物地理祖先评估中的应用

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483709

Colleen M. Callahan, Holden Bridge

{"title":"Data Mining of Rare Alleles to Assess Biogeographic Ancestry","authors":"Colleen M. Callahan, Holden Bridge","doi":"10.1109/SIEDS52267.2021.9483709","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483709","url":null,"abstract":"The United States Department of Defense (DoD) routinely seeks more efficient ways to examine genetic data applied to cases of foreign or domestic crime. The process of identifying biogeographic ancestry groups using forensic DNA data to provide investigative leads is currently performed on Single Nucleotide Polymorphisms (SNP). The motivation for this project was to determine whether SNP assessment of biogeographic ancestry can be replicated using analysis of autosomal Short Tandem Repeats (STR) while preserving predictive accuracy. Replacing SNP analysis with STR analysis is theoretically more efficient. STR data can be generated from a significantly smaller amount of DNA. Additionally, readily available genetic data can be analyzed well after collection. Moreover, in contrast to SNP analysis, STR analysis is more cost effective per sample. Several considerations for this paper were necessary: 1) Whether or not STR profiles at 24 loci can be distinguished into distinct clusters using microvariants and off-ladder alleles. 2) Given that there is identifiable clustering, whether or not these clusters can be probabilistically identified as members biogeographic ancestry groups. STR profiles consisting of 24 loci from N=2,348 subjects were analyzed. The present analysis employed multidimensional scaling (MDS), which provides a measure of dissimilarity between STR profiles and reduces the tabular profiles into two latent dimensions. Using the scaled MDS coordinates, a Gaussian Mixture Model (GMM) was constructed which provides probabilities of belongingness for every data point to each cluster. Results from the model indicated separations between certain biogeographic ancestry groups with the probabilities generated from the GMM providing a posteriori confidence levels for group membership. Such analyses may be of benefit for efforts in future crime investigation where biogeographic ancestry identification is needed.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116358278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Incorporating Supply Chain Design into the Engineering Product Design Phase 将供应链设计纳入工程产品设计阶段

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483770

Kundan Paudyal, C. MacKenzie

引用次数: 0

A Comprehensive COVID-19 Database for the United States 美国COVID-19综合数据库

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483754

Gunnar Sundberg, Bayazit Karaman

{"title":"A Comprehensive COVID-19 Database for the United States","authors":"Gunnar Sundberg, Bayazit Karaman","doi":"10.1109/SIEDS52267.2021.9483754","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483754","url":null,"abstract":"The diversity in responses to and conditions resulting from the COVID-19 pandemic in the United States has provided rich data for researchers to study, especially as the pandemic continues to progress. With more than a full year of data available in different regions and at different granularities, methods of analysis requiring larger datasets are now worth examining or refining. Furthermore, as the United States seeks to move away from national and state-wide policies into approaches focused on individual communities, open data must be provided at both the state and county levels. In this paper, a comprehensive database encompassing COVID-19 data and a large body of related data is proposed. The database includes data on cases and deaths, testing, mobility, demographics, weather, and more at both the US state and county levels. The system was implemented using the Python framework Django and the high-performance RDBMS PostgreSQL. A data-processing pipeline was implemented using the asynchronous task library Celery to gather and clean data from various verified sources. This database has been used to build a web application for concise reporting and an open API for public access to the data. A reference web application using the API is currently available at www.bigdatacovid.com, and the API is available at www.bigdatacovid.com/api/v1, with API documentation available on the website.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127671887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Output Random Forest Regression to Emulate the Earliest Stages of Planet Formation 模拟行星形成早期阶段的多输出随机森林回归

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-26 DOI: 10.1109/SIEDS52267.2021.9483749

Kevin Hoffman, Jae Yoon Sung, Andr'e Zazzera

{"title":"Multi-Output Random Forest Regression to Emulate the Earliest Stages of Planet Formation","authors":"Kevin Hoffman, Jae Yoon Sung, Andr'e Zazzera","doi":"10.1109/SIEDS52267.2021.9483749","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483749","url":null,"abstract":"In the current paradigm of planet formation re-search, it is believed that the first step to forming massive bodies (such as asteroids and planets) requires that small interstellar dust grains floating through space collide with each other and grow to larger sizes. The initial formation of these pebbles is governed by an integro-differential equation known as the Smoluchowski coagulation equation [1], to which analytical solutions are intractable for all but the simplest possible scenarios. While brute-force methods of approximation have been developed, they are computationally costly, currently making it infeasible to simulate this process including other physical processes relevant to planet formation, and across the very large range of scales on which it occurs. In this paper, we take a machine learning approach to designing a system for a much faster approximation. We develop a multi-output random forest regression model trained on brute-force simulation data to approximate distributions of dust particle sizes in protoplanetary disks at different points in time. The performance of our random forest model is measured against the existing brute-force models, which are the standard for realistic simulations. Results indicate that the random forest model can generate highly accurate predictions relative to the brute-force simulation results, with an R2 of 0.97, and do so significantly faster than brute-force methods.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116194724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Program: 2021 Systems and Information Engineering Design Symposium (SIEDS) - Table of contents 项目:2021系统与信息工程设计研讨会(SIEDS) -目录表

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 1900-01-01 DOI: 10.1109/sieds52267.2021.9483765

引用次数: 0