PPT-Predicting zero-day software vulnerabilities through data m

Author : sherrill-nordquist | Published Date : 2016-08-09

Su Zhang Department of Computing and Information Science Kansas State University 1 Outline Motivation Related work Proposed approach Possible techniques Plan 2 Outline

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Predicting zero-day software vulnerabilities through data m: Transcript


Su Zhang Department of Computing and Information Science Kansas State University 1 Outline Motivation Related work Proposed approach Possible techniques Plan 2 Outline Motivation Related work. It also provides examples of NZEB energy targets from 64257ve European Member States Introduction The UK Government has committed to a challenging CO emissions reduction target for 2050 Europe too has implemented a number of Directives designed to m CS . 795/895. References. . Reference 1. Big List of Information Security Vulnerabilities, John . Spacey, 2011 . http://. simplicable.com/new/the-big-list-of-information-security-vulnerabilities. Reference 2. Top Ten Database Security Threats, . Reduce Risk and Cost. Jonathan . Trull. @. jonathantrull. CISO, . Qualys. Seth Corder . @. corderseth. Automation Specialist, BMC. The Great Divide. 2. DevOps. Security. 3. Attack-Defend Cycle (OODA Loop). Laura Guidry-Grimes, Georgetown University. Elizabeth Victor, USF & Georgetown University. FEMMSS Conference, 2012. Introduction. Vulnerabilities. Rejection of Kantian isolated ‘. willers. ’ account. . Kotian. . | Author, NSA IAM, CEH. Product . Line Manager | Next Generation Security Platforms. rohanrkotian. @hp.com. Next Generation Cyber Threats. Shining . the Light on the Industries' Best Kept. landscape. Nathaniel Husted . nhusted@Indiana.edu. Indiana University. Personal Introduction. PhD Candidate at Indiana University. Focus in “Security Informatics” from the School of Informatics and Computing. CS . 795/895. References. . Reference 1. Big List of Information Security Vulnerabilities, John . Spacey, 2011 . http://. simplicable.com/new/the-big-list-of-information-security-vulnerabilities. Reference 2. Top Ten Database Security Threats, . Su Zhang. Department of Computing and Information Science. Kansas State University. 1. Outline. Motivation.. Related work.. Proposed approach.. Possible techniques.. Plan.. 2. Outline. Motivation.. Related work.. CS . 795/895. References. . Reference 1. Big List of Information Security Vulnerabilities, John . Spacey, 2011 . http://. simplicable.com/new/the-big-list-of-information-security-vulnerabilities. Reference 2. Top Ten Database Security Threats, . Group 5:. Katie Hardman. Tom . Horley. Daniel Hyatt. Executive Summary. Data Description. Data Preparation and Exploration. Scatter Plots of Grade and Finished Area vs Sale Price. Decision Tree Rules to predict highest and lowest Sale Prices. Criterion-Related Validation. Regression & Correlation. What’s the difference between the two?. Significance . Testing. Type I and type II errors. Statistical power to reject the null. . Chapter 6 Predicting Future Performance. Criterion-Related Validation. Regression & Correlation. What’s the difference between the two?. Significance . Testing. Type I and type II errors. Statistical power to reject the null. . Chapter 6 Predicting Future Performance. for . Austin Energy Conference. (A funny thing happened on the way to utopia). April 13, 2017. Alex Athey, PhD. Emerging Security and Technology Group. Applied Research Laboratories. The University of Texas at Austin. The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand

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