PPT-Anomaly Detection Lecture Notes for Chapter
Author : pasty-toler | Published Date : 2018-11-23
9 Introduction to Data Mining 2 nd Edition by Tan Steinbach Karpatne Kumar With additional slides and modifications by Carolina Ruiz WPI 11202018 Introduction
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Anomaly Detection Lecture Notes for Chapter: Transcript
9 Introduction to Data Mining 2 nd Edition by Tan Steinbach Karpatne Kumar With additional slides and modifications by Carolina Ruiz WPI 11202018 Introduction to Data Mining 2nd Edition. And 57375en 57375ere Were None meets the standard for Range of Reading and Level of Text Complexity for grade 8 Its structure pacing and universal appeal make it an appropriate reading choice for reluctant readers 57375e book also o57373ers students -. Traffic Video Surveillance. Ziming. Zhang, . Yucheng. Zhao and . Yiwen. Wan. Outline. Introduction. &Motivation. Problem Statement. Paper Summeries. Discussion and Conclusions. What are . Anomalies?. Introduction and Use Cases. Derick . Winkworth. , Ed Henry and David Meyer. Agenda. Introduction and a Bit of History. So What Are Anomalies?. Anomaly Detection Schemes. Use Cases. Current Events. Q&A. Machine Learning . Techniques. www.aquaticinformatics.com | . 1. Touraj. . Farahmand. - . Aquatic Informatics Inc. . Kevin Swersky - . Aquatic Informatics Inc. . Nando. de . Freitas. - . Department of Computer Science – Machine Learning University of British Columbia (UBC) . Craig Buchanan. University of Illinois at Urbana-Champaign. CS 598 MCC. 4/30/13. Outline. K-Nearest Neighbor. Neural Networks. Support Vector Machines. Lightweight Network Intrusion Detection (LNID). &. Intrusion . Detection Systems. 1. Intruders. Three classes of intruders:. Examples of Intrusion. Performing a remote root compromise of an e-mail server. Defacing a Web server. Guessing and cracking passwords. Detection. Carolina . Ruiz. Department of Computer Science. WPI. Slides based on . Chapter 10 of. “Introduction to Data Mining”. textbook . by Tan, Steinbach, Kumar. (all figures and some slides taken from this chapter. System Log Analysis for Anomaly Detection. Shilin . He. ,. . Jieming. Zhu, . Pinjia. . He,. and Michael R. . Lyu. Department of Computer Science and Engineering, . The Chinese University of Hong Kong, Hong . Nathalie . Japkowicz. , Colin . Bellinger. , . Shiven. Sharma, Rodney Berg, Kurt . Ungar. . University of Ottawa, Northern Illinois University. Radiation Protection Bureau, Health Canada. Yasin. Yilmaz, . Mahsa. Mozaffari. Secure and Intelligent Systems Lab. sis.eng.usf.edu. Department of Electrical Engineering. University of South Florida, Tampa, FL. S. u. leyman. . Uluda. g. Department of . Shilin . He. ,. . Jieming. Zhu, . Pinjia. . He,. and Michael R. . Lyu. Department of Computer Science and Engineering, . The Chinese University of Hong Kong, Hong Kong. 2016/10/26. Background & Motivation. 14. . World-Leading Research with Real-World Impact!. CS 5323. Outline. Anomaly detection. Facts and figures. Application. Challenges. Classification. Anomaly in Wireless. . 2. Recent News. Hacking of Government Computers Exposed 21.5 Million People. Authors. Bo Sun, Fei Yu, Kui Wu, Yang Xiao, and Victor C. M. Leung.. . Presented by . Aniruddha Barapatre. Introduction. Importance of Cellular phones.. Due to the open radio transmission environment and the physical vulnerability of mobile devices , . Institute of High Energy Physics, CAS. Wang Lu (Lu.Wang@ihep.ac.cn). Agenda. Introduction. Challenges and requirements of anomaly detection in large scale storage systems . Definition and category of anomaly.
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