PPT-Anomaly detection of large scale distributed storage system based on machine learning

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Institute of High Energy Physics CAS Wang Lu LuWangihepaccn Agenda Introduction Challenges and requirements of anomaly detection in large scale storage systems

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Anomaly detection of large scale distributed storage system based on machine learning: Transcript

Institute of High Energy Physics CAS Wang Lu LuWangihepaccn Agenda Introduction Challenges and requirements of anomaly detection in large scale storage systems Definition and category of anomaly. 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. Intruders. WenZhan. Song. Cryptography and Network Security. 1. Intruders. Three classes of intruders:. Examples of Intrusion. Performing a remote root compromise of an e-mail server. Defacing a Web server. Jimmy Lin and Alek . Kolcz. Twitter, Inc.. Presented by: Yishuang Geng and Kexin Liu. 2. Outline. •Is twitter big data? . •How . can machine learning help twitter?. •Existing challenges?. •Existing literature of large-scale learning. Problem motivation. Machine Learning. Anomaly detection example. Aircraft engine features:. . = heat generated. = vibration intensity. …. (vibration). (heat). Dataset:. New engine:. Density estimation. Anomaly-based . Network Intrusion . Detection (A-NIDS). by Nitish Bahadur, Gulsher Kooner, . Caitlin Kuhlman. 1. PALANTIR CYBER An End-to-End Cyber Intelligence Platform for Analysis & Knowledge Management [Online]. Available: . &. 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. Scholar: . Andrew . Emmott. Focus: . Machine Learning. Advisors: . Tom . Dietterich. , Prasad . Tadepalli. Donors: . Leslie and Mark Workman. Acknowledgements:. Funding for my research is . Madan Musuvathi. . Visiting Professor, UCLA . Principal Researcher, Microsoft Research. Course Project. Write-ups due June 1. st. Project presentations . 12 presentations, 10 mins each, 15 min slack. 9. Introduction to Data Mining, . 2. nd. Edition. by. Tan. , Steinbach, Karpatne, . Kumar. With additional slides and modifications by Carolina Ruiz, WPI. 11/20/2018. Introduction to Data Mining, 2nd Edition. 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. “Anomaly Detection: A Tutorial”. Arindam. . Banerjee. , . Varun. . Chandola. , . Vipin. Kumar, Jaideep . Srivastava. , . University of Minnesota. Aleksandar. . Lazarevic. , . United Technology Research Center. 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. Yonggang Cui. 1. , Zoe N. Gastelum. 2. , Ray Ren. 1. , Michael R. Smith. 2. , . Yuewei. Lin. 1. , Maikael A. Thomas. 2. , . Shinjae. Yoo. 1. , Warren Stern. 1. 1 . Brookhaven National Laboratory, Upton, USA.

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