PPT-Experience Report: System Log Analysis for Anomaly Detection

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Shilin He Jieming Zhu Pinjia He and Michael R Lyu Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong 20161026 Background

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Experience Report: System Log Analysis for Anomaly Detection: Transcript

Shilin He Jieming Zhu Pinjia He and Michael R Lyu Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong 20161026 Background amp Motivation. Jimeng. Sun, . Huiming. . Qu. , . Deepayan. . Chakrabarti. & Christos . Faloutsos. Presented By. Bhavana. . Dalvi. Outline. Motivation. Problem Definition. Neighborhood formation. Anomaly detection. Problem motivation. Machine Learning. Anomaly detection example. Aircraft engine features:. . = heat generated. = vibration intensity. …. (vibration). (heat). Dataset:. New engine:. Density estimation. &. 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. for . eRetailer Web application. Ramya Ramalinga Moorthy, . EliteSouls Consulting Services . Contents. Introduction . Need for Performance Anomaly Detection & Forecasting Models. ERetailer Problem Space Overview. DETECTION. Scholar: . Andrew . Emmott. Focus: . Machine Learning. Advisors: . Tom . Dietterich. , Prasad . Tadepalli. Donors: . Leslie and Mark Workman. Acknowledgements:. Funding for my research is . © 2015 Blueocean Market Intelligence. 1. Implemented real time anomaly detection system for a leading PC manufacturer globally(1/2). © 2015 Blueocean Market Intelligence. 2. Client: . Leading PC Manufacturer in the US. 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 . Vishwanath Saragadam . , Jian Wang, . Xin Li, . Aswin. . Sankaranarayanan. 1. Hyperspectral images. Information as a function of space and wavelength. Wavelength. Space. Data from . SpecTIR. 2. . 400nm. 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. Showcase by . Abhishek Shah, Mahdi Alouane. , Marie Solman. , Satishraju Rajendran and Eno-Obong Inyang. . Showcasing work by Cai Lile, Li Yiqun On. . ANOMALY DETECTION IN THERMAL IMAGES USING DEEP NEURAL NETWORKS. Project Lead: . Farokh. . Bastani. , I-Ling Yen, . Latifur. Khan. Date: April 7, 2011. 2010/Current Project Overview. Self-Detection of Abnormal Event Sequences. 2. Tasks:. Prepare Cisco event sequence data for analysis tools.. 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 , . Marek . Pawłowski. , Gerard . Frankowski. , . Marcin. . Jerzak. , . Maciej. . Miłostan. , Tomasz Nowak. Poznań. Supercomputing and Networking Center. Agenda. Introduction . System Architecture .

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