Shanghai / Anomaly / Bangkok / Xiamen / Emeriville / Boston / Ayia Napa / Anomal / New York / Nanchang / Riccione / Guangzhou / Quito / Wuhan / Shenzhen / Las Vegas / Menuires / Xi'an / Indianapolis / Kunming / San Diego / Coventry / /
Company
Computer Sciences / Intrusion Detection Systems / Cloud Computing Networks / McGraw-HIll / Pearson / CONDOR’s / toLibc Attacks Using Network Intrusion Detection Systems / International Digital Laboratory / Y.Y.Tan A.S. / /
Country
Ecuador / Italy / Cyprus / Thailand / France / United States / China / / /
Event
Force Majeure / /
Facility
Furnival Building / University of Warwick / Sheffield Hallam University / /
IndustryTerm
neural networks / data mining / e - business / Internet Episodes / software-based product / anomaly detection systems / important solution / neural network / window algorithm / applications/services / Internet Security / integrated anomaly server / detection solution / e - commerce / computing / above systems / security devices / /
Organization
Department of Informatics / d.day@shu.ac.uk National Polytechnic School / National Polytechnic School / University of Warwick / Sheffield Hallam University / National Secretariat of Higher Education / Science / Technology / and Innovation of Ecuador / /
Person
David J. Day / Guo-Song / Ryan Trost / Jane K. Brownlow / Zhi-Chao / Karen Gettman / Wei-Min / Denys A. Flores / Silva Fraga / /
Position
high administrator / author / correspondent / administrator / analyst / Attack Classification Using Feed-Forward / D.J. / /
CONDOR: A Hybrid IDS to Offer Improved Intrusion Detection DAY, David and FLORES, Denys Available from Sheffield Hallam University Research Archive (SHURA) at: http://shura.shu.ac.uk/5246/