PPT-Project Aim To model a Rogue Base Station (RBS) identification system based on anomaly-based

Secure Realtime Communications over 5G PhD Researcher Name Mohammad Saedi Supervisors Adrian Moore Christopher Nugent Philip Perry Contribution to Knowledge To create a data set that . Anomaly Detection for. Cyber Security. Presentation by Mike Calder . Anomaly Detection. Used for cyber security. Detecting threats using network data. Detecting threats using host-based data. In some domains, anomalies are detected so that they can be removed/corrected. 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. James Towers. Object Flow Ltd. Chair INCOSE UK MBSE Working Group. The 3 Evils . (from Holt & Perry). 1 – A Lack of Understanding. . (Unknown Unknowns). Applies to both individuals and organisations (projects). Using Software and System Cost Models. Anca-Juliana Stoica, IT Dept, UU. 26th International Forum on COCOMO and Systems/Software Cost Modeling. University of Southern California, Los Angeles, CA. November 2-4, 2011. Presented by Richard Brockway. Christine Wireless, Inc.. Internet-Protocol Connected System. Benefits of IP Based Systems. Interoperability (frequency bands, manufacturers, technologies). Scalability-Very small through very large systems. Presented . by. Jeff . Bibeau. , Max Levine, . Jie. . Gao. Showcasing Work . by. . Milos . Hauskrecht. , . Iyad. . Batal. , Michal . Valko. , . Shyam. . Visweswaran. ,. Gregory F. Cooper, Gilles Clermont.. Presented by Richard Brockway. Christine Wireless, Inc.. Internet-Protocol Connected System. Benefits of IP Based Systems. Interoperability (frequency bands, manufacturers, technologies). Scalability-Very small through very large systems. 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 . Defining probability-based rail station catchments for demand modelling. Marcus Young PhD student, Transportation Research Group 7 January 2016 2 Outline Research background Developing a station choice model 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. 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. E2E Security . Auditing and . Enforcement . in Trusted and Untrusted SOA. Northrop Grumman Cybersecurity. Research Consortium (NGCRC). Spring 2015 Symposium. 29/30 April 2015. PI: Prof. Bharat Bhargava.