{"48995":{"#nid":"48995","#data":{"type":"event","title":"Terror Queues","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETITLE:\u003C\/strong\u003E Terror Queues\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESPEAKER:\u003C\/strong\u003E Professor Edward Kaplan\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EABSTRACT:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThis article presents the first model developed\nspecifically for understanding the infiltration and interdiction of ongoing\nterror plots by undercover intelligence agents, and does so via novel\napplication of ideas from queueing theory and Markov population processes. The\nresulting \u0022terror queue\u0022 models predict the number of undetected\nterror threats in an area from agent activity\/utilization data, and also\nestimate the rate with which such threats can be interdicted.\u0026nbsp; The models\ntreat terror plots as customers and intelligence agents as servers. Agents\nspend all of their time either detecting and infiltrating new terror plots (in\nwhich case they are \u0022available\u0022), or interdicting already detected\nterror plots (in which case they are \u0022busy\u0022). Initially we examine a\nMarkov model assuming that intelligence agents, while unable to detect all\nplots, never err by falsely detecting fake plots.\u0026nbsp; While this model can be\nsolved numerically, a simpler Ornstein-Uhlenbeck diffusion approximation yields\nsome results in closed form while providing nearly identical numerical\nperformance.\u0026nbsp; The transient behavior of the terror queue model is\ndiscussed briefly along with a sample sensitivity analysis to study how model\npredictions compare to simulated results when using estimated versus known\nterror plot arrival rates. The diffusion model is then extended to allow for\nthe false detection of fake plots. Such false detection is a real feature of\ncounterterror intelligence given that intelligence agents or informants can\nmake mistakes, as well as the proclivity of terrorists to deliberately\nbroadcast false information. The false detection model is illustrated using\nsuicide bombing data from Israel.\n\n\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"Terror Queues","format":"limited_html"}],"field_summary_sentence":[{"value":"Terror Queues"}],"uid":"27187","created_gmt":"2010-01-19 10:15:21","changed_gmt":"2016-10-08 01:49:32","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2010-03-03T10:00:00-05:00","event_time_end":"2010-03-03T11:00:00-05:00","event_time_end_last":"2010-03-03T11:00:00-05:00","gmt_time_start":"2010-03-03 15:00:00","gmt_time_end":"2010-03-03 16:00:00","gmt_time_end_last":"2010-03-03 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[{"id":"5227","name":"Markov"},{"id":"8263","name":"terror"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}