Predicting the Structure of Covert Networks using Genetic Programming, Cognitive Work Analysis and Social Network Analysis

Created by W.Langdon from gp-bibliography.bib Revision:1.3838

@InProceedings{Baber:2009:MSG,
  author =       "C. Baber and N. Stanton and D. Howard and 
                 Robert J. Houghton",
  title =        "Predicting the Structure of Covert Networks using
                 Genetic Programming, Cognitive Work Analysis and Social
                 Network Analysis",
  booktitle =    "NATO RTO Modelling and Simulation Group Symposium",
  year =         "2009",
  editor =       "J. Ruiz",
  number =       "RTO-MP-MSG-069 AC/323(MSG-069)TP/297",
  pages =        "Paper 15",
  address =      "Brussels, Belgium",
  month =        "15-16 " # oct,
  organisation = "NATO Science and Technology Organization",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-92-837-0100-2",
  URL =          "http://ftp.rta.nato.int/public//PubFullText/RTO/MP/RTO-MP-MSG-069///MP-MSG-069-15.pdf",
  URL =          "http://ftp.rta.nato.int/public//PubFullText/RTO/MP/RTO-MP-MSG-069///MP-MSG-069-15.doc",
  size =         "14 pages",
  abstract =     "A significant challenge in intelligence analysis
                 involves knowing when a social network description is
                 complete, i.e., when sufficient connections have been
                 found to render the network complete. In this paper, a
                 combination of methods is used to predict covert
                 network structures for specific missions. The intention
                 is to support hypothesis-generation in the Social
                 Network Analysis of covert organisations. The project
                 employs a four phase approach to modelling social
                 networks, working from task descriptions rather than
                 from contacts between individual: phase one involves
                 the collation of intelligence covering types of
                 mission, in terms of actors and goals; phase two
                 involves the building of task models, based on
                 Cognitive Work Analysis, to provide both a process
                 model of the operation and an indication of the
                 constraints under which the operation will be
                 performed; phase three involves the generation of
                 alternative networks using Genetic Programming; phase
                 four involves the analysis of the resulting networks
                 using social network analysis. Subsequent analysis
                 explores the resilience of the networks, in terms of
                 their resistance to losses of agents or tasks. The
                 project demonstrates that it is possible to define a
                 set of structures that can be tackled using different
                 intervention strategies, demonstrates how patterns of
                 social network structures can be predicted on the basis
                 of task knowledge, and how these structures can be used
                 to guide the gathering of intelligence and to define
                 plausible Covert Networks.",
  notes =        "Cited by \cite{conf/ichit/HowardC12}

                 RTO-MP-MSG-069 - Current uses of M&S Covering Support
                 to Operations, Human Behaviour Representation,
                 Irregular Warfare, Defence against Terrorism and
                 Coalition Tactical Force Integration

                 Utilisation actuelle M&S couvrant le soutien aux
                 operations, la representation du comportement humain,
                 la guerre asymetrique, la defense contre le terrorisme
                 et l'integration d'une force tactique de
                 coalition

                 https://www.cso.nato.int/pubs/rdp.asp?RDP=RTO-MP-MSG-069",
}

Genetic Programming entries for Chris Baber Neville Stanton Daniel Howard Robert J Houghton

Citations