Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Forecasting Violent Extremist Cyber Recruitment

Published: 01 November 2015 Publication History
  • Get Citation Alerts
  • Abstract

    The Internet's increasing use as a means of communication has led to the formation of cyber communities, which have become appealing to violent extremist (VE) groups. This paper presents research on forecasting the daily level of cyber-recruitment activity of VE groups. We used a previously developed support vector machine model to identify recruitment posts within a Western jihadist discussion forum. We analyzed the textual content of this data set with latent Dirichlet allocation (LDA), and we fed these analyses into a variety of time series models to forecast cyber-recruitment activity within the forum. Quantitative evaluations showed that employing LDA-based topics as predictors within time series models reduces forecast error compared with naive (random-walk), autoregressive integrated moving average, and exponential smoothing baselines. To the best of our knowledge, this is the first result reported on this forecasting task. This research could ultimately help assist with efficient allocation of intelligence analysts in response to predicted levels of cyber-recruitment activity.

    References

    [1]
    L. A. Overbey, G. McKoy, J. Gordon, and S. McKitrick, “Automated sensing and social network analysis in virtual worlds,” in Proc. IEEE Int. Conf. Intell. Secur. Inform. (ISI), Vancouver, BC, Canada, May 2010, pp. 179–184.
    [2]
    R. Torok, “‘Make a bomb in your mums kitchen’: Cyber recruiting and socialisation of ‘White Moors’ and home grown Jihadists,” in Proc. 1st Austral. Counter Terrorism Conf., Nov. 2010, pp. 54–61.
    [3]
    W. V. Fitzgerald. (Jun. 2010). Interview With Westboro Baptist Church: Hate Name God. [Online]. Available: http://www.digitaljournal.com/article/293364
    [4]
    M. Rogers, “The psychology of cyber-terrorism,” in Terrorists, Victims and Society: Psychological Perspectives on Terrorism and Its Consequences. Chichester, U.K.: Wiley, 2003, pp. 77–92.
    [5]
    S. O’Rourke, “Virtual radicalisation: Challenges for police,” in Proc. 8th Austral. Inf. Warfare Secur. Conf., Dec. 2007, pp. 29–35.
    [6]
    S. Mandal and E.-P. Lim, “Second life: Limits of creativity or cyber threat?” in Proc. IEEE Conf. Technol. Homeland Secur., May 2008, pp. 498–503.
    [7]
    R. R. Tomes, “Waging war on terror relearning counterinsurgency warfare,” Parameters, vol. 34, no. 1, pp. 16–28, 2004.
    [8]
    F. Gutiérrez, “Recruitment in a civil war: A preliminary discussion of the Colombian case,” 2006.
    [9]
    M. Humphreys and J. M. Weinstein, “Who fights? The determinants of participation in civil war,” Amer. J. Political Sci., vol. 52, no. 2, pp. 436–455, 2008.
    [10]
    M. I. Lichbach, The Rebel’s Dilemma. Ann Arbor, MI, USA: Univ. Michigan Press, 1998.
    [11]
    K. Peters and P. Richards, “‘Why we fight’: Voices of youth combatants in Sierra Leone,” J. Int. African Inst., vol. 68, no. 2, pp. 183–210, Apr. 1998.
    [12]
    J. M. Weinstein, Inside Rebellion: The Politics of Insurgent Violence. New York, NY, USA: Cambridge Univ. Press, 2007.
    [13]
    R. D. Petersen, Resistance and Rebellion: Lessons From Eastern Europe. New York, NY, USA: Cambridge Univ. Press, 2001.
    [14]
    S. L. Popkin, “The rational peasant,” Theory Soc., vol. 9, no. 3, pp. 411–471, 1980.
    [15]
    J. C. Scott, The Moral Economy of the Peasant: Rebellion and Subsistence in Southeast Asia. London, U.K.: Yale Univ. Press, 1976.
    [16]
    E. J. Wood, Insurgent Collective Action and Civil War in El Salvador. New York, NY, USA: Cambridge Univ. Press, 2003.
    [17]
    R. W. McGehee, Deadly Deceits: My 25 Years in the CIA, Z. Sklar, Ed. New York, NY, USA: Sheridan Square Pub., 1983.
    [18]
    M. Conway, “Terrorism and the Internet: New media—New threat?” Parliamentary Affairs, vol. 59, no. 2, pp. 283–298, 2006.
    [19]
    R. Torok, “Developing an explanatory model for the process of online radicalisation and terrorism,” Secur. Inform., vol. 2, no. 1, pp. 1–10, 2013.
    [20]
    L. Bowman-Grieve, “A psychological perspective on virtual communities supporting terrorist & extremist ideologies as a tool for recruitment,” Secur. Inform., vol. 2, no. 1, pp. 1–5, 2013.
    [21]
    E. F. Kohlmann, “Al-Qaida’s MySpace: Terrorist recruitment on the Internet,” CTC Sentinel, vol. 1, no. 2, pp. 8–9, 2008.
    [22]
    L. A. Overbey et al., “Virtual DNA: Investigating cyber-behaviors in virtual worlds,” Space and Naval Warfare System Center Atlantic, Charleston, SC, USA, Tech. Rep. 33-09E, 2009.
    [23]
    G. S. McNeal, “Cyber embargo: Countering the Internet jihad,” Case Western Reserve Univ. J. Int. Law, vol. 39, pp. 789–826, 2008.
    [24]
    H. Chen, S. Thoms, and T. Fu, “Cyber extremism in Web 2.0: An exploratory study of international Jihadist groups,” in Proc. IEEE Int. Conf. Intell. Secur. Inform. (ISI), Taipei, Taiwan, Jun. 2008, pp. 98–103.
    [25]
    M. Yang, M. Kiang, H. Chen, and Y. Li, “Artificial immune system for illicit content identification in social media,” J. Amer. Soc. Inf. Sci. Technol., vol. 63, no. 2, pp. 256–269, 2012.
    [26]
    A. Basu, “Social network analysis of terrorist organizations in India,” in Proc. Conf. North Amer. Assoc. Comput. Soc. Org. Sci. (NAACSOS). Notre Dame, IN, USA, 2005, pp. 26–28.
    [27]
    K. M. Carley, “Destabilization of covert networks,” Comput. Math. Org. Theory, vol. 12, no. 1, pp. 51–66, 2006.
    [28]
    M. Chau and J. Xu, “Using Web mining and social network analysis to study the emergence of cyber communities in blogs,” in Terrorism Informatics. New York, NY, USA: Springer-Verlag, 2008, pp. 473–494.
    [29]
    J. Diesner and K. M. Carley, “Using network text analysis to detect the organizational structure of covert networks,” in Proc. Conf. North Amer. Assoc. Comput. Soc. Org. Sci. (NAACSOS), Pittsburgh, PA, USA, 2004, pp. 1–6.
    [30]
    Z. Chen, B. Liu, M. Hsu, M. Castellanos, and R. Ghosh, “Identifying intention posts in discussion forums,” in Proc. NAACL-HLT, Jun. 2013, pp. 1041–1050.
    [31]
    D. M. Blei, A. Y. Ng, and M. I. Jordan, “Latent Dirichlet allocation,” J. Mach. Learn. Res., vol. 3, pp. 993–1022, 2003.
    [32]
    X. Wang and A. McCallum, “Topics over time: A non-Markov continuous-time model of topical trends,” in Proc. 12th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, 2006, pp. 424–433. [Online]. Available: http://dl.acm.org/citation.cfm?id=1150450
    [33]
    D. M. Blei and J. D. Lafferty, “Dynamic topic models,” in Proc. 23rd Int. Conf. Mach. Learn., 2006, pp. 113–120. [Online]. Available: http://dl.acm.org/citation.cfm?id=1143859
    [34]
    T. Fu, A. Abbasi, and H. Chen, “A focused crawler for dark Web forums,” J. Amer. Soc. Inf. Sci. Technol., vol. 61, no. 6, pp. 1213–1231, 2010.
    [35]
    J. R. Scanlon and M. S. Gerber, “Automatic detection of cyber-recruitment by violent extremists,” Secur. Inform., vol. 3, no. 1, pp. 1–10, Aug. 2014.
    [36]
    H. Chen, W. Chung, J. Qin, E. Reid, M. Sageman, and G. Weimann, “Uncovering the dark Web: A case study of Jihad on the Web,” J. Amer. Soc. Inf. Sci. Technol., vol. 59, no. 8, pp. 1347–1359, 2008.
    [37]
    Artificial Intelligence Laboratory, University Of Arizona. (2014). Dark Web Forum Portal: Ansar Al Jihad Network English Website. [Online]. Available: http://cri-portal.dyndns.org
    [38]
    Google Inc. (2014). Google Translate. [Online]. Available: http://translate.google.com/
    [39]
    M. S. Gerber, “Predicting crime using Twitter and kernel density estimation,” Decision Support Syst., vol. 61, pp. 115–125, May 2014.
    [40]
    I. Feinerer and K. Hornik. (2014). tm: Text Mining Package, R Foundation for Statistical Computing, R Package Version 0.5-10. [Online]. Available: http://CRAN.R-project.org/package=tm
    [41]
    T. P. Jurka, L. Collingwood, A. E. Boydstun, E. Grossman, and W. van Atteveldt. (2014). RTextTools: Automatic Text Classification Via Supervised Learning, R Package Version 1.4.2. [Online]. Available: http://CRAN.R-project.org/package=RTextTools
    [42]
    R Core Team. (2014). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. [Online]. Available: http://www.R-project.org/
    [43]
    P. Whittle, Hypothesis Testing in Time Series Analysis, vol. 4. Uppsala, Sweden: Almqvist & Wiksells, 1951.
    [44]
    R. J. Hyndman et al. (2014). Forecast: Forecasting Functions for Time Series and Linear Models, R Package Version 5.3. [Online]. Available: http://CRAN.R-project.org/package=forecast
    [45]
    R. J. Hyndman, A. B. Koehler, R. D. Snyder, and S. Grose, “A state space framework for automatic forecasting using exponential smoothing methods,” Int. J. Forecast., vol. 18, no. 3, pp. 439–454, 2002.
    [46]
    B.-H. Mevik, R. Wehrens, and K. H. Liland. (2013). PLS: Partial Least Squares and Principal Component Regression, R Package Version 2.4-3. [Online]. Available: http://CRAN.R-project.org/package=pls
    [47]
    R. J. Hyndman and A. B. Koehler, “Another look at measures of forecast accuracy,” Int. J. Forecast., vol. 22, no. 4, pp. 679–688, 2006.
    [48]
    W. H. Webster, D. E. Winter, A. L. Steel, Jr., W. M. Baker, R. J. Bruemmer, and K. L. Wainstein, “Final report of the William H. Webster Commission on the Federal Bureau of Investigation, counterterrorism intelligence, and the events at Fort Hood, Texas on November 5, 2009,” FBI Headquarters, Washington, DC, USA, Tech. Rep., 2012.
    [49]
    D. M. Blei and J. D. McAuliffe, “Supervised topic models,” in Proc. NIPS, vol. 7. 2007, pp. 121–128.

    Cited By

    View all
    • (2019)Modeling Islamist Extremist Communications on Social Media using Contextual DimensionsProceedings of the ACM on Human-Computer Interaction10.1145/33592533:CSCW(1-22)Online publication date: 7-Nov-2019

    Index Terms

    1. Forecasting Violent Extremist Cyber Recruitment
            Index terms have been assigned to the content through auto-classification.

            Recommendations

            Comments

            Information & Contributors

            Information

            Published In

            cover image IEEE Transactions on Information Forensics and Security
            IEEE Transactions on Information Forensics and Security  Volume 10, Issue 11
            Nov. 2015
            214 pages

            Publisher

            IEEE Press

            Publication History

            Published: 01 November 2015

            Author Tags

            1. natural language processing
            2. Violent extremist cyber-recruitment
            3. forecasting
            4. time series analysis

            Qualifiers

            • Research-article

            Contributors

            Other Metrics

            Bibliometrics & Citations

            Bibliometrics

            Article Metrics

            • Downloads (Last 12 months)0
            • Downloads (Last 6 weeks)0
            Reflects downloads up to

            Other Metrics

            Citations

            Cited By

            View all
            • (2019)Modeling Islamist Extremist Communications on Social Media using Contextual DimensionsProceedings of the ACM on Human-Computer Interaction10.1145/33592533:CSCW(1-22)Online publication date: 7-Nov-2019

            View Options

            View options

            Get Access

            Login options

            Media

            Figures

            Other

            Tables

            Share

            Share

            Share this Publication link

            Share on social media