1. Crime Science Marianne Junger [Cla09] R. V. Clarke. Crime science. In E. McLaughlin and T. Newburn, editors, Handbook of Criminal Theory, pages 271-283. Sage, London, 2009. http://www.sagepub.com/books/Book228876 http://www.sagepub.com/books/Book228876

2. Contents Origins of crime Theories of Crime Science Situational Crime Prevention Cyber-crime Science 2

3. Origins of crime Two essential and different factors 1.Person factors (criminality) 2.Situations (crime) Cyber-crime Science 3

4. Person factors Crime is ‘natural behaviour’ Everybody has the potential Some more than others… How can we know? Indirect evidence: –observe animals –observe babies Cyber-crime Science 4

5. Physical Aggression of Toddlers Dutch Toddlers (17 months), in %SometimesOftenSum Take things65,820,586,3 Pulls others56,4662,4 Pushes to get what he wants45,310,355,6 Hits others42,73,446,1 Start fights24,81,726,5 Threatens others22,23,425,6 Bites14,53,417,9 Kicks2,60 Sum94 Cyber-crime Science 5 [Ake07] C. van Aken, M. Junger, M. Verhoeven, M. A. G. van Aken, and M. Dekovic. Externalizing behaviors and minor unintentional injuries in toddlers: Common risk factors? Journal of Pediatric Psychology, 32(2):230-244, Mar 2007. http://dx.doi.org/10.1093/jpepsy/jsj118 http://dx.doi.org/10.1093/jpepsy/jsj118

6. Physical Aggression of Toddlers (contd.) Most toddlers are physically aggressive The level of aggression decreases over time Data suggests: »Aggression has to be ‘unlearned’ »During first (eight) years in life 6 Cyber-crime Science [Tre00] R. E. Tremblay. The development of aggressive behavior during childhood: what have we learned in the past century? Int. J. of Behavioral Development, 24(2):129-141, Jun 2000. http://dx.doi.org/10.1080/016502500383232. http://dx.doi.org/10.1080/016502500383232.

7. Problem of person approach for prevention Stability of behaviour is high Potential for change decreases over the life course »See experimental evidence »Studies with mothers & babies, small children, older children, adolescents Cyber-crime Science 7

8. Malleability of behaviour is limited Cyber-crime Science 8 [Hec06] J. J. Heckman. Skill formation and the economics of investing in disadvantaged children. Science, 312(5782):1900-1902, 2006. http://dx.doi.org/10.1038/428598a http://dx.doi.org/10.1038/428598a

9. Theories of crime science Cyber-crime Science 9 [Cla09] R. V. Clarke. Crime science. In E. McLaughlin and T. Newburn, editors, Handbook of Criminal Theory, pages 271-283. Sage, London, 2009. http://www.sagepub.com/books/Book228876 http://www.sagepub.com/books/Book228876

10. Crime science- summary Incident oriented Purpose: understand the modus operandi of crime Goal: prevention Basis: Rational choice, Opportunity theory & Routine Activities Means: Situational crime prevention Practice: Measure effectiveness and efficiency Cyber-crime Science 10

11. Theoretical foundation Routine Activity Approach (RAT) »crime occurs when a potential offender meets with a suitable target in the absence of a capable guardian. Crime Pattern theory »crime is concentrated at particular places (hot spots), targets the same victims repeatedly, (repeat victimisation), and selects hot products. Rational choice perspective »criminals make a bounded rational choice judging risks and benefits. Cyber-crime Science 11 Crime Opp. Every day life Society

12. Rational choice perspective Criminality is goal oriented behaviour Based on a rational decision Crime specific Crime scripts In sociology, psychology, economy, biology, public health etc Cyber-crime Science 12 [Cor08] D. B. Cornish and R. V. Clarke. The rational choice perspective. In R. Wortley and L. Mazerolle, editors, Environmental Criminology and Crime Analysis, pages 21-47. Willan Publishing, Uffculme, UK, 2008. http://www.willanpublishing.co.uk/cgi- bin/indexer?product=9781843922803http://www.willanpublishing.co.uk/cgi- bin/indexer?product=9781843922803

13. RAT - Opportunity theory Crime is the outcome of the interaction between dispositions and situations Crime is the product of choice Crime specific focus essential for effective prevention Crime is heavily concentrated Crime can be reduced by environmental changes Cyber-crime Science 13 [Fel98] M. Felson and R. V. Clarke. Opportunity makes the thief: Practical theory for crime prevention. Police Research Series Paper 98, Home Office, Policing and Reducing Crime Unit, London, 1998. http://www.homeoffice.gov.uk/rds/prgpdfs/fprs98.pdfhttp://www.homeoffice.gov.uk/rds/prgpdfs/fprs98.pdf

14. Wealth paradox Wealth presents opportunity »More to steal in houses »Less surveillance More wealth hence more crime Cyber-crime Science 14 [Coh79] L. E. Cohen and M. Felson. Social change and crime rate trends: A routine activity approach. American Sociological Review, 44(4):588-608, Aug 1979. http://www.jstor.org/pss/2094589 http://www.jstor.org/pss/2094589

15. Crime triangle Cyber-crime Science 15

16. Situational approach Used in many disciplines/fields »Economy »Social psychology, e.g., marketing »Traffic »Public health Cyber-crime Science 16

17. Opportunity correlates Cyber-crime Science 17 [Pea04] H. Pearson. Public health: The demon drink. Nature, 428:598-600, Apr 2004. http://dx.doi.org/10.1038/428598a http://dx.doi.org/10.1038/428598a

18. Situational crime prevention 18 [Cla08] R. V. Clarke. Situational crime prevention. In R. Wortley and L. Mazerolle, editors, Environmental Criminology and Crime Analysis, pages 178-194. Willan Publishing, London, Jun 2008. http://www.routledge.com/9781843922803http://www.routledge.com/9781843922803

19. Situational crime prevention Based on the theories of Crime Science A standard methodology based on experiments and action research. A set of opportunity-reducing techniques. A body of evaluated practice including studies of displacement. Cyber-crime Science 19

20. Experiments and action Research Cyber-crime Science 20 1 2,3 4 5 1. collection of data about the nature of problem 2. analysis of the situational conditions 3. systematic study of means of blocking opportunities 4. implementation of the most promising means 5. monitoring of results and dissemination of experience. [Lay04] G. Laycock. The UK car theft index: An example of government leverage. In Understanding and Preventing Car Theft, Crime Prevention Studies 17, pages 25-44. Criminal Justice Press, Monsey, New York, 2004

21. Opportunity reducing techniques Increase effort »Time, skills Increase risks »Of getting caught, failure, loosing resources Reduce rewards »So that the offender has less benefits after the crime Reduce provocation »So that the offender is less tempted to start Remove excuses »So that the offender cannot justify the crime Cyber-crime Science 21

22. Practical examples Cyber-crime Science 22

23. Increase effort: alley gating Cyber-crime Science 23 [Bow04a] K. J. Bowers, S. D. Johnson, and A. F. G. Hirschfield. Closing off opportunities for crime: An evaluation of Alley-Gating. European J. on Criminal Policy and Research, 10(4):285-308, Sep 2004. http://dx.doi.org/10.1007/s10610-005-5502-0http://dx.doi.org/10.1007/s10610-005-5502-0

24. Increase risks: surveillance Cyber-crime Science 24

25. Reduce rewards: RFID tags Cyber-crime Science 25

26. Reduce provocations: Flyers Cyber-crime Science 26 OrderDisorder: graffiti 1. Alley, flyer on bicycle33%69% 2. No trespassing27%82% 3. Supermarket30%58% 4. Littering/noise52%80% 5. Stealing Euro : graffiti, no litter on ground 13% 27% 6. Stealing Euro 5: no graffiti, litter on ground 25% [Kei08] K. Keizer, S. Lindenberg, and L. Steg. The spreading of disorder. Science, 322(5908):1681-1685, Dec 2008. http://dx.doi.org/10.1126/science.1161405http://dx.doi.org/10.1126/science.1161405

27. Remove excuses: Eyes Cyber-crime Science 27 Pounds paid per litre of milk consumed as a function of week and image type. [Bat06] M. Bateson, D. Nettle, and G. Roberts. Cues of being watched enhance cooperation in a real-world setting. Biology Letters, 2(3):412-414, Sep 2006. http://dx.doi.org/10.1098/rsbl.2006.0509 http://dx.doi.org/10.1098/rsbl.2006.0509

28. Remove excuses (contd.) Underspecified methods Confounding variables Invalid statistics Lack of insight »Still: nice hypothesis to basis new research on Cyber-crime Science 28 [Car12] C. C. Carbon and V. M. Hesslinger. Bateson et al.'s (2006) cues-of-being-watched paradigm revisited. Swiss Journal of Psychology, 70(4):Article 58, Dec 2011. http://dx.doi.org/10.1024/1421-0185/a000058 http://dx.doi.org/10.1024/1421-0185/a000058

29. Cyber-crime Science 29

30. Displacement? Most important issue! Detoxification of gas in UK households Cyber-crime Science 30 [Cla88b] R. V. Clarke and P. Mayhew. The British gas suicide story and its criminological implications. Crime and Justice, 10:79-116, 1988. http://www.jstor.org/stable/1147403http://www.jstor.org/stable/1147403

31. Displacement? Detoxification of gas in UK households Cyber-crime Science 31 [Cla88b] R. V. Clarke and P. Mayhew. The British gas suicide story and its criminological implications. Crime and Justice, 10:79-116, 1988. http://www.jstor.org/stable/1147403http://www.jstor.org/stable/1147403

32. Diffusion of benefits Diffusion of benefits: Examples »Alley gating… »Tagging of expensive electronic products in shops Meta-analysis* » 25% diffusion of benefits, » 50% nothing at all » 25% displacement – never complete Cyber-crime Science 32 [Gue09] R. T. Guerette and K. J. Bowers. Assessing the extent of crime displacement and diffusion of benefits: a review of situational crime prevention evaluations. Criminology, 47(4):1331-1368, Nov 2009. http://dx.doi.org/10.1111/j.1745-9125.2009.00177.x.http://dx.doi.org/10.1111/j.1745-9125.2009.00177.x.

33. Discussion This was ‘normal’ crime…. See for a large collection of examples http://www.popcenter.org/ http://www.popcenter.org/ What about cyber opportunities? Cyber-crime Science 33

34. Conclusions Origins of crime: interaction “person by situation” Importance of situations : wealth, alcohol Theories of crime science: RA, RCM, opportunities »A standard methodology: experiments/policies. »A set of opportunity-reducing techniques: this helps! »A body of evaluated practice including studies of displacement. Cyber-crime Science 34