“The Geek and the Gumshoe” or “Can Mathematics and Computers Really Solve Crimes?”

1. “The Geek and the Gumshoe” or“Can Mathematics and Computers Really Solve Crimes?” Michael “theprez98” SchearerFrank “Thorn” Thornton

2. Introduction

3. Who are we, and why are we here?

4. The Geek: Michael Schearer • Fascinated by the application of mathematics to real-world situations • Recently separated from nearly 9 years in the U.S. Navy (flying aircraft) • Currently working for a U.S. government contractor in Maryland (flying a desk) • Contributing author to Penetration Tester's Open Source Toolkit (Volume 2) Netcat Power Tools (April 2008), and maybe more! • Football coach and proud father of three

5. When did Frank start as a cop?

6. Looking forward…

7. The Gumshoe: Frank Thornton • Law Enforcement Officer, 1980 – 2002. Served in a variety of ranks and positions from Patrol Officer to Chief of Police. Also worked in VT Forensic Lab on Latent Fingerprints and crime scene investigations. Rated as a Class I (Homicide) Death Investigator by Vermont’s Office of the Chief Medical Examiner • Hacking computers since ~1973 • Helped create ANSI Standard “ANSI/NIST-CSL 1-1993 Data Format for the Interchange of Fingerprint Information” • Author and co-author of a half-dozen books on computer security. (Cheerfully blatant plug!)

8. Agenda • Introduction • Explanation • Videos • Perceptions • Math, Computers & Crime • Math in everyday life • Math and crime-fighting • Conclusions • Questions & Answers

9. Police Investigations Are ALL About Collecting Data • Who • What • When • Where • How

10. Investigations differ from other data collection in several areas • Everyone lies to the police. • Fact has to be separated from:-Lies.-Fiction.-Opinion.-Other false positives. (May be thousands) • Eye witnesses have a high credibility with prosecutors and juries, less so with cops. • Everyone lies to the police. • Failure can be dangerous to the public. • Did we mention that everyone lies to the police?

11. Information = Data This is sometimes recognized at some level. Joseph Wambaugh, ex-LAPD Detective, award winning mystery novelist and screenwriter wrote this in The Black Marble: “Clarence looked around at the roar of activity, at the grinding paper mill. Paper everywhere. Take away my gun and car, but please don't take my pencils.”

12. Information = Data “You walked in with information and a pretty face.You can’t leave with both.”

13. Doesn’t it really work like on CSI? • The CSI Effect • Perception and Reality • DNA Testing • AFIS Searches • School-Associated Violence • Cops are always doing exciting things like getting in fights or shooting bad guys

14. So, knowing all that, what other tools are available to help investigations?

15. “Time for science!” So let’s explore how math and computer technology can help with investigations…

16. Math is everywhere. • Elections • Voting, exit polls, voter identification/analysis • Sports • Statistics, sabermetrics, betting/sports book • Lottery • Probability (or perhaps improbability!) • Math in advertising • frequency atlas, Google advertisements, British two pound coin

17. Billboard say what?

18. What is wrong with this picture?

19. Can Mathematics and Computers Really Solve Crimes?

20. Crash Reconstruction • Collision evidence • positions of rest, skid marks, roadway markings, damage to vehicles, damage to property • Other evidence • Witness recollections, traffic control devices, weather conditions, lighting issues • Available specifications • Newton’s laws of motion • Collision reconstruction techniques • Damaged-based • trajectory-based

21. Image Deblurring • “Enhance…enhance…enhance…” • Blurring is typically caused by movement during the capture process by the camera or by the subject, or an out of focus lens • Deblurring involves finding a mathematical description of how the image was blurred

22. Image Deblurring Before… After

23. Image Deblurring A camera captured this image Image deblurring produced this image

24. Deblurring Fingerprints • A very touchy subject! By deblurring a fingerprint, are non-existent details being added to a latent print? • Typically, any enhancement (fingerprint or otherwise) must be verifiable and able to be duplicated by another expert • The risk in “crossing the line” is highly dependent upon use of tools

25. Fingerprint Matching • Different vendors use different algorithms • 10 different Fingerprint Individuality models • Minutiae matching vs. Pattern matching • Speed and throughput vs. accuracy • Error rates • Type I (FP, FRR) vs. Type II (FN, FAR) • Crossover or Equal Error Rate • Security vs. Forensic Science

26. Receiver Operating Characteristics

27. Fingerprint Classification

29. Escape Math • Variables • Time, Method of travel, Achievable speeds, Traffic density, Traffic choke points • Dijkstra’s algorithm • Link-state routing protocols (OSPF), MapQuest, Google Maps • Random walks • Calculate distance escaped POWs could travel in WW2 • Trawler problem • Drive-time calculations (MapPoint) • Social network analysis (to be discussed later)

30. Dijkstra’s Algorithm

31. Random walks

32. Trawler problem

33. Narrowing the Suspect Pool • Profiling • Psychological/criminal • Geographic (to be discussed later) • Venn diagrams

34. Social Networks • Social network analysis • Google’s PageRank algorithm is an example of network analysis • Organized crime, gangs, terrorist cells, individuals, other organizations • Social relationships in terms of nodes and ties • Determine the social capital of individual actors • Things to consider • Who are someone’s closest friends/associates? • Where might that person flee to? • Structural cohesion: could you eliminate a specific individual from a group which could cause that group to collapse?

35. Social network of a project team

36. Social network of 9/11 terrorists

37. Crime Mapping • Choropleths • Pin Mapping • Hot Spot Analysis • Geographic Profiling

38. France, 1829

39. London, September 1854

40. Choropleths and Pin Mapping • NYPD has used traditional pin mapping since at least 1900 • University of Chicago researchers mapped crime in Chicago neighborhoods (1920-30s) • These methods of mapping helped to identify relationships between crime and neighborhoods, social disorganization, poverty, and physical deterioration

41. Automated Crime Mapping • Automated mapping began in the late 1960s • Did not really “take off” until the 1990s • Hot Spot Analysis • Finding geographic concentrations of types of crimes; finding causes for those hot spots; aggressive policing in those areas • Geographic profiling • If psychological profiling tells you “who”, geographic profiling tells you “where”

43. Hot Spot Analysis

44. Hot Spot Analysis

45. Geographic Profiling • If Psychological/criminal profiling tells you “who”, geographic profiling tell you “where” • Suitable for serial crimes: murder, rape, robbery, arson, predatory crimes • Gives police a starting point from which to narrow down lists of suspects • Does not replace traditional investigative techniques, but supplements them to help manage the large volume of information

46. Geographic Profiling • CrimeStat, Dragnet, Predator, Rigel • Theory is based upon “journey to crime” and “principle of least effort” • “Journey to crime” varies among type of crime, age, race, etc. • Includes a buffer zone around the offender’s home or base of operations

47. Saanich Serial Arsonist

48. Jeopardy Surface

49. Probability of Offender Residence

50. GeoProfile