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Power Laws for Cyber Crime. Richard Overill & Jantje Silomon Department of Informatics King’s College London. Power Laws. Characterise a multitude of processes which produce a large number of small events but a small number of large events: p(x) = C x -α log p(x) = log C - α log x
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Power Laws for Cyber Crime Richard Overill & Jantje Silomon Department of Informatics King’s College London
Power Laws • Characterise a multitude of processes which produce a large number of small events but a small number of large events: • p(x) = C x -α • log p(x) = log C - α log x • A log-log plot is a straight line with gradient -α • the exponent α characterises the power law in a phenomenological sense.
Previous Work • L F Richardson (1948/60) • “fatal quarrels” • L-E Cederman (2003) • wars • A Clauset et al. (2005/7) • terrorism in G7: α = 1.7 • N F Johnson et al. (2005/6) • old wars, new wars • R Coelho et al. (2008) • low-medium UK incomes: α = 3.1 - 3.3
Cyber Crime Dataset • 11 years (1997 - 2007) of US CSI (Computer Security Institute) annual average financial loss data over 12 e-crime categories. • Corrected for US$ inflation. • Cleaned to remove internal inconsistencies. • Kolmogorov-Smirnov test for divergence as x 0. • 99 data points representing 6737 incidents. • Minus-one jack-knife re-sampling provides uncertainty bounds on α.
Results & Conclusions • A double power regime appears to be in operation: • αL = 1.7 ± 0.1; r2L = 0.994 (over 92 points) • αR = 3.1 ± 0.3; r2R = 0.900 (over 7 points) • xX= $2.858M ± 0.350 • exponent of ~1.7 shared with incidence of terrorism in G7 nations. • exponent of ~3.1 shared with distribution of low-medium UK incomes.
Conjectures • Heists below ~$2.85M are characterised by a pre-planned, opportunistic, ‘ambush’ strategy. • Heists above ~$2.85M (financial fraud and IP theft) are characterised by an economic infrastructure (Serious Organised Cybercrime) • R Overill & J Silomon, Single and Double Power Laws for Cyber Crimes, J Information Warfare 10 (3) 29 – 36 (December 2011).