1. Strategic Management of Cybercrime Making Crime Pay A/Prof Paul A. Watters Research Director ICSL

2. Overview  Use business planning activities to interpret current cybercrime tactics within a strategic context  Understand the key drivers for management in cybercrime organisations  Predict how new threats to cybercrime might change or curtail future organisational planning

3. Business Planning  Cybercrime organisations are like any other business What cash return is sought by their investors?  ROI What are the (non-cash) critical success factors?  Risk management – threat of arrest, seizure of capital

4. Business Planning  How do we know they operate like a business?

5. Business Analysis Steps 1. What do we do? 2. To whom do we do it? 3. How do we do it? 4. How can we beat or avoid competition?

6. What do we do?  Goal is to maximise revenue through fraud Identify most vulnerable targets  The unemployed or desperate Identity schemes which maximise return but minimise risk  Low or nil cost to operate, minimal risk of detection or arrest Scheme proceeds laundered through legitimate businesses  Cheque cashing fraud, mules

7. To whom do we do it?  Identify asset-rich countries with sophisticated banking systems Must have easy means to “cash out” Attack launched from countries with no extradition treaty with target Local “protection” from government, police, legitimate business as cover etc Individual loss < minimum thresholds for investigation (no loss aggregation)

8. How do we do it? Example: Implied Obligation?

9. How do we do it?

10. How can we beat or avoid competition?  Principle of specialisation Writing kits or running attacks? Diversified industrial – very 1970’s  Strategic HR Hiring the best talent  Partnerships Strategic outsourcing where it makes sense  Trade organisations Sharing knowledge, intelligence and expertise freely

11. Strategy from tactical data?  Key challenge to measure the threat landscape Mapping of campaigns to identifiable groups Estimate of potential impact  Quantitative – dollars lost  Qualitative – harm to reputation, confidence in banking

12. Phishing Campaigns Australian Data Volume

13. Optimised threat management  Can we use data mining to optimise response to threats? Best allocation of resources to different types of threat  Existing kits = takedowns, resource management  New kits = forensic investigation, focused intelligence discovery/updates

14. An Example: New Threats

15. Time Volume of new attacks

16. No Simple Answers Only 5% of variation in new case volume over time accounted for by linear model!

17. Profiling – Know Your Enemy

18. Summary  Cybercriminals operate as businesses  Analysing cybercrime data helps us interpret the threat landscape Understanding of current activity levels Prediction of future types of activity Reveals the drivers and business planning choices undertaken by criminal groups  Simple techniques only achieve so much More sophisticated algorithms needed to improve predictability