Competitive Privacy: Secure Analysis on Integrated Sequence Data

1. Competitive Privacy: Secure Analysis on Integrated Sequence Data Raymond Chi-Wing Wong1, Eric Lo2 The Hong Kong University of Science and Technology1 Hong Kong Polytechnic University2 Prepared by Raymond Chi-Wing Wong Presented by Raymond Chi-Wing Wong

2. Outline • Introduction • Problem • Algorithm • Conclusion

3. 1. Introduction • In this talk, • “competitive privacy” • occurs when two datasets from two different sources are integrated • Illustrate this concept with a transportation application • Give the motivation why two datasets should be integrated • Explain that there is a privacy issue in this application

4. 1. Introduction • Transportation Application Both companies has implemented RFID-based electronic Transportation payment systems (e.g., Washington DC’s SmarTrip system and Hong Kong Octopus System). Passenger travel history in the bus company Passenger travel history in the metro company Bus Company B Metro Company M

5. These two sequences are stored separately. Suppose that the bus company and the metro company want to collaborate and offer discounts to passengers who traveled from airport to uptown using a combination of bus and metro. We need to integrate these two datasets to know the total number of such passengers RFID No. = 222“Downtown Station”, “Uptown Station” 10:15am 11:00am RFID No. = 222 “Airport Bus Stop”, “Downtown Bus Stop” Bus Company B Metro Company M 9:00am 10:00am

6. RFID No. = 222 “Airport Bus Stop”, “Downtown Bus Stop”, “Downtown Station”, “Uptown Station” 9:00am 10:15am 10:00am 11:00am RFID No. = 222“Downtown Station”, “Uptown Station” 10:15am 11:00am RFID No. = 222 “Airport Bus Stop”, “Downtown Bus Stop” Bus Company B Metro Company M 9:00am 10:00am

7. RFID No. = 222 “Airport Bus Stop”, “Downtown Bus Stop”, “Downtown Station”, “Uptown Station” RFID No. = 222“Downtown Station”, “Uptown Station” RFID No. = 222“Airport Bus Stop”, “Downtown Bus Stop” Bus Company B Metro Company M

8. 1. Introduction • In this talk, • “competitive privacy” • occurs when two datasets from two different sources are merged • Illustrate this concept with a transportation application • Give the motivation why two datasets should be integrated • Explain that there is a privacy issue in this application

9. 1. Introduction • In this talk, • “competitive privacy” • occurs when two datasets from two different sources are merged • Illustrate this concept with a transportation application • Give the motivation why two datasets should be integrated • Explain that there is a privacy issue in this application

10. RFID No. = 222 “Airport Bus Stop”, “Downtown Bus Stop”, “Downtown Station”, “Uptown Station” If the metro company knows that the no. of passengers using sB is 80,000, then it may offer discounts to passengers using its own service sM to attract more passengers This statistical information about the competitive services corresponds to the “competitive privacy” of the bus company Data integration may cause privacy issues. Thus, the original service sB operated by the bus company will be definitely affected. No of Passengers = 80,000 No of Passengers = 10,000 Service sB“Downtown Bus Stop”, “Bay Bus Stop” Service sM“Downtown Station”, “Bay Station” These two services are competitive. Bus Company B Metro Company M

11. 2. Problem • Given • two companies • the bus company • the metro company • Objective • After the datasets from these two companies are integrated, • no company can infer any statistical information about the competitive services of the other company

12. 2. Problem • Contribution • We are the first to propose the concept of “competitive privacy” • Privacy model when sequence datasets are integrated • Previous works • Privacy model when relational datasets are integrated

13. 3. Algorithm

14. Trusted Third Party Determine whether this query allows that the metro company can infer any statistical information about the competitive services of the bus company. If yes, we reject the query. If no, we give the answer of this query. Integrated database answer 1 query 1 Bus Company B Metro Company M

15. 3. Algorithm • Idea: • We reject any queries related to the statistical information about all competitive services • We skip the details

16. 4. Conclusion • Privacy Model for Data Integration • Competitive Privacy • Algorithm

17. Q&A

18. 4. Empirical Studies • Real dataset • Hong Kong Local Transportation Metro Data • 63 stations • 6 transfer stations • 4 railway lanes

19. 4. Empirical Studies • Variation • No. of tuples in the integrated dataset • The pattern size in a query • Measurements • Audit time (the time to determine whether this query should be answered or rejected) • Ratio of rejected queries (or restricted queries)

20. 4. Empirical Studies The audit time is small. The ratio of restricted queries is small.

22. Trusted Third Party Determine whether this query allows that the bus company can infer any statistical information about the competitive services of the metro company. If yes, we reject the query. If no, we give the answer of this query. Integrated database 20,000 answer 1 e.g., the total number of passengers who have a travel pattern “Airport Bus Stop”, “Downtown Bus Stop”, “Downtown Station”, “Uptown Station”. query 1 Pattern Size = 4 Bus Company B Metro Company M

23. Trusted Third Party Determine whether this query allows that the bus company can infer any statistical information about the competitive services of the metro company. If yes, we reject the query. If no, we give the answer of this query. Integrated database answer 2 query 2 Bus Company B Metro Company M

24. Trusted Third Party Determine whether this query allows that the bus company can infer any statistical information about the competitive services of the metro company. If yes, we reject the query. If no, we give the answer of this query. Integrated database answer 3 query 3 Bus Company B Metro Company M

25. Each query alone may not provide any statistical information of the competitive services • However, the combination of all query answers may allow that the metro company can infer the statistical information of competitive services

26. Trusted Third Party Knowledge 2: there are two services from “Downtown District” to “Bay District” 1. The service provided by the bus company (“Downtown Bus Stop” to “Bay Bus Stop”) 2. The service provided by the metro company (“Downtown Station” to “Bay Station”) Knowledge 3: the total number of passengers who have a travel pattern “Downtown Station” to “Bay Station” = 10,000 Integrated database Conclusion: the total number of passengers who have a travel pattern “Downtown Bus Stop” to “Bay Bus Stop” = 90,000 – 10,000 = 80,000 The statistical information of the competitive services of the bus company. Knowledge 1 Query: the total number of passengers who have a travel pattern “Downtown District”, “Bay District” 90,000 Bus Company B Metro Company M

27. RFID No. = 222 “Airport Bus Stop”, “Downtown Bus Stop”, “Downtown Station”, “Uptown Station” Both companies want to know the total number of passengers traveling from “Airport Bus Stop” to “Uptown Station” Roll-up Both companies want to know the total number of passengers traveling from “Airport District” to “Uptown District” Bus Company B Metro Company M

28. Trusted Third Party Determine whether this query allows that the metro company can infer any statistical information about the competitive services of the bus company. If yes, we reject the query. If no, we give the answer of this query. Integrated database answer 1 query 1 Bus Company B Metro Company M

29. Trusted Third Party Determine whether this query allows that the metro company can infer any statistical information about the competitive services of the bus company. If yes, we reject the query. If no, we give the answer of this query. Integrated database answer 2 query 2 Bus Company B Metro Company M

30. Trusted Third Party Integrated database answer 3 query 3 Bus Company B Metro Company M