Bài giảng Bảo mật cơ sở dữ liệu - Security Methods for Statistical Databases

Nội dung text: Bài giảng Bảo mật cơ sở dữ liệu - Security Methods for Statistical Databases

1. Security Methods for Statistical Databases
2. Introduction ▪ Statistical Databases containing medical information are often used for research ▪ Some of the data is protected by laws to help protect the privacy of the patient ▪ Proper security precautions must be implemented to comply with laws and respect the sensitivity of the data
3. Accuracy vs. Confidentiality Accuracy – Confidentiality – Researchers Patients, laws want to extract and database accurate and administrators meaningful data want to maintain the privacy of patients and the confidentiality of their information
4. Laws ▪ Health Insurance Portability and Accountability Act – HIPAA (Privacy Rule) ▪ Covered organizations must comply by April 14, 2003 ▪ Designed to improve efficiency of healthcare system by using electronic exchange of data and maintaining security ▪ Covered entities (health plans, healthcare clearinghouses, healthcare providers) may not use or disclose protected information except as permitted or required ▪ Privacy Rule establishes a “minimum necessary standard” for the purpose of making covered entities evaluate their current regulations and security precautions
5. HIPAA Compliance ▪ Companies offer 3rd Party Certification of covered entities ▪ Such companies will check your company and associating companies for compliance with HIPAA ▪ Can help with rapid implementation and compliance to HIPAA regulations
6. Types of Statistical Databases ▪ Static – a static ▪ Dynamic – changes database is made continuously to reflect once and never real-time data changes ▪ Example: most online ▪ Example: U.S. Census research databases
7. Security Methods ▪ Access Restriction ▪ Query Set Restriction ▪ Microaggregation ▪ Data Perturbation ▪ Output Perturbation ▪ Auditing ▪ Random Sampling
8. Access Restriction ▪ Databases normally have different access levels for different types of users ▪ User ID and passwords are the most common methods for restricting access ▪ In a medical database: ▪ Doctors/Healthcare Representative – full access to information ▪ Researchers – only access to partial information (e.g. aggregate information)
9. Query Set Restriction ▪ A query-set size control can limit the number of records that must be in the result set ▪ Allows the query results to be displayed only if the size of the query set satisfies the condition ▪ Setting a minimum query-set size can help protect against the disclosure of individual data
10. Query Set Restriction ▪ Let K represents the minimum number or records to be present for the query set ▪ Let R represents the size of the query set ▪ The query set can only be displayed if K R
11. Query Set Restriction Query 1 Query 2 Original Database Query 2 Query Results K Results Query 1 K Query Results Results
12. Microaggregation ▪ Raw (individual) data is grouped into small aggregates before publication ▪ The average value of the group replaces each value of the individual ▪ Data with the most similarities are grouped together to maintain data accuracy ▪ Helps to prevent disclosure of individual data
13. Microaggregation ▪ National Agricultural Statistics Service (NASS) publishes data about farms ▪ To protect against data disclosure, data is only released at the county level ▪ Farms in each county are averaged together to maintain as much purity, yet still protect against disclosure
14. Microaggregation Age Microaggregated Age 10 11.67 12 Average 11.67 13 11.67 57 56.67 54 Average 56.67 59 56.67
15. Microaggregation User ry e s u lt u Q s e R Averaged Original Microaggregated Data Data
16. Data Perturbation ▪ Perturbed data is raw data with noise added ▪ Pro: With perturbed databases, if unauthorized data is accessed, the true value is not disclosed ▪ Con: Data perturbation runs the risk of presenting biased data
17. Data Perturbation User 1 Noise Added ry e s u lt u Q s e R Original Perturbed Database Database R e su Q lts u e ry User 2
18. Output Perturbation ▪ Instead of the raw data being transformed as in Data Perturbation, only the output or query results are perturbed ▪ The bias problem is less severe than with data perturbation
19. Output Perturbation Query User 1 Results ery Qu ts sul Re Noise Added to Results Original Database Re su lts Query Q Results ue ry User 2
20. Auditing ▪ Auditing is the process of keeping track of all queries made by each user ▪ Usually done with up-to-date logs ▪ Each time a user issues a query, the log is checked to see if the user is querying the database maliciously
21. Random Sampling ▪ Only a sample of the records meeting the requirements of the query are shown ▪ Must maintain consistency by giving exact same results to the same query ▪ Weakness - Logical equivalent queries can result in a different query set
22. Comparison Methods The following criteria are used to determine the most effective methods of statistical database security: ▪ Security – possibility of exact disclosure, partial disclosure, robustness ▪ Richness of Information – amount of non-confidential information eliminated, bias, precision, consistency ▪ Costs – initial implementation cost, processing overhead per query, user education
23. A Comparison of Methods Method Security Richness of Costs Information Query-set Restriction Low Low1 Low Microaggregation Moderate Moderate Moderate Data Perturbation High High-Moderate Low Output Perturbation Moderate Moderate-low Low Auditing Moderate-Low Moderate High Sampling Moderate Moderate-Low Moderate 1 Quality is low because a lot of information can be eliminated if the query does not meet the requirements
24. Sources ▪ This presentation is posted on ▪ Adam, Nabil R. ; Wortmann, John C.; Security- Control Methods for Statistical Databases: A Comparative Study; ACM Computing Surveys, Vol. 21, No. 4, December 1989 ( adam.pdf?key1=76895&key2=1947043301&coll=portal&dl=ACM&CFID=4702747&CFTOKEN=83773110) ▪ Official HIPAA – ( incur ▪ Bernstein, Stephen W.; Impact of HIPAA on BioTech/Pharma Research: Rules of the Road ( ▪ Service Bureau; 3rd Party Testing (