1.
Seminar Title

2.
Agenda
 Data Mining
 Why data mining
 Solution
 Applications of data mining
 Privacy Preservation with data mining
 Objectives
 Techniques
 Advantages
 Disadvantages
 Applications of PPDM
 Conclusion
 References

3.
Data Mining
 The task of discovering interesting patterns from
large amount of data.
 Process of Analyzing data from different sources into
useful information.

4.
Why data mining
 Data explosion problem
 Advance data collection tools and database
technology leads to tremendous amount of
data stored in database.
 We are drowning data but starving for
knowledge.

5.
Solution
1) Data Warehouse - for storing large amount
of data
2) Data Mining - Extracting required
knowledge.

6.
Applications
Industry Application
Finance Credit Card Analysis
Insurance Claims and Fraud Analysis
Telecommunication Call record Analysis
Transport Logistic Analysis
Consumer Goods Promotion analysis
Scientific Research Image, Audio, Video
Security Intrusion Detection System

7.
Privacy Preservation with data mining
 Sensitive information should not be disclosed.
 Data mining aims to extract useful information from huge data where privacy
preserving aims to protect data against loss.
 Protect users information from intruders.
 Thus privacy is important for data mining application and also for
government because there are so many applications of data mining to handle
terrorisms.
 Preserve privacy while data collection and mining.

8.
Objectives
 Perform data mining on union of two private data.
 Private data – users can not see internal data but can see
output.
 Achieving data mining goals without scarifying the
privacy of users.
 Develop an algorithm for modifying the original data
but private data and knowledge remain private after
mining process.

9.
Techniques
 Data Perturbation
 Blocking Based Technique
 Cryptographic Technique
 Hybrid Technique
 Condensation Approach Technique

10.
Advantages
 Help in development of various data mining
techniques.
 Allow safe sharing of large amount of data.
 Allow privacy for sensitive data.
 Track the current and large amount of data by
using Data Mining technique.

11.
Disadvantages
 Need to improve technology.
 Hackers are smart to hack data.

12.
Applications
 Improve customer services.
 Speed up the drug investigation.
 Homeland security.
 Medical database mining.
 Customer transaction.

13.
Conclusion
Due to right to privacy in information, PPDM
has one of the newest trend in privacy and security
and data mining research. Data mining is useful to
extract required pattern from large amount of data
where privacy on data mining keep information
safe.

14.
References
 International Journal of Advanced Research in Computer and
Communication Engineering Vol. 2, Issue 4, April 2013.
 International Journal of Computer Applications Technology and
Research Volume 3- Issue 7, 403-408, July 2014.
 International Journal of Innovative Research in Computer and
Communication Engineering (An ISO 3297: 2007 Certified
Organization) Vol. 2, Special Issue 3, July 2015.
 International Journal on Cybernetics and Informatics (IJCI) Vol. 3, No.
1, February 2014.