Name
Title | ||
|---|---|---|
Privacy-Preserving Outsourcing of Pattern Mining of Event-Log Data - A Use-Case from Process Industry |
Abstract | ||
|---|---|---|
With the advent of cloud computing and its model for IT services based on the Internet and big data centers, the interest of industries into XaaS ("Anything as a Service") paradigm is increasing. Business intelligence and knowledge discovery services are typical services that companies tend to externalize on the cloud, due to their data intensive nature and the algorithms complexity. What is appealing for a company is to rely on external expertise and infrastructure to compute the analytical results and models which are required by the business analysts for understanding the business phenomena under observation. Although it is advantageous to achieve sophisticated analysis there exist several serious privacy issues in this paradigm. In this paper we investigate through an industrial use-case the application of a framework for privacypreserving outsourcing of pattern mining on event-log data. Moreover, we present and discuss some ideas about possible extensions. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CloudCom.2016.0095 | 2016 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) |
Keywords | Field | DocType |
anonymization,data privacy,case study,pattern | Data science,Process industry,Computer science,Outsourcing,Knowledge extraction,Business intelligence,Big data,Cloud computing,Knowledge process outsourcing,The Internet | Conference |
ISBN | Citations | PageRank |
978-1-5090-1446-0 | 0 | 0.34 |
References | Authors | |
17 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessandro Marrella | 1 | 0 | 0.34 |
| Anna Monreale | 2 | 581 | 42.49 |
| Benjamin Klöpper | 3 | 3 | 1.54 |
| Martin W. Krueger | 4 | 0 | 0.34 |