Name
Abstract | ||
|---|---|---|
The amount of computing done in the cloud is greatly increasing. The decentralized nature of the cloud, however, makes it difficult for individuals to ensure that the computation is being done correctly. Thus, the concept of "cloud auditing" has appeared. As applications in the cloud become more sensitive, the need for auditing systems to provide rapid analysis and quick responses also increases. Machine learning algorithms can be employed for the purposes of providing audit data. Few of these algorithms can be done in an online fashion, however. In this work, we examine one such online machine learning algorithm, and describe how it might be employed in a distributed computing environment. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SERVICES.2013.43 | SERVICES |
Keywords | Field | DocType |
rapid analysis,cloud auditing,online fashion,online machine,audit data,quick response,decentralized nature,real-time cloud auditing paradigm,cloud computing,auditing,learning artificial intelligence | Online machine learning,Data mining,Audit,Distributed Computing Environment,Computer science,Computational learning theory,Database,Computation,Cloud computing,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-0-7695-5024-4 | 0 | 0.34 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert Nix | 1 | 0 | 0.34 |
| Murat Kantarcioglu | 2 | 2470 | 168.03 |
| Sachin Shetty | 3 | 323 | 55.94 |