Name
Abstract | ||
|---|---|---|
The Cloud Security Alliance lists data theft and insider attacks as critical threats to cloud security. Our work puts forth an approach using a train, monitor, detect pattern which leverages a stateful rule based k-nearest neighbors anomaly detection technique and system state data to detect inside attacker data theft on Infrastructure as a Service (IaaS) nodes. We posit, instantiate, and demonstrate our approach using the Eucalyptus cloud computing infrastructure where we observe a 100 percent detection rate for abnormal login events and data copies to outside systems. |
Year | Venue | Field |
|---|---|---|
2016 | IEEE Global Communications Conference | Anomaly detection,Rule-based system,Computer science,Computer security,Login,Computer network,Insider,Cloud computing security,Stateful firewall,Data theft,Cloud computing |
DocType | ISSN | Citations |
Conference | 2334-0983 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jason Nikolai | 1 | 24 | 2.58 |
| Yong Wang | 2 | 93 | 12.91 |