Name
Abstract | ||
|---|---|---|
This paper investigates the issues of malicious transactions by insiders in database systems. It establishes a number of rule sets to constrain the relationship between data items and transactions. A type of graph, called Predictive Dependency Graph, has been developed to determine data flow patterns among data items. This helps in foretelling which operation of a transaction has the ability to subsequently affect a sensitive data item. In addition, the paper proposes a mechanism to monitor suspicious insiders' activities and potential harm to the database. With the help of the Predictive Dependency Graphs, the presented model predicts and prevents potential damage caused by malicious transactions. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-30436-1_18 | INFORMATION SECURITY AND PRIVACY RESEARCH |
Keywords | Field | DocType |
Insider Threat, Transactions, Database, Security | Graph,Computer security,Computer science,Harm,Insider threat,Database transaction,Dependency graph,Data flow diagram | Conference |
Volume | ISSN | Citations |
376 | 1868-4238 | 0 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weihan Li | 1 | 3 | 1.10 |
| Brajendra Panda | 2 | 331 | 39.58 |
| Qussai Yaseen | 3 | 104 | 12.37 |