Name
Abstract | ||
|---|---|---|
One threat to collaborative intrusion detection systems (CIDSs) is statistic-poisoning attacks. In these attacks, adversaries inject incorrect security sensor reports to the system's repository to corrupt the published attack statistics. A novel, robust approach to computing attack statistics published by CIDSs can help counter this threat. This approach is based on contributor-level aggregation and preferential voting. In experiments, this approach effectively detected large-scale attacks and was more resistant to attacks than the basic approach. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/MSP.2011.97 | IEEE Security & Privacy |
Keywords | Field | DocType |
robust approach,contributor-level aggregation,published attack statistic,computing attack statistic,preferential voting,basic approach,incorrect security sensor report,large-scale attack,intrusion detection system,securing collaborative intrusion detection,intrusion detection,entropy,cybersecurity,collaboration,computer security,privacy,network security | Ranked voting system,Internet privacy,Host-based intrusion detection system,Computer science,Computer security,Network security,Computer network,Intrusion prevention system,Attack tolerance,Intrusion detection system,Alert correlation | Journal |
Volume | Issue | ISSN |
9 | 6 | 1540-7993 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steven Cheung | 1 | 18 | 1.70 |