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Data holders need to share the alerts data that they detected for correlation and analysis purpose. In such cases, privacy issues turn out to be a major concern. This paper proposes a model to correlate and analyze intrusion alerts with privacy-preserving capability. The raw intrusion alerts are protected by improved k-anonymity method, which preserves the alert regulation inside disturbed data records...
Privacy issues are concerned when data holders share their detected security data for correlation and analysis purpose. This paper proposes an approach to correlate and analyze intrusion alerts, while preserve privacy for alert holders. The raw intrusion alerts are protected by improved k-anonymity model, which preserves the alert regulation inside disturbed data records. With this privacy preserving...
Privacy preserving becomes an important issue in the development progress of data mining techniques, especially in distributed data mining. Secure multiparty computation methods are proposed to protect the privacy in distributed environment, but shows low performance under massive nodes. This paper presents an adaptive privacy preserving data mining model based on data perturbation method to improve...
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