Towards privacy-anomaly detection: Discovering correlation between privacy and security-anomalies
| Autor: | Barry O'Sullivan, Simon N. Foley, Muhammad Imran Khan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Relational database ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS Data_MISCELLANEOUS Anonymization 020206 networking & telecommunications 02 engineering and technology k-anonymity Anomaly detection computer.software_genre Correlation Electronic privacy K-anonymity 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences Normative ComputingMilieux_COMPUTERSANDSOCIETY 020201 artificial intelligence & image processing Data mining Relational databases computer General Environmental Science |
| Zdroj: | Procedia Computer Science FNC/MobiSPC |
| Popis: | Part of special issue: The 17th International Conference on Mobile Systems and Pervasive Computing (MobiSPC), The 15th International Conference on Future Networks and Communications (FNC),The 10th International Conference on Sustainable Energy Information Technology In this paper a notion of privacy-anomaly detection is presented where normative privacy is modelled using k-anonymity. Based on the model, normative privacy-profiles are constructed, and deviation from normative privacy-profile at runtime is labelled as a privacy-anomaly. Furthermore, the paper investigates whether there is a correlation between security-anomalies and privacy-anomalies, that is, whether the privacy-anomalies labelled by privacy-anomaly detection system are detected by conventional security-anomaly detection system used for detecting malicious accesses to databases by insiders. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|